{"doi": "10.1109/tccn.2023.3306851", "title": "Deep Joint Source-Channel Coding for Image Transmission With Visual Protection", "pdf": "papers/2023_Xu_Deep_Joint_Source_Channel_Coding_for_Image_Transmission_With_Visual_Protection.pdf", "pdf_exists": true, "pdf_sha256": "4f0d82b2601c422f2c808c105865b21cd6f4c6ea3169927acd3aaea77e58cb08", "manifest_sha256": "4f0d82b2601c422f2c808c105865b21cd6f4c6ea3169927acd3aaea77e58cb08", "page_count_extracted": 13, "characters_reflowed": 63083, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 4], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3294754", "title": "Joint Source-Channel Coding for a Multivariate Gaussian Over a Gaussian MAC Using Variational Domain Adaptation", "pdf": "papers/2023_Li_Joint_Source_Channel_Coding_for_a_Multivariate_Gaussian_Over_a_Gaussian_MAC_Using_Variationa.pdf", "pdf_exists": true, "pdf_sha256": "0b4d2b5663d8c7c7b43a483919a73aa3674824305c9aae608c2a1c06031577c7", "manifest_sha256": "0b4d2b5663d8c7c7b43a483919a73aa3674824305c9aae608c2a1c06031577c7", "page_count_extracted": 14, "characters_reflowed": 63241, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3236940", "title": "Neuromorphic Wireless Cognition: Event-Driven Semantic Communications for Remote Inference", "pdf": "papers/2023_Chen_Neuromorphic_Wireless_Cognition_Event_Driven_Semantic_Communications_for_Remote_Inference.pdf", "pdf_exists": true, "pdf_sha256": "25c11e22e157136d9bc926d541545356b434bd602f0a434d6ff74dd570f6ae50", "manifest_sha256": "25c11e22e157136d9bc926d541545356b434bd602f0a434d6ff74dd570f6ae50", "page_count_extracted": 14, "characters_reflowed": 65588, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3306852", "title": "Non-Orthogonal Multiple Access Enhanced Multi-User Semantic Communication", "pdf": "papers/2023_Li_Non_Orthogonal_Multiple_Access_Enhanced_Multi_User_Semantic_Communication.pdf", "pdf_exists": true, "pdf_sha256": "0195d45d5bb08f44257e76f6e6384cfc563cdfdbdeaf05303041bceaab4bb3ef", "manifest_sha256": "0195d45d5bb08f44257e76f6e6384cfc563cdfdbdeaf05303041bceaab4bb3ef", "page_count_extracted": 16, "characters_reflowed": 72124, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 10], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3250206", "title": "Semantics-Native Communication via Contextual Reasoning", "pdf": "papers/2023_Seo_Semantics_Native_Communication_via_Contextual_Reasoning.pdf", "pdf_exists": true, "pdf_sha256": "28ad411e7bb8a3574f0834f9cfc91e9d77045b64837dc2a0c0e6ff7236c44260", "manifest_sha256": "28ad411e7bb8a3574f0834f9cfc91e9d77045b64837dc2a0c0e6ff7236c44260", "page_count_extracted": 14, "characters_reflowed": 76275, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3346481", "title": "Adaptable Semantic Compression and Resource Allocation for Task-Oriented Communications", "pdf": "papers/2024_Liu_Adaptable_Semantic_Compression_and_Resource_Allocation_for_Task_Oriented_Communications.pdf", "pdf_exists": true, "pdf_sha256": "2b2ba65e72e1d959c5b67111cf4a3ea6bb69de409783073f4a70b525f68f8f5e", "manifest_sha256": "2b2ba65e72e1d959c5b67111cf4a3ea6bb69de409783073f4a70b525f68f8f5e", "page_count_extracted": 14, "characters_reflowed": 69774, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3400820", "title": "Adaptive Compression Offloading and Resource Allocation for Edge Vision Computing", "pdf": "papers/2024_Xiao_Adaptive_Compression_Offloading_and_Resource_Allocation_for_Edge_Vision_Computing.pdf", "pdf_exists": true, "pdf_sha256": "1147b5b440a03950baa182d112426e04afbc02758f2a438c827fa2d91207d172", "manifest_sha256": "1147b5b440a03950baa182d112426e04afbc02758f2a438c827fa2d91207d172", "page_count_extracted": 13, "characters_reflowed": 68684, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3315386", "title": "Adaptive Modulation and Retransmission Scheme for Semantic Communication Systems", "pdf": "papers/2024_Gao_Adaptive_Modulation_and_Retransmission_Scheme_for_Semantic_Communication_Systems.pdf", "pdf_exists": true, "pdf_sha256": "8c50ea8ad484e575db31a9bbd162ccbd8f633862782f82cbd62fae26fb2e1285", "manifest_sha256": "8c50ea8ad484e575db31a9bbd162ccbd8f633862782f82cbd62fae26fb2e1285", "page_count_extracted": 14, "characters_reflowed": 68274, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 10}, "selected_pages": [1, 3, 8, 11], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3326302", "title": "DeepMA: End-to-End Deep Multiple Access for Wireless Image Transmission in Semantic Communication", "pdf": "papers/2024_Zhang_DeepMA_End_to_End_Deep_Multiple_Access_for_Wireless_Image_Transmission_in_Semantic_Communica.pdf", "pdf_exists": true, "pdf_sha256": "20b5a27d9f6c1919f993a988b7b4ae647854e19df4ba894e81bab02e3bf8ef9f", "manifest_sha256": "20b5a27d9f6c1919f993a988b7b4ae647854e19df4ba894e81bab02e3bf8ef9f", "page_count_extracted": 16, "characters_reflowed": 77612, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 9, 13], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3375496", "title": "Feature Importance-Aware Task-Oriented Semantic Transmission and Optimization", "pdf": "papers/2024_Wang_Feature_Importance_Aware_Task_Oriented_Semantic_Transmission_and_Optimization.pdf", "pdf_exists": true, "pdf_sha256": "c15172d3c601d151bee086857df0c9da22adde3187547dc9f2db43134ba37ccf", "manifest_sha256": "c15172d3c601d151bee086857df0c9da22adde3187547dc9f2db43134ba37ccf", "page_count_extracted": 15, "characters_reflowed": 72740, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3392803", "title": "How to Evaluate Semantic Communications for Images With ViTScore Metric?", "pdf": "papers/2024_Zhu_How_to_Evaluate_Semantic_Communications_for_Images_With_ViTScore_Metric.pdf", "pdf_exists": true, "pdf_sha256": "d364f0c9b35e26325700ca3dc8345051a5e6c02c5a6b2e2029daac9173c1e61f", "manifest_sha256": "d364f0c9b35e26325700ca3dc8345051a5e6c02c5a6b2e2029daac9173c1e61f", "page_count_extracted": 15, "characters_reflowed": 69465, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3401712", "title": "LaMoSC: Large Language Model-Driven Semantic Communication System for Visual Transmission", "pdf": "papers/2024_Zhao_LaMoSC_Large_Language_Model_Driven_Semantic_Communication_System_for_Visual_Transmission.pdf", "pdf_exists": true, "pdf_sha256": "d2ad9472bcb5cc44f9ef9884d11c55b7fa7389481624fe49f2d28e0278a0b4f1", "manifest_sha256": "d2ad9472bcb5cc44f9ef9884d11c55b7fa7389481624fe49f2d28e0278a0b4f1", "page_count_extracted": 14, "characters_reflowed": 66028, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 12}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3375506", "title": "SC-PNC: Semantic Communication-Empowered Physical-Layer Network Coding", "pdf": "papers/2024_Pan_SC_PNC_Semantic_Communication_Empowered_Physical_Layer_Network_Coding.pdf", "pdf_exists": true, "pdf_sha256": "deed56f947a08717f4bcf0b1265937020e7ce2c3938a4ab86ba40c4383bbdbed", "manifest_sha256": "deed56f947a08717f4bcf0b1265937020e7ce2c3938a4ab86ba40c4383bbdbed", "page_count_extracted": 15, "characters_reflowed": 80103, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 10, 13], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3394867", "title": "SCAN: Semantic Communication With Adaptive Channel Feedback", "pdf": "papers/2024_Zhang_SCAN_Semantic_Communication_With_Adaptive_Channel_Feedback.pdf", "pdf_exists": true, "pdf_sha256": "637602b1d7472cd24411823315fa87ebcae54d805d19b5677334330cde302286", "manifest_sha256": "637602b1d7472cd24411823315fa87ebcae54d805d19b5677334330cde302286", "page_count_extracted": 