发表TPAMI、ICML等国际顶级期刊和会议论文70余篇,专著2本,申请专利20余项,参与制定国内外标准6项,相关论文获ACM MM2025 RichMediaGAI最佳论文奖、ICML2025 MAS杰出论文奖、ESI高被引与热点论文。获WAIC云帆明日之星全球最终榜单(全球10人)、华为卓越青年学者、德国DAAD AInet Fellowship(全球19人)。带领学生获IEEE国际低功耗计算机视觉竞赛LPCV全球冠军、无人机追逐竞赛全球冠军等奖项。研究成果被百度、英特尔等作为领域代表性技术和关键特性集成至PaddleSlim、OpenVINO等国际主流压缩工具和推理库。相关技术应用至商汤、百度等互联网领军企业。个人主页:https://jinyangguo.github.io/
获奖情况
WAIC云帆明日之星全球最终榜单
华为卓越青年学者
ACM MM2025 RichMediaGAI最佳论文奖
IEEE国际低功耗计算机视觉竞赛LPCV全球冠军
无人机追逐竞赛全球冠军
发明专利
[1] 一种基于自适应对比知识蒸馏的网络压缩方法和装置。专利号:ZL202310758129.8
[2] 一种训练后稀疏基准评测方法及装置。专利号:ZL202411577605.7
[3] 一种训练后稀疏模型的优化方法及系统。专利号:ZL202411577615.0
代表性论文
[1] Compressing large language models by joint sparsification and quantization,in ICML 2024
[1] J. Guo, D. Xu, and G. Lu. CBANet: Toward Complexity and Bitrate Adaptive Deep Image Compression Using a Single Network. IEEE Transactions on Image Processing, 32: 2049–2062 (2023)
[2] C. He, Y. Ding, J. Guo, R. Gong, H. Qin, and X. Liu. DA-KD: Difficulty-Aware Knowledge Distillation for Efficient Large Language Models. Proceedings of the 42nd International Conference on Machine Learning (ICML), Proceedings of Machine Learning Research, 267: 22379–22391 (2025)
[3] G. Yang, C. He, J. Guo, J. Wu, Y. Ding, A. Liu, H. Qin, P. Ji, and X. Liu. LLMCBench: Benchmarking Large Language Model Compression for Efficient Deployment. Advances in Neural Information Processing Systems, 37: 87532–87544 (2024, Spotlight)
[4] J. Guo, J. Wu, Z. Wang, J. Liu, G. Yang, Y. Ding, R. Gong, H. Qin, and X. Liu. Compressing Large Language Models by Joint Sparsification and Quantization. Proceedings of the 41st International Conference on Machine Learning (ICML), Proceedings of Machine Learning Research, 235: 16945–16957 (2024)
[5] R. Gong, X. Liu, Y. Li, Y. Fan, X. Wei, and J. Guo. Pushing the Limit of Post-Training Quantization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 47(7): 5556–5570 (2025)