论文发表
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发布日期:   2026-07-02

专著

  1. 黄永峰，《IP网络多媒体通信技术》，人民邮电出版社，2003.1
  2. 黄永峰，《因特网语音通信技术》，人民邮电出版社，2001,12（863高技术丛书）
  3. 黄永峰，厥勇等,《 Windows/Linux/UNIX综合组网技术》，清华大学出版社，2002.9
  4. 李星，黄永峰，《高速计算机互联网络》，人民邮电出版社，2005.6（”十五”国家重点图书出版规划项目）
  5. 王欣靖，李星，黄永峰，《网络新技术点评》，人民邮电出版社, 2003,12
  6. 黄永峰，李星，《计算机网络教程》，清华大学出版社，2006.2(清华大学信息技术学院系列教材）
  7. 黄永峰，邓泽，《Data & Voice Network》,人民邮电出版社, 2002.10
  8. 黄永峰，周可，《Route and switch》,人民邮电出版社, 2004.3
  9. 黄永峰、赵建庆编著，《SIP协议及其应用》，人民邮电出版社，2009.1

论文

2026

  1. Yang, P., Yin, J., Zheng, H., Bai, X., Wang, H., Sun, Y., Huang, Y., & Qi, T. (2026, March). MRM: Black-box membership inference attacks against multimodal RAG systems. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 40, pp. 34295–34303).
  2. Yang, P., Li, Y., Wang, S., Liu, X., Gan, H., Li, X., Gao, Q., & Huang, Y. (2026, March). OncoCoT: A temporal-causal chain-of-thought dataset for oncologic decision-making. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 40, pp. 34277–34285).
  3. Yang, P., Zheng, H., Luo, Y., Liu, X., Wang, J., Wang, H., Huang, Y., & Qi, T. (2026, March). ShieldRAG: Safeguarding retrieval-augmented generation from untrusted knowledge bases. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 40, pp. 34286–34294).
  4. Yin, J., Li, D., Wang, W., Yang, P., Wang, H., Ma, Y., Huang, Y., & Qi, T. (2026, May). DHEval: A dynamic hallucination evaluation protocol robust to data contamination. In ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 3336–3340). IEEE.
  5. Qi, T., Yin, J., Cai, D., Xie, Y., Wang, H., Hu, Z., Huang, Y., & Lane, N. D. (2026). Auditing unauthorized training data from AI generated content using information isotopes. Nature Communications.
  6. Zou, J., Qi, Z., Yang, J., Ma, G., Tao, D., Zheng, W., & Huang, Y. (2026). Context-fused emotional flow modeling for dynamic affective recognition in dialogue interactions. Expert Systems with Applications, Article 132855.
  7. Liao, R., Gan, G., Huang, Y., & Huang, Z. (2026). From symmetry toward weak asymmetry: Secure steganography under the receiver’s partial channel knowledge. In Proceedings of the 35th USENIX Security Symposium (USENIX Security 26).