15, "characters_reflowed": 72588, "section_pages": {"introduction": 1, "method": 2, "experiment": 3, "conclusion": 14}, "selected_pages": [1, 6, 10], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2023.3345858", "title": "Speech Semantic Communication Based on Swin Transformer", "pdf": "papers/2024_Zhou_Speech_Semantic_Communication_Based_on_Swin_Transformer.pdf", "pdf_exists": true, "pdf_sha256": "4ba7309ec2d2e5c9d1c3bd662c4604a4e84b73d1259692d5a33db17034f5ab78", "manifest_sha256": "4ba7309ec2d2e5c9d1c3bd662c4604a4e84b73d1259692d5a33db17034f5ab78", "page_count_extracted": 13, "characters_reflowed": 63945, "section_pages": {"introduction": 1, "method": 4, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 3, 4, 8], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3589577", "title": "A Physical Layer Security Framework for IRS-Assisted Integrated Sensing and Semantic Communication Systems", "pdf": "papers/2025_Amiriara_A_Physical_Layer_Security_Framework_for_IRS_Assisted_Integrated_Sensing_and_Semantic_Communi.pdf", "pdf_exists": true, "pdf_sha256": "ffd0e9cd1ff96bcfdd67340936040023c348306a8994902d03f57bd4c557f2c9", "manifest_sha256": "ffd0e9cd1ff96bcfdd67340936040023c348306a8994902d03f57bd4c557f2c9", "page_count_extracted": 15, "characters_reflowed": 74990, "section_pages": {"introduction": 1, "method": 2, "experiment": 3, "conclusion": 3}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3544275", "title": "A Theory for Semantic Channel Coding With Many-to-One Source", "pdf": "papers/2025_Ma_A_Theory_for_Semantic_Channel_Coding_With_Many_to_One_Source.pdf", "pdf_exists": true, "pdf_sha256": "fa45f9ad3809477454073dd385ce939b2f19dde95d28e60b9836ca2ee5fc2cf6", "manifest_sha256": "fa45f9ad3809477454073dd385ce939b2f19dde95d28e60b9836ca2ee5fc2cf6", "page_count_extracted": 10, "characters_reflowed": 49827, "section_pages": {"introduction": 1, "method": 2, "experiment": 6, "conclusion": 9}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3528891", "title": "Adversarial Attacks Against Shared Knowledge Interpretation in Semantic Communications", "pdf": "papers/2025_Hoang_Adversarial_Attacks_Against_Shared_Knowledge_Interpretation_in_Semantic_Communications.pdf", "pdf_exists": true, "pdf_sha256": "0b0e75856a0ec52c6016e3ce27d7989b72dbe9f6e92cc32f9ee2211bf331c356", "manifest_sha256": "0b0e75856a0ec52c6016e3ce27d7989b72dbe9f6e92cc32f9ee2211bf331c356", "page_count_extracted": 17, "characters_reflowed": 82533, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 16}, "selected_pages": [1, 2, 12], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3543834", "title": "Conceptual Learning and Causal Reasoning for Semantic Communication", "pdf": "papers/2025_Wheeler_Conceptual_Learning_and_Causal_Reasoning_for_Semantic_Communication.pdf", "pdf_exists": true, "pdf_sha256": "7e0824781183af01f1372f52af7da21aebfba16c131e70a377d2ae3ee2a9dc7a", "manifest_sha256": "7e0824781183af01f1372f52af7da21aebfba16c131e70a377d2ae3ee2a9dc7a", "page_count_extracted": 15, "characters_reflowed": 76284, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3438371", "title": "Content Adaptive Distributed Joint Source-Channel Coding for Image Transmission With Hyperprior", "pdf": "papers/2025_Li_Content_Adaptive_Distributed_Joint_Source_Channel_Coding_for_Image_Transmission_With_Hyperpr.pdf", "pdf_exists": true, "pdf_sha256": "b6af11e5789c3994b75429d6a89e353058dd24734199bd05bf9c3949d9e84142", "manifest_sha256": "b6af11e5789c3994b75429d6a89e353058dd24734199bd05bf9c3949d9e84142", "page_count_extracted": 13, "characters_reflowed": 56335, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3549782", "title": "Deep Reinforced Feature Compression and Channel Equalization for Semantic Communications", "pdf": "papers/2025_Seon_Deep_Reinforced_Feature_Compression_and_Channel_Equalization_for_Semantic_Communications.pdf", "pdf_exists": true, "pdf_sha256": "ffc0f766f5e6dc52b5d6b41df7d44b89b3fcb340ea0b4df13614a7606f8bd83b", "manifest_sha256": "ffc0f766f5e6dc52b5d6b41df7d44b89b3fcb340ea0b4df13614a7606f8bd83b", "page_count_extracted": 14, "characters_reflowed": 67272, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 12}, "selected_pages": [1, 3, 10], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3533008", "title": "Digital Semantic Communication System With a Learnable Channel Estimator for OFDM Transmission", "pdf": "papers/2025_Feng_Digital_Semantic_Communication_System_With_a_Learnable_Channel_Estimator_for_OFDM_Transmissi.pdf", "pdf_exists": true, "pdf_sha256": "0a46fe1c429192c38807c09d51fff0d36ea444b8fb9742500e2bdc9d7516d73a", "manifest_sha256": "0a46fe1c429192c38807c09d51fff0d36ea444b8fb9742500e2bdc9d7516d73a", "page_count_extracted": 10, "characters_reflowed": 45080, "section_pages": {"introduction": 1, "method": 2, "experiment": 6, "conclusion": 9}, "selected_pages": [1, 2, 5], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3510586", "title": "Digital-SC: Digital Semantic Communication With Adaptive Network Split and Learned Non-Linear Quantization", "pdf": "papers/2025_Guo_Digital_SC_Digital_Semantic_Communication_With_Adaptive_Network_Split_and_Learned_Non_Linear.pdf", "pdf_exists": true, "pdf_sha256": "6c04ffbd3f18caae255938323f2ddf78f63701906c2eac5dc91f0749f7328859", "manifest_sha256": "6c04ffbd3f18caae255938323f2ddf78f63701906c2eac5dc91f0749f7328859", "page_count_extracted": 13, "characters_reflowed": 67027, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 7], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3543387", "title": "EESC-S: An Emotion-Enhanced Semantic Communication Framework for Speech Transmission", "pdf": "papers/2025_Tan_EESC_S_An_Emotion_Enhanced_Semantic_Communication_Framework_for_Speech_Transmission.pdf", "pdf_exists": true, "pdf_sha256": "1a96c63e5eacdac6aece7d75e70a1d2264029438c08e49fbb721464b1794c2d0", "manifest_sha256": "1a96c63e5eacdac6aece7d75e70a1d2264029438c08e49fbb721464b1794c2d0", "page_count_extracted": 14, "characters_reflowed": 69096, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3592294", "title": "Fluid Antenna-Enabled Near-Field Integrated Sensing, Computing, and Semantic Communication for Emerging Applications", "pdf": "papers/2025_Yang_Fluid_Antenna_Enabled_Near_Field_Integrated_Sensing_Computing_and_Semantic_Communication_for.pdf", "pdf_exists": true, "pdf_sha256": "25ae59b64a1fb5e87d78e51f1b14e9dfbacc42f100aa5b2f9dfb75be98937d9f", "manifest_sha256": "25ae59b64a1fb5e87d78e51f1b14e9dfbacc42f100aa5b2f9dfb75be98937d9f", "page_count_extracted": 17, "characters_reflowed": 87979, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 16}, "selected_pages": [1, 9, 14], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3520132", "title": "GAI-Enhanced Robust Semantic Communication With Asymmetric Architecture", "pdf": "papers/2025_Ren_GAI_Enhanced_Robust_Semantic_Communication_With_Asymmetric_Architecture.pdf", "pdf_exists": true, "pdf_sha256": "776e089cec9e5cf1bed465877d7ef630eeac2c6cac75a862c86d95a9cc7403bb", "manifest_sha256": "776e089cec9e5cf1bed465877d7ef630eeac2c6cac75a862c86d95a9cc7403bb", "page_count_extracted": 12, "characters_reflowed": 56534, "section_pages": {"introduction": 1, "method": 2, "experiment": 