Huang, Yongfeng

18 publications

NeurIPS 2025 Black-Box Membership Inference Attack for LVLMs via Prior Knowledge-Calibrated Memory Probing Jinhua Yin, Peiru Yang, Chen Yang, Huili Wang, Zhiyang Hu, Shangguang Wang, Yongfeng Huang, Tao Qi

TMLR 2025 Efficient Diffusion Models: A Survey Hui Shen, Jingxuan Zhang, Boning Xiong, Rui Hu, Shoufa Chen, Zhongwei Wan, Xin Wang, Yu Zhang, Zixuan Gong, Guangyin Bao, Chaofan Tao, Yongfeng Huang, Ye Yuan, Mi Zhang

NeurIPS 2025 SWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications Jinyang Li, Xiaolong Li, Ge Qu, Per Jacobsson, Bowen Qin, Binyuan Hui, Shuzheng Si, Nan Huo, Xiaohan Xu, Yue Zhang, Ziwei Tang, Yuanshuai Li, Florensia Widjaja, Xintong Zhu, Feige Zhou, Yongfeng Huang, Yannis Papakonstantinou, Fatma Ozcan, Chenhao Ma, Reynold Cheng

AAAI 2025 Training with "Paraphrasing the Original Text" Teaches LLM to Better Retrieve in Long-Context Tasks Yijiong Yu, Yongfeng Huang, Zhixiao Qi, Zhe Zhou

AAAI 2025 pFedGPA: Diffusion-Based Generative Parameter Aggregation for Personalized Federated Learning Jiahao Lai, Jiaqi Li, Jian Xu, Yanru Wu, Boshi Tang, Siqi Chen, Yongfeng Huang, Wenbo Ding, Yang Li

ICMLW 2024 Mitigate Position Bias in Large Language Models via Scaling a Single Dimension Yijiong Yu, Huiqiang Jiang, Xufang Luo, Qianhui Wu, Chin-Yew Lin, Dongsheng Li, Yuqing Yang, Yongfeng Huang, Lili Qiu

ACML 2024 RedditEM: Unveiling Diachronic Semantic Shifts in Social Network Discourse Jiajun Zou, Sixing Wu, Jinshuai Yang, Minghu Jiang, Yongfeng Huang

AAAI 2024 Towards the Robustness of Differentially Private Federated Learning Tao Qi, Huili Wang, Yongfeng Huang

IJCAI 2023 FedSampling: A Better Sampling Strategy for Federated Learning Tao Qi, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie

NeurIPS 2022 FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning Tao Qi, Fangzhao Wu, Chuhan Wu, Lingjuan Lyu, Tong Xu, Hao Liao, Zhongliang Yang, Yongfeng Huang, Xing Xie

IJCAI 2022 Rethinking InfoNCE: How Many Negative Samples Do You Need? Chuhan Wu, Fangzhao Wu, Yongfeng Huang

AAAI 2021 Distribution Matching for Rationalization Yongfeng Huang, Yujun Chen, Yulun Du, Zhilin Yang

AAAI 2021 Fairness-Aware News Recommendation with Decomposed Adversarial Learning Chuhan Wu, Fangzhao Wu, Xiting Wang, Yongfeng Huang, Xing Xie

IJCAI 2021 User-as-Graph: User Modeling with Heterogeneous Graph Pooling for News Recommendation Chuhan Wu, Fangzhao Wu, Yongfeng Huang, Xing Xie

IJCAI 2020 User Modeling with Click Preference and Reading Satisfaction for News Recommendation Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang

IJCAI 2019 Neural News Recommendation with Attentive Multi-View Learning Chuhan Wu, Fangzhao Wu, Mingxiao An, Jianqiang Huang, Yongfeng Huang, Xing Xie

AAAI 2016 Personalized Microblog Sentiment Classification via Multi-Task Learning Fangzhao Wu, Yongfeng Huang

AAAI 2015 Microblog Sentiment Classification with Contextual Knowledge Regularization Fangzhao Wu, Yangqiu Song, Yongfeng Huang