2025

  1. Long, Y., Yang, Z., Wang, Z., Zhou, Z., Huang, Y., & Zhou, L. (2025, April). SCF-stega: Controllable linguistic steganography based on semantic communications framework. In ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 1–5). IEEE.
  2. Liu, R., Huang, F., Liu, G., Tao, D., Wang, B., & Huang, Y. (2025, December). CG-UIE: A category-guided universal information extraction framework for event extraction. In Proceedings of the 2025 6th International Conference on Computers and Artificial Intelligence Technology (pp. 131–137). IEEE.
  3. Bai, M., Pang, K., Liao, G., Yang, J., & Huang, Y. (2025). Shimmer: A provably secure steganography based on entropy collecting mechanism. In Proceedings of the 34th USENIX Security Symposium (USENIX Security 25) (pp. 5949–5965).
  4. Liao, G., Yang, J., Shao, W., & Huang, Y. (2025). A framework for designing provably secure steganography. In Proceedings of the 34th USENIX Security Symposium (USENIX Security 25) (pp. 6837–6856).
  5. Yin, J., Yang, P., Yang, C., Wang, H., Hu, Z., Wang, S., Huang, Y., & Qi, T. (2025). Black-box membership inference attack for LVLMs via prior knowledge-calibrated memory probing. In Advances in Neural Information Processing Systems (Vol. 38, pp. 99554–99578).
  6. Pang, K., Qi, T., Wu, C., Bai, M., Jiang, M., & Huang, Y. (2025). ModelShield: Adaptive and robust watermark against model extraction attack. IEEE Transactions on Information Forensics and Security, 20, 1767–1782.
  7. Guo, S., Pang, K., Yang, Z., Li, Y., Qing, Y., & Huang, Y. (2025, June). Reinforcement learning-based copyright protection watermarking for large language model. In Proceedings of the 2025 ACM Workshop on Information Hiding and Multimedia Security (pp. 114–120).
  8. Wang, H., Wu, C., Huang, Y., & Qi, T. (2025). Learning human feedback from large language models for content quality-aware recommendation. ACM Transactions on Information Systems, 43(4), 1–28.
  9. Yu, Y., Huang, Y., Qi, Z., & Zhou, Z. (2025). Training with “paraphrasing the original text” teaches LLM to better retrieve in long-context tasks. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 39, pp. 25751–25759).
  10. Zou, J., Qi, Z., Yang, J., Wei, Z., Wang, C., Yang, S., Jiang, M., & Huang, Y. (2025, April). Integrating textual and emotional dynamics for accurate detection of mental health disorders in social media. In Proceedings of the 47th Annual Meeting of the Cognitive Science Society (CogSci 2025).
  11. Bai, M., Yang, J., Pang, K., Xu, X., Yang, Z., & Huang, Y. (2025, May). Provably robust and secure steganography in asymmetric resource scenario. In Proceedings of the 2025 IEEE Symposium on Security and Privacy (IEEE S&P 2025).
  12. Pang, K., Bai, M., Yang, J., Gao, Y., Jiang, M., & Huang, Y. (2025). A plug-and-play method for linguistic alignment in language models. Knowledge-Based Systems.
  13. Tao, D., Wang, C., Huang, F., Chen, J., Huang, Y., & Jiang, M. (2025). Fine-grained stateful knowledge exploration: Effective and efficient graph retrieval with large language models. Knowledge-Based Systems.