7, "conclusion": 11}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3529692", "title": "Generative AI Empowered Semantic Feature Multiple Access (SFMA) Over Wireless Networks", "pdf": "papers/2025_Wang_Generative_AI_Empowered_Semantic_Feature_Multiple_Access_SFMA_Over_Wireless_Networks.pdf", "pdf_exists": true, "pdf_sha256": "c0c82faf4ce8a43b0de5d1a3194ddfe8bf547f26fe10a29b9a8b73ed2f6111aa", "manifest_sha256": "c0c82faf4ce8a43b0de5d1a3194ddfe8bf547f26fe10a29b9a8b73ed2f6111aa", "page_count_extracted": 14, "characters_reflowed": 67737, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1, 4], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3567613", "title": "Generative AI Meets Wireless Networking: An Interactive Paradigm for Intent-Driven Communications", "pdf": "papers/2025_Qin_Generative_AI_Meets_Wireless_Networking_An_Interactive_Paradigm_for_Intent_Driven_Communicat.pdf", "pdf_exists": true, "pdf_sha256": "cd9bde1b59fc3194229040971ea40a39a68afd723c98dbe6b118033d5b5d9b40", "manifest_sha256": "cd9bde1b59fc3194229040971ea40a39a68afd723c98dbe6b118033d5b5d9b40", "page_count_extracted": 22, "characters_reflowed": 117955, "section_pages": {"introduction": 1, "method": 2, "experiment": 13, "conclusion": 21}, "selected_pages": [1, 4, 22], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3556751", "title": "Generative AI-Driven Incentive Mechanism for Semantic Communications in RSMA Networks", "pdf": "papers/2025_Liu_Generative_AI_Driven_Incentive_Mechanism_for_Semantic_Communications_in_RSMA_Networks.pdf", "pdf_exists": true, "pdf_sha256": "f93f04c3f4ef14ddab5dffd202dbcf1f8f399a57dca0f92177bada207533c926", "manifest_sha256": "f93f04c3f4ef14ddab5dffd202dbcf1f8f399a57dca0f92177bada207533c926", "page_count_extracted": 15, "characters_reflowed": 78187, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3435524", "title": "Generative AI-Driven Semantic Communication Networks: Architecture, Technologies, and Applications", "pdf": "papers/2025_Liang_Generative_AI_Driven_Semantic_Communication_Networks_Architecture_Technologies_and_Applicati.pdf", "pdf_exists": true, "pdf_sha256": "e44e06d239072a61f3264c320e0b573b4e2e35a4c7f17c22163acdfa9ebae192", "manifest_sha256": "e44e06d239072a61f3264c320e0b573b4e2e35a4c7f17c22163acdfa9ebae192", "page_count_extracted": 21, "characters_reflowed": 116157, "section_pages": {"introduction": 1, "method": 2, "experiment": 13, "conclusion": 20}, "selected_pages": [1, 3, 12], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3544282", "title": "Heterogeneous Gateway Planning for Semantic Communication in Industrial Networks", "pdf": "papers/2025_Sun_Heterogeneous_Gateway_Planning_for_Semantic_Communication_in_Industrial_Networks.pdf", "pdf_exists": true, "pdf_sha256": "447ee7f8eb5b490d06a3e72c232b2e4c95ce662689b98cde064e5f5b49ecb28e", "manifest_sha256": "447ee7f8eb5b490d06a3e72c232b2e4c95ce662689b98cde064e5f5b49ecb28e", "page_count_extracted": 13, "characters_reflowed": 65256, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3422496", "title": "Joint Source-Channel Coding for Channel-Adaptive Digital Semantic Communications", "pdf": "papers/2025_Park_Joint_Source_Channel_Coding_for_Channel_Adaptive_Digital_Semantic_Communications.pdf", "pdf_exists": true, "pdf_sha256": "5aaef9b4f7cacd3a9c1f84d4d7ee0be1c00bf7b526bccc8d6393452d11f2c093", "manifest_sha256": "5aaef9b4f7cacd3a9c1f84d4d7ee0be1c00bf7b526bccc8d6393452d11f2c093", "page_count_extracted": 15, "characters_reflowed": 77124, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2, 8], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3531461", "title": "Model-Enabled Task-Oriented Semantic Communications Through Knowledge Synchronization", "pdf": "papers/2025_Tian_Model_Enabled_Task_Oriented_Semantic_Communications_Through_Knowledge_Synchronization.pdf", "pdf_exists": true, "pdf_sha256": "8b9d889280617451035f244a0c005e53f061733d058c32f5996569bc90705bf7", "manifest_sha256": "8b9d889280617451035f244a0c005e53f061733d058c32f5996569bc90705bf7", "page_count_extracted": 13, "characters_reflowed": 65887, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 8], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3529747", "title": "Optimizing Resource Allocation for Multi-Modal Semantic Communication in Mobile AIGC Networks: A Diffusion-Based Game Approach", "pdf": "papers/2025_Liu_Optimizing_Resource_Allocation_for_Multi_Modal_Semantic_Communication_in_Mobile_AIGC_Network.pdf", "pdf_exists": true, "pdf_sha256": "38314e044a0fe8aef60dd5dc3a1ec7c6d57f68d368328b5156222ace511f07e0", "manifest_sha256": "38314e044a0fe8aef60dd5dc3a1ec7c6d57f68d368328b5156222ace511f07e0", "page_count_extracted": 15, "characters_reflowed": 70043, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3546935", "title": "Progressive Learned Image Transmission for Semantic Communication Using Hierarchical VAE", "pdf": "papers/2025_Zhang_Progressive_Learned_Image_Transmission_for_Semantic_Communication_Using_Hierarchical_VAE.pdf", "pdf_exists": true, "pdf_sha256": "c9d2b355286341ed6227777973cf3e0064cd3e5bbf588a7cc46acaa11325f7a1", "manifest_sha256": "c9d2b355286341ed6227777973cf3e0064cd3e5bbf588a7cc46acaa11325f7a1", "page_count_extracted": 15, "characters_reflowed": 73384, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1, 10, 12], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3452053", "title": "R-UAV-Net: Enhanced YOLOv4 With Graph-Semantic Compression for Transformative UAV Sensing in Paddy Agronomy", "pdf": "papers/2025_Sangaiah_R_UAV_Net_Enhanced_YOLOv4_With_Graph_Semantic_Compression_for_Transformative_UAV_Sensing_in.pdf", "pdf_exists": true, "pdf_sha256": "e4efc9dadca81065cf0dd8aee2b7a73014d3e039eb3f9a816dde7f93b0a778b8", "manifest_sha256": "e4efc9dadca81065cf0dd8aee2b7a73014d3e039eb3f9a816dde7f93b0a778b8", "page_count_extracted": 13, "characters_reflowed": 62784, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3511960", "title": "Rate-Distortion-Perception Controllable Joint Source-Channel Coding for High-Fidelity Generative Semantic Communications", "pdf": "papers/2025_Tan_Rate_Distortion_Perception_Controllable_Joint_Source_Channel_Coding_for_High_Fidelity_Genera.pdf", "pdf_exists": true, "pdf_sha256": "6bb6bef18deefce5a4c8a606c607a52878a37bf2efa2ec6a8d450cd67235fb24", "manifest_sha256": "6bb6bef18deefce5a4c8a606c607a52878a37bf2efa2ec6a8d450cd67235fb24", "page_count_extracted": 15, "characters_reflowed": 75809, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2, 11, 12, 14], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3451724", "title": "Semantic Image Encoding and Communication for Earth Observation With LEO Satellites", "pdf": "papers/2025_Bui_Semantic_Image_Encoding_and_Communication_for_Earth_Observation_With_LEO_Satellites.pdf", "pdf_exists": true, "pdf_sha256": "35eedcb9181bbf03862fcc7b322a95be430f2c5e77c75438a2253980302623a0", "manifest_sha256": "35eedcb9181bbf03862fcc7b322a95be430f2c5e77c75438a2253980302623a0", "page_count_extracted": 15, "characters_reflowed": 74348, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3482354", "title": "Semantic Information Extraction and Multi-Agent Communication Optimization Based on Generative Pre-Trained