  14. Yang, J., Bai, M., Pang, K., Gao, Y., Zou, J., & Huang, Y. (2025). A novel framework of semantic-based text steganography. IEEE Transactions on Dependable and Secure Computing.
  15. Wang, Y., Wang, H., Pang, K., Li, Y., & Huang, Y. (2025). LLM-based tuning-free linguistic steganalysis. In Proceedings of the International Conference on Electronic Information Engineering and Computer Technology (EIEECT 2025).

2024

  1. Qi, T., Wang, H., & Huang, Y. (2024, March). Towards the robustness of differentially private federated learning. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, pp. 19911–19919).
  2. Huang, Q., Huang, F., Tao, D., Zhao, Y., Wang, B., & Huang, Y. (2024, April). Coq: An empirical framework for multi-hop question answering empowered by large language models. In ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 11566–11570). IEEE.
  3. Liao, G., Yang, J., Pang, K., et al. (2024). Co-Stega: Collaborative linguistic steganography for the low capacity challenge in social media. In Proceedings of the 2024 ACM Workshop on Information Hiding and Multimedia Security (pp. 7–12).
  4. Gao, Y., Yang, J., Chen, C., Pang, K., & Huang, Y. (2024, April). Enhancing steganography of generative image based on image retouching. In ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 4945–4949). IEEE.
  5. Liang, Y., Zhang, Z., Xu, X., & Huang, Y. (2024, August). Layered system architecture for covert communication based on social networks. In Proceedings of the International Conference on Computational & Experimental Engineering and Sciences (pp. 243–250). Springer.
  6. Huang, Q., Huang, F., Tao, D., Wang, B., & Huang, Y. (2024, April). UNIFIT: A unified framework for instruction tuning to improve instruction following ability for large language models. In Proceedings of the 46th Annual Meeting of the Cognitive Science Society (CogSci 2024) (pp. 2121–2126).
  7. Ahmad, B., Wu, Z., Huang, Y., & Rehman, S. U. (2024). Enhancing the security in IoT and IIoT networks: An intrusion detection scheme leveraging deep transfer learning. Knowledge-Based Systems, 305, Article 112614.
  8. Zou, J., Zhang, Y., Wu, S., Yang, J., Qin, X., Ying, L., Jiang, M., & Huang, Y. (2024). A machine reading comprehension framework for recognizing emotion cause in conversations. Knowledge-Based Systems, 289, Article 111532.
  9. Zou, J., Wu, S., Yang, J., Jiang, M., & Huang, Y. (2024, September). RedditEM: Unveiling diachronic semantic shifts in social network discourse. In Proceedings of the 16th Asian Conference on Machine Learning (ACML 2024) (pp. 968–983).
  10. Li, L., Zhang, Y., Zou, J., & Huang, Y. (2024, August). HieRelBERT: Enhanced lexical relation embedding based-on hierarchical contrast learning. In Proceedings of the International Conference on Computational & Experimental Engineering and Sciences.
  11. Xu, X., Yang, Z., & Huang, Y. (2024, August). Smart contract aided attribute-based signature algorithm with non-monotonic access structures. In Proceedings of the International Conference on Computational & Experimental Engineering and Sciences.

2023

  1. Yang, J., Yang, Z., Ge, X., Zou, J., Gao, Y., & Huang, Y. (2023, June). LINK: Linguistic steganalysis framework with external knowledge. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 1–5). IEEE.
  2. Qi, T., Wu, F., Lyu, L., Huang, Y., & Xie, X. (2023, August). FedSampling: A better sampling strategy for federated learning. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023) (pp. 4154–4162).
  3. Qi, T., Wu, F., Wu, C., He, L., Huang, Y., & Xie, X. (2023). Differentially private knowledge transfer for federated learning. Nature Communications, 14(1), Article 3785.
  4. Wang, H., Yang, Z., Yang, J., Chen, C., & Huang, Y. (2023). Linguistic steganalysis in few-shot scenario. IEEE Transactions on Information Forensics and Security, 18, 4870–4882.
  5. Tu, H., Yang, Z., Yang, J., Zhou, L., & Huang, Y. (2023). FET-LM: Flow-enhanced variational autoencoder for topic-guided language modeling. IEEE Transactions on Neural Networks and Learning Systems.
  6. Wu, C., Wu, F., Huang, Y., & Xie, X. (2023). Personalized news recommendation: Methods and challenges. ACM Transactions on Information Systems, 41(1), 1–50.
  7. Bai, M., Huang, Y., Yang, J., Pang, K., & Li, S. (2023, October). Exploration of the effectiveness and characteristics of ChatGPT in steganalysis tasks. In Proceedings of AIBC 2023.
  8. Zou, J., Zhang, Y., Yang, J., Wu, S., Jiang, M., & Huang, Y. (2023, September). Emotion recognition in social network texts based on a multilingual architecture. In Proceedings of the 2023 IEEE International Conference on Data Mining (ICDM 2023).
  9. Yang, P., Wang, H., Huang, Y., Yang, S., Zhang, Y., Huang, L., Zhang, Y., Wang, G., Yang, S., He, L., & Huang, Y. (2023). LMKG: A large-scale and multi-source medical knowledge graph for intelligent medicine applications. Knowledge-Based Systems, Article 111323.
  10. Ding, C., Fu, Z., Yang, Z., Yu, Q., Li, D., & Huang, Y. (2023). Context-aware linguistic steganography model based on neural machine translation. IEEE/ACM Transactions on Audio, Speech, and Language Processing.
  11. Pang, K., Bai, M., Yang, J., Wang, H., Jiang, M., & Huang, Y. (2023, December). FreMAX: A simple method towards truly secure generative linguistic steganography. In ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing.
  12. Wang, H., Yang, Z., Yang, J., Gao, Y., & Huang, Y. (2023, November). Hi-Stega: A hierarchical linguistic steganography framework combining retrieval and generation. In Proceedings of ICONIP 2023 (pp. 41–54).
  13. Pang, K., Yang, J., Gao, Y., Bai, M., Yang, Z., Zhang, M., & Huang, Y. (2023, November). CATS: Connection-aware and interaction-based text steganalysis in social networks. In Proceedings of ICONIP 2023 (pp. 109–121).
  14. Chen, C., Yang, J., Gao, Y., Wang, H., & Huang, Y. (2023, November). Minimizing distortion in steganography via adaptive language model tuning. In Proceedings of ICONIP 2023 (pp. 571–584).
  15. Huang, F., Huang, Q., Zhao, Y., Qi, Z., Wang, B., Huang, Y., & Li, S. (2023, November). A three-stage framework for event-event relation extraction with large language model. In Proceedings of ICONIP 2023 (pp. 434–446).
  16. Qi, Z., Huang, Y., Wu, J., & Li, S. (2023, October). FoodS and FoodIM: Food-testing item recommendation models for two different users with different usage abilities. In Proceedings of AIBC 2023.
  17. Li, L., Zhang, Y., Zou, J., & Huang, Y. (2023, August). PNPT: Prototypical network with prompt template for few-shot relation extraction. In Proceedings of SMP 2023 (CCIS, Vol. 1945).