Transformer", "pdf": "papers/2025_Zhou_Semantic_Information_Extraction_and_Multi_Agent_Communication_Optimization_Based_on_Generati.pdf", "pdf_exists": true, "pdf_sha256": "0187ccb60e6a69a19a0a472f870d748b3fa9c9a7dcebdd40f091aebd19f7e09b", "manifest_sha256": "0187ccb60e6a69a19a0a472f870d748b3fa9c9a7dcebdd40f091aebd19f7e09b", "page_count_extracted": 13, "characters_reflowed": 59784, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 4], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3526839", "title": "Semantic Successive Refinement: A Generative AI-Aided Semantic Communication Framework", "pdf": "papers/2025_Zhang_Semantic_Successive_Refinement_A_Generative_AI_Aided_Semantic_Communication_Framework.pdf", "pdf_exists": true, "pdf_sha256": "54b784754b59fc961adf2d5ab942934e5867da960e1df2aaeac63577b6500394", "manifest_sha256": "54b784754b59fc961adf2d5ab942934e5867da960e1df2aaeac63577b6500394", "page_count_extracted": 13, "characters_reflowed": 67151, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 9], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3417627", "title": "Semantic Utility Loss of Information for Energy Efficient Semantic Status Update Communications", "pdf": "papers/2025_Xu_Semantic_Utility_Loss_of_Information_for_Energy_Efficient_Semantic_Status_Update_Communicati.pdf", "pdf_exists": true, "pdf_sha256": "f925e8e84d9e2dd9b0615d5175ebb031eba18afde0df8b39e8fb54e460e9fb1b", "manifest_sha256": "f925e8e84d9e2dd9b0615d5175ebb031eba18afde0df8b39e8fb54e460e9fb1b", "page_count_extracted": 16, "characters_reflowed": 80086, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 12}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3522140", "title": "SINR-Adaptive and CBR-Controllable Semantic Cellular Communication Considering Imperfect CSI and Inter-Cell Co-Channel Interference", "pdf": "papers/2025_Niu_SINR_Adaptive_and_CBR_Controllable_Semantic_Cellular_Communication_Considering_Imperfect_CSI.pdf", "pdf_exists": true, "pdf_sha256": "811f9462582de4a7c4783eb9e8f218c6b9b5eeda04f9b79c9b2cf6b8c22e658f", "manifest_sha256": "811f9462582de4a7c4783eb9e8f218c6b9b5eeda04f9b79c9b2cf6b8c22e658f", "page_count_extracted": 18, "characters_reflowed": 85972, "section_pages": {"introduction": 1, "method": 2, "experiment": 11, "conclusion": 17}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3424842", "title": "SwinJSCC: Taming Swin Transformer for Deep Joint Source-Channel Coding", "pdf": "papers/2025_Yang_SwinJSCC_Taming_Swin_Transformer_for_Deep_Joint_Source_Channel_Coding.pdf", "pdf_exists": true, "pdf_sha256": "e0a91a87726a233edebb580f272c26bd3cdcdd37cacb069951902c788b92ecff", "manifest_sha256": "e0a91a87726a233edebb580f272c26bd3cdcdd37cacb069951902c788b92ecff", "page_count_extracted": 15, "characters_reflowed": 62180, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2, 6, 8], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2024.3465651", "title": "Task-Oriented Communication for Graph Data: A Graph Information Bottleneck Approach", "pdf": "papers/2025_Li_Task_Oriented_Communication_for_Graph_Data_A_Graph_Information_Bottleneck_Approach.pdf", "pdf_exists": true, "pdf_sha256": "e0172bfb5ac0edffeef068e1193a438f87d6caa37d02a51e5ee11a4bc99f76f5", "manifest_sha256": "e0172bfb5ac0edffeef068e1193a438f87d6caa37d02a51e5ee11a4bc99f76f5", "page_count_extracted": 15, "characters_reflowed": 71192, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 8], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3720357", "title": "3-D Gaussian SLAM Based on Joint Source-Channel Coding and Multi-Scale Constraints", "pdf": "papers/2026_Liu_3_D_Gaussian_SLAM_Based_on_Joint_Source_Channel_Coding_and_Multi_Scale_Constraints.pdf", "pdf_exists": true, "pdf_sha256": "e866be9d16481084eade39b8a38c1ba1049295d44a4d8dc9ef121e5d3ef83d61", "manifest_sha256": "e866be9d16481084eade39b8a38c1ba1049295d44a4d8dc9ef121e5d3ef83d61", "page_count_extracted": 15, "characters_reflowed": 80672, "section_pages": {"introduction": 1, "method": 4, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3712130", "title": "6G-Oriented Semantic Extraction in Semantic Communications: From DL to Large AI Models", "pdf": "papers/2026_Wei_6G_Oriented_Semantic_Extraction_in_Semantic_Communications_From_DL_to_Large_AI_Models.pdf", "pdf_exists": true, "pdf_sha256": "37767cc02eac657001476bd3ac0ddcc2c545845e6f5b95aa1cc8424b8785f709", "manifest_sha256": "37767cc02eac657001476bd3ac0ddcc2c545845e6f5b95aa1cc8424b8785f709", "page_count_extracted": 21, "characters_reflowed": 112915, "section_pages": {"introduction": 1, "method": 2, "experiment": 13, "conclusion": 15}, "selected_pages": [1, 8, 13], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3670165", "title": "A Dynamic Adaptive Deep Coding-Classification Framework for Intelligent Pragmatic Tasks in Semantic Communication", "pdf": "papers/2026_Yan_A_Dynamic_Adaptive_Deep_Coding_Classification_Framework_for_Intelligent_Pragmatic_Tasks_in_S.pdf", "pdf_exists": true, "pdf_sha256": "26fe0399a05bb05259e4b1b46047e96a593144f207ed29c5de17a7bf3fdaafcf", "manifest_sha256": "26fe0399a05bb05259e4b1b46047e96a593144f207ed29c5de17a7bf3fdaafcf", "page_count_extracted": 16, "characters_reflowed": 75140, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 12], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3705838", "title": "A Learned Network Coding Scheme for Robust Image Transmission in Lossy Relay Networks", "pdf": "papers/2026_Shen_A_Learned_Network_Coding_Scheme_for_Robust_Image_Transmission_in_Lossy_Relay_Networks.pdf", "pdf_exists": true, "pdf_sha256": "f48f0bd5b9c3f26047de2407a8fcb6119e4fea9589b3ac1c80be501c6d9c264f", "manifest_sha256": "f48f0bd5b9c3f26047de2407a8fcb6119e4fea9589b3ac1c80be501c6d9c264f", "page_count_extracted": 16, "characters_reflowed": 71381, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 10}, "selected_pages": [1, 2, 9], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3721535", "title": "A Lite Robust Semantic Communication (LRSC) Scheme via Enhancing Fidelity", "pdf": "papers/2026_Dong_A_Lite_Robust_Semantic_Communication_LRSC_Scheme_via_Enhancing_Fidelity.pdf", "pdf_exists": true, "pdf_sha256": "5feb4496864359f042b8234a1329b2bcc4638f4cb4b033f628f2aea68f21d73f", "manifest_sha256": "5feb4496864359f042b8234a1329b2bcc4638f4cb4b033f628f2aea68f21d73f", "page_count_extracted": 13, "characters_reflowed": 70119, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 11}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3637049", "title": "A Semantic-Aware Resource Allocation for Emerging AAV-NOMA Networks Empowered by Bayesian Active Inference", "pdf": "papers/2026_Krayani_A_Semantic_Aware_Resource_Allocation_for_Emerging_AAV_NOMA_Networks_Empowered_by_Bayesian_Ac.pdf", "pdf_exists": true, "pdf_sha256": "c41c8a57e15d96775a720c1dbf2a0d45328d3e1f59da0e6cfcf521858c95c194", "manifest_sha256": "c41c8a57e15d96775a720c1dbf2a0d45328d3e1f59da0e6cfcf521858c95c194", "page_count_extracted": 18, "characters_reflowed": 85541, "section_pages": {"introduction": 1, "method": 2, "experiment": 11, "conclusion": 17}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3561304", "title": "Adaptive Cross-Modal Super-Resolution Semantic Communication for Mobile AI-Generated Panoramic Video", "pdf": "papers/2026_Gao_Adaptive_Cross_Modal_Super_Resolution_Semantic_Communication_for_Mobile_AI_Generated_Panoram.pdf", "pdf_exists": true, "pdf_sha256": "90703a5cd963af2da6dd6afca448ec51fb41f0c50168a2d5ac79a594bedadcdf", "manifest_sha256": "90703a5cd963af2da6dd6afca448ec51fb41f0c50168a2d5ac79a594bedadcdf", "page_count_extracted": 