2022

  1. Chen, Y., Zhang, Y., & Huang, Y. (2022). Learning reasoning patterns for relational triple extraction with mutual generation of text and graph. In Findings of the Association for Computational Linguistics: ACL 2022 (pp. 1638–1647). Association for Computational Linguistics.
  2. Qi, T., Wu, F., Wu, C., Sun, P., Wu, L., Wang, X., Huang, Y., & Xie, X. (2022). ProFairRec: Provider fairness-aware news recommendation. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘22).
  3. Qi, T., Wu, F., Wu, C., & Huang, Y. (2022). News recommendation with candidate-aware user modeling. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘22).
  4. Qi, T., Wu, F., Wu, C., & Huang, Y. (2022). FUM: Fine-grained and fast user modeling for news recommendation. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘22).
  5. Wu, C., Wu, F., Qi, T., & Huang, Y. (2022). NoisyTune: A little noise can help you finetune pretrained language models better. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (pp. 680–685).
  6. Wu, C., Wu, F., & Huang, Y. (2022). Rethinking InfoNCE: How many negative samples do you need? In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI 2022) (pp. 2509–2515).
  7. Wu, C., Wu, F., Qi, T., & Huang, Y. (2022). UserBERT: Pre-training user model with contrastive self-supervision. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘22) (pp. 2087–2092).
  8. Wu, C., Wu, F., Qi, T., Li, C., & Huang, Y. (2022). Is news recommendation a sequential recommendation task? In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘22) (pp. 2382–2386).
  9. Wu, C., Wu, F., Qi, T., Zhang, C., Huang, Y., & Xu, T. (2022). MM-Rec: Visiolinguistic model empowered multimodal news recommendation. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘22) (pp. 2560–2564).
  10. Wu, C., Wu, F., Qi, T., Liu, Q., Tian, X., Li, J., He, W., Huang, Y., & Xie, X. (2022). FeedRec: News feed recommendation with various user feedbacks. In Proceedings of the ACM Web Conference 2022 (WWW ‘22) (pp. 2088–2097).
  11. Wu, C., Wu, F., Qi, T., Huang, Y., & Xie, X. (2022). FedAttack: Effective and covert poisoning attack on federated recommendation via hard sampling. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ‘22).
  12. Wu, C., Wu, F., Qi, T., & Huang, Y. (2022). Two birds with one stone: Unified model learning for both recall and ranking in news recommendation. In Findings of the Association for Computational Linguistics: ACL 2022 (pp. 3474–3480).
  13. Li, Q., Yang, Z., Qin, X., Tao, D., Pan, H., & Huang, Y. (2022). CBFF: A cloud–blockchain fusion framework ensuring data accountability for multi-cloud environments. Journal of Systems Architecture, 124, Article 102405.
  14. Yang, J., Yang, Z., Zou, J., Tu, H., & Huang, Y. (2022). Linguistic steganalysis towards social network. IEEE Transactions on Information Forensics and Security.
  15. Wu, C., Wu, F., Lyu, L., Huang, Y., & Xie, X. (2022). Communication-efficient federated learning via knowledge distillation. Nature Communications, 13(1).
  16. Wu, C., Wu, F., Lyu, L., Qi, T., Huang, Y., & Xie, X. (2022). A federated graph neural network framework for privacy-preserving personalization. Nature Communications, 13(1).
  17. Wu, C., Wu, F., Qi, T., Zhang, W.-Q., Xie, X., & Huang, Y. (2022). Removing AI’s sentiment manipulation of personalized news delivery. Humanities and Social Sciences Communications.
  18. Chen, Y., Wu, C., Qi, T., Yuan, Z., Zhang, Y., Yang, S., Guan, J., Sun, D., & Huang, Y. (2022). Semi-supervised named entity recognition in multi-level contexts. Neurocomputing, 520, 194–204.
  19. Qi, Y., Yang, Z., Huang, Y., & Li, X. (2022). Blockchain-based light-weighted provable data possession for low performance devices. Computers, Materials & Continua, 73(2), 2205–2221.
  20. Qi, Y., Huang, Y., & Li, X. (2022). Blockchain-based privacy-preserving public auditing for group shared data. Intelligent Automation & Soft Computing, 35(3), 2603–2618.
  21. Qi, Y., Huang, Y., & Li, X. (2022). Blockchain-based privacy-preserving group data auditing with secure user revocation. Computer Systems Science and Engineering, 45(1), 183–199.
  22. 齐伊宁，秦宣梅，孙东红，潘鸿运，李琪，黄永峰，王丹丹 (2022). 面向领域数据安全可信共享的云链融合系统. 中国传媒大学学报(自然科学版), 29(2).
  23. Chen, F., Yang, Z., & Huang, Y. (2022). A multi-task learning framework for end-to-end aspect sentiment triplet extraction. Neurocomputing, 479.
  24. Wu, C., Wu, F., He, X., & Huang, Y. (2022). DebiasGAN: Eliminating position bias in news recommendation with adversarial learning. In Findings of the Association for Computational Linguistics: EMNLP 2022.
  25. Qi, T., Wu, F., Wu, C., Lyu, L., Xu, T., Liao, H., Yang, Z., Huang, Y., & Xie, X. (2022). FairVFL: A fair vertical federated learning framework with contrastive adversarial learning. In Advances in Neural Information Processing Systems (NeurIPS 2022).
  26. Qin, X., Yang, Z., Li, Q., Pan, H., Yang, Z., & Huang, Y. (2022). Attribute-based encryption with outsourced computation for access control in IoTs. In Proceedings of the 3rd Asia Service Sciences and Software Engineering Conference (ASSE 2022).
  27. Zou, J., Wu, S., Yang, Z., et al. (2022). Association extraction and recognition of multiple emotion expressed in social texts. In Proceedings of the International Conference on Artificial Intelligence and Security (ICAIS 2022).
  28. Zou, J., Wu, S., Yang, Z., et al. (2022). Aspect-level sentiment classification based on graph attention network with BERT. In Proceedings of the International Conference on Artificial Intelligence and Security (ICAIS 2022).
  29. Zhang, Y., Chen, Y., & Huang, Y. (2022). RelU-Net: Syntax-aware graph U-Net for relational triple extraction. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022).

2021

  1. Qin, X., Huang, Y., Yang, Z., & Li, X. (2021). A blockchain-based access control scheme with multiple attribute authorities for secure cloud data sharing. Journal of Systems Architecture, 112, Article 101854.
  2. Qin, X., Huang, Y., Yang, Z., & Li, X. (2021). LBAC: A lightweight blockchain-based access control scheme for the internet of things. Information Sciences, 554, 222–235.
  3. Yang, Z., Yang, H., Chang, C.-C., Huang, Y., & Chang, C.-C. (2022). Real-time steganalysis for streaming media based on multi-channel convolutional sliding windows. Knowledge-Based Systems, 237, Article 107561.
  4. Yang, Z., Xiang, L., Zhang, S., Sun, X., & Huang, Y. (2021). Linguistic generative steganography with enhanced cognitive-imperceptibility. IEEE Signal Processing Letters, 28, 409–413.
  5. Yang, J., Yang, Z., Zhang, S., Tu, H., & Huang, Y. (2022). SeSy: Linguistic steganalysis framework integrating semantic and syntactic features. IEEE Signal Processing Letters, 29, 31–35.
  6. Chen, Y., Wu, C., & Huang, Y. (2022). Enhancing structure modeling for relation extraction with fine-grained gating and co-attention. Neurocomputing, 467, 282–291.
  7. Qi, T., Qiu, S., Shen, X., Chen, H., Yang, S., Wen, H., Zhang, Y., Wu, Y., & Huang, Y. (2021). KeMRE: Knowledge-enhanced medical relation extraction for Chinese medicine instructions. Journal of Biomedical Informatics, 120, Article 103834.
  8. Chen, F., Shi, Z., Yang, Z., & Huang, Y. (2022). Recurrent synchronization network for emotion-cause pair extraction. Knowledge-Based Systems, 238, Article 107965.
  9. Yang, Z., He, J., Zhang, S., Yang, J., & Huang, Y. (2021). TStego-THU: Large-scale text steganalysis dataset. In Proceedings of the International Conference on Artificial Intelligence and Security (ICAIS 2021).
  10. Zhang, S., Yang, Z., Yang, J., & Huang, Y. (2021). Provably secure generative linguistic steganography. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 3046–3055).
  11. Wang, H., Yang, Z., Hu, Y., Yang, Z., & Huang, Y. (2021). Fast detection of heterogeneous parallel steganography for streaming voice. In Proceedings of the 2021 ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec ‘21) (pp. 137–142).
  12. Chen, Y., Zhang, Y., Hu, C., & Huang, Y. (2021). Jointly extracting explicit and implicit relational triples with reasoning pattern enhanced binary pointer network. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2021) (pp. 5694–5703).
  13. Qi, T., Wu, F., Wu, C., & Huang, Y. (2021). Personalized news recommendation with knowledge-aware interactive matching. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘21).
  14. Qi, T., Wu, F., Wu, C., & Huang, Y. (2021). PP-Rec: News recommendation with personalized user interest and time-aware news popularity. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) (pp. 5457–5467).
  15. Qi, T., Wu, F., Wu, C., Yang, P., Yu, Y., Xie, X., & Huang, Y. (2021). HieRec: Hierarchical user interest modeling for personalized news recommendation. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) (pp. 5446–5456).
  16. Qi, T., Wu, F., Wu, C., Huang, Y., & Xie, X. (2021). Uni-FedRec: A unified privacy-preserving news recommendation framework for model training and online serving. In Findings of the Association for Computational Linguistics: EMNLP 2021 (pp. 1438–1448).
  17. Wu, C., Wu, F., Qi, T., & Huang, Y. (2021). Hi-Transformer: Hierarchical interactive transformer for efficient and effective long document modeling. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021) (pp. 848–853).
  18. Wu, C., Wu, F., & Huang, Y. (2021). One teacher is enough? Language model distillation from multiple teachers. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 4408–4413).
  19. Wu, C., Wu, F., Huang, Y., & Xie, X. (2021). User-as-graph: User modeling with heterogeneous graph pooling for news recommendation. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021) (pp. 1624–1630).
  20. Wu, C., Wu, F., Qi, T., & Huang, Y. (2021). Empowering news recommendation with pre-trained language models. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR ‘21) (pp. 1652–1656).
  21. Wu, C., Wu, F., & Huang, Y. (2021). DA-Transformer: Distance-aware transformer. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 2021) (pp. 2059–2068).
  22. Wu, C., Wu, F., Wang, X., Huang, Y., & Xie, X. (2021). Fairness-aware news recommendation with decomposed adversarial learning. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021).
  23. Wu, C., Wu, F., Yu, Y., Qi, T., Huang, Y., & Liu, Q. (2021). NewsBERT: Distilling pre-trained language model for intelligent news application. In Findings of the Association for Computational Linguistics: EMNLP 2021 (pp. 3285–3295).