16, "characters_reflowed": 73432, "section_pages": {"introduction": 1, "method": 2, "experiment": 2, "conclusion": 2}, "selected_pages": [1, 10], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3662328", "title": "Adaptive Frame Interpolation Symbolic Semantic Communication for Low Latency Wireless Video Transmission", "pdf": "papers/2026_Qi_Adaptive_Frame_Interpolation_Symbolic_Semantic_Communication_for_Low_Latency_Wireless_Video.pdf", "pdf_exists": true, "pdf_sha256": "6028866b15aaee6b76195370cfd77bf2b485c3aaa66b54b5edb2602052002d5c", "manifest_sha256": "6028866b15aaee6b76195370cfd77bf2b485c3aaa66b54b5edb2602052002d5c", "page_count_extracted": 16, "characters_reflowed": 65783, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 6], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3692647", "title": "Adaptive Semantic Image Transmission With Object Prioritization and Over-the-Air Validation", "pdf": "papers/2026_Ding_Adaptive_Semantic_Image_Transmission_With_Object_Prioritization_and_Over_the_Air_Validation.pdf", "pdf_exists": true, "pdf_sha256": "ec41c10bbd6eeadac3fd3aba9f9f688d5d1b5f7c10adba357446658d7db3e851", "manifest_sha256": "ec41c10bbd6eeadac3fd3aba9f9f688d5d1b5f7c10adba357446658d7db3e851", "page_count_extracted": 15, "characters_reflowed": 71806, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3657061", "title": "Channel-Adaptive Cross-Modal Generative Semantic Communication for Point Cloud Transmission", "pdf": "papers/2026_Yang_Channel_Adaptive_Cross_Modal_Generative_Semantic_Communication_for_Point_Cloud_Transmission.pdf", "pdf_exists": true, "pdf_sha256": "fc2c0cbefb0ce6d46ed87361521545a13d8e154d9b512ea040bbc2376f813762", "manifest_sha256": "fc2c0cbefb0ce6d46ed87361521545a13d8e154d9b512ea040bbc2376f813762", "page_count_extracted": 16, "characters_reflowed": 72259, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 10], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3689868", "title": "Channel-Adaptive Semantic Communication for Stereoscopic Media: Design and Prototype Implementation", "pdf": "papers/2026_Men_Channel_Adaptive_Semantic_Communication_for_Stereoscopic_Media_Design_and_Prototype_Implemen.pdf", "pdf_exists": true, "pdf_sha256": "61743818006102e68ec573ad5985a31a6238c1efbd56d829e3198ab572db2ec6", "manifest_sha256": "61743818006102e68ec573ad5985a31a6238c1efbd56d829e3198ab572db2ec6", "page_count_extracted": 17, "characters_reflowed": 80578, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 14}, "selected_pages": [1, 9], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3705851", "title": "Channel-Aware Latent Flow-Matching Semantic Communication for Agentic AI", "pdf": "papers/2026_Zhang_Channel_Aware_Latent_Flow_Matching_Semantic_Communication_for_Agentic_AI.pdf", "pdf_exists": true, "pdf_sha256": "c7f39bd3f64e225062e5801998aea346529503de59bf7edbdc4a6301de611bc0", "manifest_sha256": "c7f39bd3f64e225062e5801998aea346529503de59bf7edbdc4a6301de611bc0", "page_count_extracted": 13, "characters_reflowed": 56966, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 3, 9], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3598379", "title": "Complex Valued Linear Discriminant Analysis on mmWave Radar Face Signatures for Task-Oriented Semantic Communication", "pdf": "papers/2026_Baby_Complex_Valued_Linear_Discriminant_Analysis_on_mmWave_Radar_Face_Signatures_for_Task_Oriente.pdf", "pdf_exists": true, "pdf_sha256": "367ff3860a6e007a58df4d26bbe3e49f4ded98ea83949ec2e3ecee71d76d6c62", "manifest_sha256": "367ff3860a6e007a58df4d26bbe3e49f4ded98ea83949ec2e3ecee71d76d6c62", "page_count_extracted": 13, "characters_reflowed": 57651, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3705844", "title": "Conquering High Packet-Loss Erasure: MoE Swin Transformer-Based Video Semantic Communication", "pdf": "papers/2026_Teng_Conquering_High_Packet_Loss_Erasure_MoE_Swin_Transformer_Based_Video_Semantic_Communication.pdf", "pdf_exists": true, "pdf_sha256": "fd2278bbfe4fd2a085a71bebfe859b8fc94407431e6d704e62506a077e7f8aaf", "manifest_sha256": "fd2278bbfe4fd2a085a71bebfe859b8fc94407431e6d704e62506a077e7f8aaf", "page_count_extracted": 18, "characters_reflowed": 73716, "section_pages": {"introduction": 1, "method": 2, "experiment": 11, "conclusion": 17}, "selected_pages": [1, 2, 8, 12], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3637040", "title": "Content-Aware Scheduling Policy for Goal-Oriented Status Updating With Multiple Sources", "pdf": "papers/2026_Peng_Content_Aware_Scheduling_Policy_for_Goal_Oriented_Status_Updating_With_Multiple_Sources.pdf", "pdf_exists": true, "pdf_sha256": "284f5f913d2bb21ef806d9e4e14506c7187b6f2dd42f5dfa946b7172720621d3", "manifest_sha256": "284f5f913d2bb21ef806d9e4e14506c7187b6f2dd42f5dfa946b7172720621d3", "page_count_extracted": 13, "characters_reflowed": 63113, "section_pages": {"introduction": 1, "method": 2, "experiment": 2, "conclusion": 12}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3677171", "title": "Convolutional Autoencoder-Enhanced Semantic Communication in Optical Fiber Systems", "pdf": "papers/2026_Cai_Convolutional_Autoencoder_Enhanced_Semantic_Communication_in_Optical_Fiber_Systems.pdf", "pdf_exists": true, "pdf_sha256": "d2742d07f6cea8028b609f05938ec89c3ae2135d28615d6be018c7a31b3c1a44", "manifest_sha256": "d2742d07f6cea8028b609f05938ec89c3ae2135d28615d6be018c7a31b3c1a44", "page_count_extracted": 13, "characters_reflowed": 59493, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 2, 8], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3695848", "title": "Cross-Domain Semantic Image Communication Empowered by LEO Embodied Intelligence", "pdf": "papers/2026_Zhang_Cross_Domain_Semantic_Image_Communication_Empowered_by_LEO_Embodied_Intelligence.pdf", "pdf_exists": true, "pdf_sha256": "1b3d9011d99870c952db092fdc776c69e40ebea904de4f6337a1047571b6330c", "manifest_sha256": "1b3d9011d99870c952db092fdc776c69e40ebea904de4f6337a1047571b6330c", "page_count_extracted": 13, "characters_reflowed": 59252, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 4], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3706089", "title": "D-SIC: Energy-Efficient Digital Semantic Image Communication via Large Generative Models", "pdf": "papers/2026_Khalid_D_SIC_Energy_Efficient_Digital_Semantic_Image_Communication_via_Large_Generative_Models.pdf", "pdf_exists": true, "pdf_sha256": "cc30a23758e8cca4cb0d2d55b6438259bb562bfb83402359072325b40507fc6d", "manifest_sha256": "cc30a23758e8cca4cb0d2d55b6438259bb562bfb83402359072325b40507fc6d", "page_count_extracted": 16, "characters_reflowed": 70793, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 14}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3705826", "title": "DiT-JSCC: Rethinking Deep JSCC With Diffusion Transformers and Semantic Representations", "pdf": "papers/2026_Tan_DiT_JSCC_Rethinking_Deep_JSCC_With_Diffusion_Transformers_and_Semantic_Representations.pdf", "pdf_exists": true, "pdf_sha256": "3c5c9e41b51a2323046fc426f4d435a6b823291c51cab939e5510d27df0fc8ac", "manifest_sha256": "3c5c9e41b51a2323046fc426f4d435a6b823291c51cab939e5510d27df0fc8ac", "page_count_extracted": 16, "characters_reflowed": 76591, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 3], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3658783", "title": "Frame-Based