发明专利

2025

  1. 黄永峰、高悦、庞凯怡、陈程、余辉，《基于语义编码的鲁棒图像合成隐写方法》，申请号：202511099038.3
  2. 黄永峰、管磊、余辉，《一种跨网络平台的虚拟身份对齐方法和系统》，申请号：202511099038.3

2024

  1. 黄永峰、张蕴琪、陶丹丹、余辉，《知识三元组抽取方法、装置、电子设备及可读存储介质》，申请号：202411706393.8
  2. 陶丹丹，黄永峰，余辉，邹佳君，齐致潇，俞一炅，《一种食品安全检测预警处理方法及装置》，申请号：202411675378.1
  3. 黄永峰、魏喆琛、余辉，《一种基于大语言模型的智慧农业图谱交互方法》
  4. 黄永峰、王琮淇、余辉，《基于大语言模型的输出一致性评测方法》
  5. 黄永峰，张子毅，杨金帅，高悦，王慧丽，陈程，《面向公共社交网络平台的背对背隐蔽通信架构》，申请号：202410011249.6

2023

  1. 黄永峰，黄颖卓，陈泽平，何亮，《基于跨模态互注意力机制的多模态文档检索方法及装置》，申请号：202310337398.7
  2. 黄永峰，汪洪钧，杨珮茹，何亮，《融合拓扑和语义信息的知识图谱表征方法及装置》，申请号：2023104501126
  3. 黄永峰，张子毅，杨金帅，高悦，王慧丽，陈程，《一套面向公共社交网络平台的无连接隐私通信协议与软件》，申请号：2023120060
  4. 黄永峰，杨金帅，张子毅，《基于动态自适应分组的文本生成式隐写方法及装置》，申请号：202311774626.3

2022

  1. 黄永峰，潘鸿运，秦宣梅，李琪，陈程，王慧丽，白旻浩，《云链融合机制下的食品安全大数据共享管理方法及系统》，申请号：2022105175774
  2. 黄永峰，黄颖卓，齐涛，何亮，《网络文本中药物名称及药物不良反应的联合检测方法》，申请号：2022101119718
  3. 黄永峰，黄颖卓，陈泽平，何亮，《基于历史病历关联挖掘的病历智能检索方法及装置》，申请号：2022113178435
  4. 黄永峰，汪洪钧，齐涛，何亮，《利用字典知识的命名体识别方法、装置、电子设备及介质》，申请号：2022100165371

软件著作权

2025

  1. 陶德昊，郑尧昊，《智慧农业知识抽取软件 V1.0》，登记号：2025SR2146194，2025.11.04，已授权

2024

  1. 陶丹丹，余辉，《食品安全抽检可视化平台 V1.0》，登记号：2024R11S2516652，已受理

2023

  1. 黄永峰，陈泽平，齐涛，何亮，《面向乙肝相关疾病的辅助诊疗系统》，登记号：2023SR0580944，2023.04.01，已授权
  2. 黄永峰，黄颖卓，邹佳君，张业玄，《面向电商评论的民意感知系统》，登记号：2023R11S2254966，2023.12.05，已受理
 本篇
论文发表 论文发表
专著 黄永峰，《IP网络多媒体通信技术》，人民邮电出版社，2003.1 黄永峰，《因特网语音通信技术》，人民邮电出版社，2001,12（863高技术丛书） 黄永峰，厥勇等,《 Windows/Linux/UNIX综合组网技术》，清华大学出版
2026-07-02 NGNLab
本篇 
论文发表 论文发表
专著 黄永峰，《IP网络多媒体通信技术》，人民邮电出版社，2003.1 黄永峰，《因特网语音通信技术》，人民邮电出版社，2001,12（863高技术丛书） 黄永峰，厥勇等,《 Windows/Linux/UNIX综合组网技术》，清华大学出版
2026-07-02 NGNLab
  目录