Zero-Shot Semantic Channel Equalization for AI-Native Communications", "pdf": "papers/2026_Fiorellino_Frame_Based_Zero_Shot_Semantic_Channel_Equalization_for_AI_Native_Communications.pdf", "pdf_exists": true, "pdf_sha256": "0c75be3e561ffe0ef1a6552bc66d2cb00249a6b15e229f327218ebfa5573d9cf", "manifest_sha256": "0c75be3e561ffe0ef1a6552bc66d2cb00249a6b15e229f327218ebfa5573d9cf", "page_count_extracted": 16, "characters_reflowed": 81414, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 15], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3662333", "title": "From Local to Global: Semantic Communication-Driven Remote 3D Scene Reconstruction Using Low-Altitude Platforms", "pdf": "papers/2026_Mai_From_Local_to_Global_Semantic_Communication_Driven_Remote_3D_Scene_Reconstruction_Using_Low.pdf", "pdf_exists": true, "pdf_sha256": "d21b72c93f30413900986800b37ae371065473e40a98d87658209e3a0d53c18e", "manifest_sha256": "d21b72c93f30413900986800b37ae371065473e40a98d87658209e3a0d53c18e", "page_count_extracted": 14, "characters_reflowed": 58694, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3709876", "title": "GDE: A Generative Diffusion Equalizer for ICSI-Free Semantic Communications in SAGINs", "pdf": "papers/2026_Shi_GDE_A_Generative_Diffusion_Equalizer_for_ICSI_Free_Semantic_Communications_in_SAGINs.pdf", "pdf_exists": true, "pdf_sha256": "59c48c3aa3f87367eee8cb173640c970e354b5212fe6ac979abef89e99bfa236", "manifest_sha256": "59c48c3aa3f87367eee8cb173640c970e354b5212fe6ac979abef89e99bfa236", "page_count_extracted": 15, "characters_reflowed": 75508, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 12}, "selected_pages": [1, 3], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3689849", "title": "Generative Semantic Communication: Diffusion Models Beyond Bit Recovery", "pdf": "papers/2026_Grassucci_Generative_Semantic_Communication_Diffusion_Models_Beyond_Bit_Recovery.pdf", "pdf_exists": true, "pdf_sha256": "cdbc00317fd83fcb0b76764fb1c221b57c8ec3cfee5644a505571bd05073c9a8", "manifest_sha256": "cdbc00317fd83fcb0b76764fb1c221b57c8ec3cfee5644a505571bd05073c9a8", "page_count_extracted": 15, "characters_reflowed": 74294, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2, 11], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3710171", "title": "Group-Level Feature-Aware Hybrid Coding for Adaptive Task-Oriented Tactile Communication", "pdf": "papers/2026_Zhang_Group_Level_Feature_Aware_Hybrid_Coding_for_Adaptive_Task_Oriented_Tactile_Communication.pdf", "pdf_exists": true, "pdf_sha256": "ae3550533cd3d7d9065836d395c78bd300b68eeb8f5bff3274effe4d44244c5e", "manifest_sha256": "ae3550533cd3d7d9065836d395c78bd300b68eeb8f5bff3274effe4d44244c5e", "page_count_extracted": 14, "characters_reflowed": 70827, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 10}, "selected_pages": [1, 2, 6], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3657147", "title": "High Quality and Secure Speech Transmission at Low Bitrate via Semantic-Acoustic Hybrid Coding for Low-Altitude Intelligent Systems", "pdf": "papers/2026_Chen_High_Quality_and_Secure_Speech_Transmission_at_Low_Bitrate_via_Semantic_Acoustic_Hybrid_Codi.pdf", "pdf_exists": true, "pdf_sha256": "e2bd6cf516fcf6766a8bbe99de15d69e64af5c734194920b977f90a4de0d12a5", "manifest_sha256": "e2bd6cf516fcf6766a8bbe99de15d69e64af5c734194920b977f90a4de0d12a5", "page_count_extracted": 11, "characters_reflowed": 54663, "section_pages": {"introduction": 1, "method": 3, "experiment": 7, "conclusion": 10}, "selected_pages": [1, 7], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3666538", "title": "Joint Semantic Compression and Massive MIMO Transmission for Edge Video Analytics", "pdf": "papers/2026_Cui_Joint_Semantic_Compression_and_Massive_MIMO_Transmission_for_Edge_Video_Analytics.pdf", "pdf_exists": true, "pdf_sha256": "f5a14e5e5a8b8394f6e6d6dd07cc5ffff5df2796c07cdb6c831786500a3c2258", "manifest_sha256": "f5a14e5e5a8b8394f6e6d6dd07cc5ffff5df2796c07cdb6c831786500a3c2258", "page_count_extracted": 15, "characters_reflowed": 72665, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3626348", "title": "Joint Trajectory Planning and Semantic Communication Design for Urban Low-Altitude UAVs", "pdf": "papers/2026_Feng_Joint_Trajectory_Planning_and_Semantic_Communication_Design_for_Urban_Low_Altitude_UAVs.pdf", "pdf_exists": true, "pdf_sha256": "38865a1aad72e826792404ac94fe56366a540b392c2594cad9f9cb6844ee486e", "manifest_sha256": "38865a1aad72e826792404ac94fe56366a540b392c2594cad9f9cb6844ee486e", "page_count_extracted": 16, "characters_reflowed": 71894, "section_pages": {"introduction": 1, "method": 2, "experiment": 2, "conclusion": 2}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3641514", "title": "Knowledge-Driven 3D Semantic Spectrum Map: KE-VQ-Transformer-Based AAV Semantic Communication and Map Completion", "pdf": "papers/2026_Wu_Knowledge_Driven_3D_Semantic_Spectrum_Map_KE_VQ_Transformer_Based_AAV_Semantic_Communication.pdf", "pdf_exists": true, "pdf_sha256": "5880be5537b7ce21093aec4bb7b46fe1baffb946e9c52a8f2602fdc7e04a03ef", "manifest_sha256": "5880be5537b7ce21093aec4bb7b46fe1baffb946e9c52a8f2602fdc7e04a03ef", "page_count_extracted": 16, "characters_reflowed": 78526, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 11], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3657116", "title": "Lagrangian-Augmented Learning for Stochastic Age of Accurate Semantic Information Minimization in Mobile Edge Computing Systems", "pdf": "papers/2026_Zhuang_Lagrangian_Augmented_Learning_for_Stochastic_Age_of_Accurate_Semantic_Information_Minimizati.pdf", "pdf_exists": true, "pdf_sha256": "5eb20c61298d2df7a570134e6f0283de510856ed25e84853cd364b367783f2b6", "manifest_sha256": "5eb20c61298d2df7a570134e6f0283de510856ed25e84853cd364b367783f2b6", "page_count_extracted": 16, "characters_reflowed": 80406, "section_pages": {"introduction": 1, "method": 2, "experiment": 2, "conclusion": 2}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3687590", "title": "Large-Scale Model-Enabled Semantic Communication via Robust Knowledge Distillation and Lightweight Architecture Search", "pdf": "papers/2026_Ding_Large_Scale_Model_Enabled_Semantic_Communication_via_Robust_Knowledge_Distillation_and_Light.pdf", "pdf_exists": true, "pdf_sha256": "0a5fb80919f61fef8f2cd9e202c64c60e2ff4dc9259d4061b9f87fdb9a203ea6", "manifest_sha256": "0a5fb80919f61fef8f2cd9e202c64c60e2ff4dc9259d4061b9f87fdb9a203ea6", "page_count_extracted": 15, "characters_reflowed": 69037, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2, 11], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3642880", "title": "LLM-Empowered Semantic Communication for Multi-Task 3D Scene Understanding in Low-Altitude Economy Networks", "pdf": "papers/2026_Wang_LLM_Empowered_Semantic_Communication_for_Multi_Task_3D_Scene_Understanding_in_Low_Altitude_E.pdf", "pdf_exists": true, "pdf_sha256": "9d7826b577282d17fa5b4c5a9db29a1df9c9376f6f5ea50abdcbb1e13d0ba899", "manifest_sha256": "9d7826b577282d17fa5b4c5a9db29a1df9c9376f6f5ea50abdcbb1e13d0ba899", "page_count_extracted": 15, "characters_reflowed": 74577, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 10], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3588246", "title": "LRGD: Low-Rank Guided Diffusion for Robust Image Transmission in Semantic Communication", "pdf": "papers/2026_Zhao_LRGD_Low_Rank_Guided_Diffusion_for_Robust_Image_Transmission_in_Semantic_Communication.pdf", "pdf_exists": true, "pdf_sha256": "547db0f791454039309f632d0d3947eb27991f7d26ff896a3316b7220a8c5a2f", "manifest_sha256": "547db0f791454039309f632d0d3947eb27991f7d26ff896a3316b7220a8c5a2f", "page_count_extracted": 16, "characters_reflowed": 85300, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3558066", "title": "Multi-Stage Semantic Communication for Low-Latency Edge Inference", "pdf": "papers/2026_Ding_Multi_Stage_Semantic_Communication_for_Low_Latency_Edge_Inference.pdf", "pdf_exists": true, "pdf_sha256": "6d0b3b0fd406f91a52bc4231f69704f4849a23f7c070a9c8b50f4c75b3048e78", "manifest_sha256": "6d0b3b0fd406f91a52bc4231f69704f4849a23f7c070a9c8b50f4c75b3048e78", "page_count_extracted": 16, "characters_reflowed": 76157, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 12}, "selected_pages": [1, 11], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3573407", "title": "Non-Orthogonal Superimposed Pilot for Goodput Enhancement in Digital Semantic Communication", "pdf": "papers/2026_Zou_Non_Orthogonal_Superimposed_Pilot_for_Goodput_Enhancement_in_Digital_Semantic_Communication.pdf", "pdf_exists": true, "pdf_sha256": "e4478d5de974eb5db8b92172d7a692371721bd4746438c0fc0f81479ecde6b74", "manifest_sha256": "e4478d5de974eb5db8b92172d7a692371721bd4746438c0fc0f81479ecde6b74", "page_count_extracted": 15, "characters_reflowed": 68552, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 2, 5], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3628475", "title": "On the Effectiveness of Task-Oriented Digital Semantic Communication System", "pdf": "papers/2026_Mao_On_the_Effectiveness_of_Task_Oriented_Digital_Semantic_Communication_System.pdf", "pdf_exists": true, "pdf_sha256": "c021ee4d93219c76de7cadf11616ff0a1b6477a105a861c2c3920b98435f5271", "manifest_sha256": "c021ee4d93219c76de7cadf11616ff0a1b6477a105a861c2c3920b98435f5271", "page_count_extracted": 16, "characters_reflowed": 81067, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3569604", "title": "Over-the-Air ODE-Inspired Neural Network for Dual Task-Oriented Semantic Communications", "pdf": "papers/2026_Liu_Over_the_Air_ODE_Inspired_Neural_Network_for_Dual_Task_Oriented_Semantic_Communications.pdf", "pdf_exists": true, "pdf_sha256": "b0562d4816a3d7d7d32005bb3dfccf1f51580f4c5511fcf9c187eb09953d86bb", "manifest_sha256": "b0562d4816a3d7d7d32005bb3dfccf1f51580f4c5511fcf9c187eb09953d86bb", "page_count_extracted": 15, "characters_reflowed": 72004, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3586904", "title": "Personalized Federated Learning for GAI-Assisted Semantic Communications", "pdf": "papers/2026_Peng_Personalized_Federated_Learning_for_GAI_Assisted_Semantic_Communications.pdf", "pdf_exists": true, "pdf_sha256": "7adb7fbd1b21ee1b61c352b24c80b2f5d5d81a2bba71fcce02e8ffc8135ff15e", "manifest_sha256": "7adb7fbd1b21ee1b61c352b24c80b2f5d5d81a2bba71fcce02e8ffc8135ff15e", "page_count_extracted": 13, "characters_reflowed": 59930, "section_pages": {"introduction": 1, "method": 2, "experiment": 2, "conclusion": 12}, "selected_pages": [1, 5], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3718954", "title": "PLM-Based Two-Stage Semantic Encoding for Task-Oriented Semantic Communication on the Fly", "pdf": "papers/2026_Cai_PLM_Based_Two_Stage_Semantic_Encoding_for_Task_Oriented_Semantic_Communication_on_the_Fly.pdf", "pdf_exists": true, "pdf_sha256": "0ff2bec7b42741c07acb12bcc933f3754a132c936e690a8c7fa40d51b42a9a8c", "manifest_sha256": "0ff2bec7b42741c07acb12bcc933f3754a132c936e690a8c7fa40d51b42a9a8c", "page_count_extracted": 18, "characters_reflowed": 92741, "section_pages": {"introduction": 1, "method": 2, "experiment": 11, "conclusion": 17}, "selected_pages": [1, 3, 5, 10], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3720206", "title": "Rate-Adaptive Vector Quantization for Deep Joint Source-Channel Coding", "pdf": "papers/2026_Seo_Rate_Adaptive_Vector_Quantization_for_Deep_Joint_Source_Channel_Coding.pdf", "pdf_exists": true, "pdf_sha256": "1aff360cf6f6334acf3dadd69a3184d1f6232794d307d81c57e6257dc3934ad9", "manifest_sha256": "1aff360cf6f6334acf3dadd69a3184d1f6232794d307d81c57e6257dc3934ad9", "page_count_extracted": 15, "characters_reflowed": 79825, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 7, 13], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3668816", "title": "Region-of-Interest Oriented Image Semantic Communication", "pdf": "papers/2026_Zhu_Region_of_Interest_Oriented_Image_Semantic_Communication.pdf", "pdf_exists": true, "pdf_sha256": "b505af9a7e725457580baa022ef8aa3b3ac9c1ac7c0eb701a28cf88d74157d40", "manifest_sha256": "b505af9a7e725457580baa022ef8aa3b3ac9c1ac7c0eb701a28cf88d74157d40", "page_count_extracted": 15, "characters_reflowed": 61209, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3558006", "title": "Resource Allocation for Semantic Communication in NTN Downlinks", "pdf": "papers/2026_Minani_Resource_Allocation_for_Semantic_Communication_in_NTN_Downlinks.pdf", "pdf_exists": true, "pdf_sha256": "9faf550aa93192f2f9ae9211fabb469a582b42d2b2a7093aab18e8ce2641e566", "manifest_sha256": "9faf550aa93192f2f9ae9211fabb469a582b42d2b2a7093aab18e8ce2641e566", "page_count_extracted": 21, "characters_reflowed": 111765, "section_pages": {"introduction": 1, "method": 2, "experiment": 13, "conclusion": 20}, "selected_pages": [1, 3, 15], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3690646", "title": "SADJSCC: Semantic-Aware DJSCC With Attribute Fidelity Evaluation for Channel-Adaptive Image Transmission", "pdf": "papers/2026_Xu_SADJSCC_Semantic_Aware_DJSCC_With_Attribute_Fidelity_Evaluation_for_Channel_Adaptive_Image_T.pdf", "pdf_exists": true, "pdf_sha256": "68800578da405c0bf3182e73299c782fe8306f9c097ab2860125f7c88f9126f6", "manifest_sha256": "68800578da405c0bf3182e73299c782fe8306f9c097ab2860125f7c88f9126f6", "page_count_extracted": 17, "characters_reflowed": 82176, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 16}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3556777", "title": "Secure and Robust Joint Source-Channel Coding With Semantic Clustering and Adversarial Purification", "pdf": "papers/2026_Huang_Secure_and_Robust_Joint_Source_Channel_Coding_With_Semantic_Clustering_and_Adversarial_Purif.pdf", "pdf_exists": true, "pdf_sha256": "02f821af7b49623ff11868e89c9cb5c9596b7f91c53c8e5709541852b75418ee", "manifest_sha256": "02f821af7b49623ff11868e89c9cb5c9596b7f91c53c8e5709541852b75418ee", "page_count_extracted": 13, "characters_reflowed": 53630, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 12}, "selected_pages": [1, 2], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3692413", "title": "Secure Intellicise Wireless Network: Agentic AI for Coverless Semantic Steganography Communication", "pdf": "papers/2026_Meng_Secure_Intellicise_Wireless_Network_Agentic_AI_for_Coverless_Semantic_Steganography_Communic.pdf", "pdf_exists": true, "pdf_sha256": "fb87deca86315e419dc5325465fa8ec24af710f054498a708da37d7e30c870a6", "manifest_sha256": "fb87deca86315e419dc5325465fa8ec24af710f054498a708da37d7e30c870a6", "page_count_extracted": 17, "characters_reflowed": 86086, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 13}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3579540", "title": "Semantic Communication for Cooperative Perception Using HARQ", "pdf": "papers/2026_Sheng_Semantic_Communication_for_Cooperative_Perception_Using_HARQ.pdf", "pdf_exists": true, "pdf_sha256": "f261e2c4004c32281cc1ee111340e7a353e79f6f20654c7bc2014a862ba9919b", "manifest_sha256": "f261e2c4004c32281cc1ee111340e7a353e79f6f20654c7bc2014a862ba9919b", "page_count_extracted": 16, "characters_reflowed": 74927, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 8, 11], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3683217", "title": "Semantic Communication for Machines: A Joint Transmission and Understanding Design", "pdf": "papers/2026_He_Semantic_Communication_for_Machines_A_Joint_Transmission_and_Understanding_Design.pdf", "pdf_exists": true, "pdf_sha256": "428a2945d2ec43f986636188b0fe5bc2c306655af6048f0c9d5c772569cbbb30", "manifest_sha256": "428a2945d2ec43f986636188b0fe5bc2c306655af6048f0c9d5c772569cbbb30", "page_count_extracted": 17, "characters_reflowed": 81514, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 16}, "selected_pages": [1, 2, 8], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3558018", "title": "Semantic Feature Division Multiple Access for Digital Semantic Multiple Access Channels", "pdf": "papers/2026_Shen_Semantic_Feature_Division_Multiple_Access_for_Digital_Semantic_Multiple_Access_Channels.pdf", "pdf_exists": true, "pdf_sha256": "1a3d69d7240d589ff30e5a30a50fa8e18d110ebe9ef5dbb53974edb5743f43e1", "manifest_sha256": "1a3d69d7240d589ff30e5a30a50fa8e18d110ebe9ef5dbb53974edb5743f43e1", "page_count_extracted": 15, "characters_reflowed": 64482, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 12}, "selected_pages": [1, 3], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3683191", "title": "Semantic Radio Access Networks: Architecture, State-of-the-Art, and Future Directions", "pdf": "papers/2026_Meng_Semantic_Radio_Access_Networks_Architecture_State_of_the_Art_and_Future_Directions.pdf", "pdf_exists": true, "pdf_sha256": "37c491cd7b109bf06f4d0f2f75fbc311bb19bae0a4c29afd181868d3b33a68a9", "manifest_sha256": "37c491cd7b109bf06f4d0f2f75fbc311bb19bae0a4c29afd181868d3b33a68a9", "page_count_extracted": 22, "characters_reflowed": 112209, "section_pages": {"introduction": 1, "method": 2, "experiment": 13, "conclusion": 21}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3710538", "title": "SemDiffShield: Agentic AI-Empowered Secure Image Semantic Communication via Cryptographic Diffusion", "pdf": "papers/2026_Zhu_SemDiffShield_Agentic_AI_Empowered_Secure_Image_Semantic_Communication_via_Cryptographic_Dif.pdf", "pdf_exists": true, "pdf_sha256": "84bb9177e6bc5606912074821f52ef8845c51ed755a1ab86f810340c151f334c", "manifest_sha256": "84bb9177e6bc5606912074821f52ef8845c51ed755a1ab86f810340c151f334c", "page_count_extracted": 15, "characters_reflowed": 70560, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 4], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3641521", "title": "ST-VJSCC: Spatio-Temporal Video DeepJSCC Scheme for Adaptive Wireless Transmission", "pdf": "papers/2026_Zhou_ST_VJSCC_Spatio_Temporal_Video_DeepJSCC_Scheme_for_Adaptive_Wireless_Transmission.pdf", "pdf_exists": true, "pdf_sha256": "c08f7aed6f83a944b6d0371f1ed6a6adff1211bdac4ef10a0576208f7bdc83b8", "manifest_sha256": "c08f7aed6f83a944b6d0371f1ed6a6adff1211bdac4ef10a0576208f7bdc83b8", "page_count_extracted": 16, "characters_reflowed": 72782, "section_pages": {"introduction": 1, "method": 2, "experiment": 10, "conclusion": 15}, "selected_pages": [1, 2, 11, 15], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3682513", "title": "Task-Adaptive Semantic Communication With Feedback: A Conditional Rate-Distortion Approach", "pdf": "papers/2026_He_Task_Adaptive_Semantic_Communication_With_Feedback_A_Conditional_Rate_Distortion_Approach.pdf", "pdf_exists": true, "pdf_sha256": "de1b5756e5fc76554669ba30b96b7235eb473ffc26823c9ad84c16e9eb34b780", "manifest_sha256": "de1b5756e5fc76554669ba30b96b7235eb473ffc26823c9ad84c16e9eb34b780", "page_count_extracted": 15, "characters_reflowed": 77241, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3691535", "title": "Task-Generalizable Deep Joint Source-Channel Coding via Hierarchical Masked Autoencoders", "pdf": "papers/2026_Dai_Task_Generalizable_Deep_Joint_Source_Channel_Coding_via_Hierarchical_Masked_Autoencoders.pdf", "pdf_exists": true, "pdf_sha256": "e96805ab750aa251c5ec239e9e069fecc664ccd9d9da3bc89df4c947f8b3a2a9", "manifest_sha256": "e96805ab750aa251c5ec239e9e069fecc664ccd9d9da3bc89df4c947f8b3a2a9", "page_count_extracted": 14, "characters_reflowed": 66920, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 13}, "selected_pages": [1, 3, 9, 13], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2025.3579558", "title": "Topic Enhanced Semantic Communication System for Reliable Semantic Recovery", "pdf": "papers/2026_Zhang_Topic_Enhanced_Semantic_Communication_System_for_Reliable_Semantic_Recovery.pdf", "pdf_exists": true, "pdf_sha256": "213818c297f906850c1a0b577fe0e57a72b9cb6261bdac33dcf4ab43cb9d46e3", "manifest_sha256": "213818c297f906850c1a0b577fe0e57a72b9cb6261bdac33dcf4ab43cb9d46e3", "page_count_extracted": 15, "characters_reflowed": 69341, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3677174", "title": "Toward Intelligent IoT Services: A Generative AI-Assisted Semantic-Aware Framework", "pdf": "papers/2026_Niu_Toward_Intelligent_IoT_Services_A_Generative_AI_Assisted_Semantic_Aware_Framework.pdf", "pdf_exists": true, "pdf_sha256": "eeab906f4c085eedbf4468fa723417e9509df5b608fedd0f2dfda0c2561f6784", "manifest_sha256": "eeab906f4c085eedbf4468fa723417e9509df5b608fedd0f2dfda0c2561f6784", "page_count_extracted": 13, "characters_reflowed": 62314, "section_pages": {"introduction": 1, "method": 2, "experiment": 8, "conclusion": 11}, "selected_pages": [1, 3], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3676414", "title": "Uplink-Assisted Joint Channel Estimation and CSI Feedback: An Approach Based on Deep Joint Source-Channel Coding", "pdf": "papers/2026_Guo_Uplink_Assisted_Joint_Channel_Estimation_and_CSI_Feedback_An_Approach_Based_on_Deep_Joint_So.pdf", "pdf_exists": true, "pdf_sha256": "fa92e5dcf72ec51c721bb0981b406463b9a628c01ad20c8c26943bb8a3eec437", "manifest_sha256": "fa92e5dcf72ec51c721bb0981b406463b9a628c01ad20c8c26943bb8a3eec437", "page_count_extracted": 15, "characters_reflowed": 76325, "section_pages": {"introduction": 1, "method": 2, "experiment": 9, "conclusion": 14}, "selected_pages": [1, 14], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}
{"doi": "10.1109/tccn.2026.3712380", "title": "VQ-DSC-R: Robust Vector Quantized-Enabled Digital Semantic Communication With OFDM Transmission", "pdf": "papers/2026_Chen_VQ_DSC_R_Robust_Vector_Quantized_Enabled_Digital_Semantic_Communication_With_OFDM_Transmissi.pdf", "pdf_exists": true, "pdf_sha256": "564ae752309e1f1603fd247652f37fcaa4cc72d37d140fdf632a9ca45805a7d8", "manifest_sha256": "564ae752309e1f1603fd247652f37fcaa4cc72d37d140fdf632a9ca45805a7d8", "page_count_extracted": 18, "characters_reflowed": 87881, "section_pages": {"introduction": 1, "method": 2, "experiment": 11, "conclusion": 17}, "selected_pages": [1, 13], "column_order": "pdftotext default reading order (not -layout)", "analysis_version": "journal_fulltext_reread_v4_2026-08-28"}