Junfeng Fang

According to our database, Junfeng Fang authored at least 104 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Out-of-Distribution-Resistant Evaluations for Explanations of Graph Neural Networks.

Junfeng Fang, Hao Wu, An Zhang, Tianlong Chen, Kun Wang, Yuxuan Liang, Roger Zimmermann, Xiang Wang

IEEE Trans. Pattern Anal. Mach. Intell., July, 2026

Community-Driven Contrastive Learning: Enhancing Global Representation in Graph Neural Networks.

Wenhao Zhou, Zhenhua Huang, Shaojie Wang, Junfeng Fang, Zhaohong Jia, Linyuan Lv, Xiaohui Xie

IEEE Trans. Artif. Intell., June, 2026

Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments.

Yuxin Chen, Xiaodong Cai, Junfeng Fang, Zhuowen Han, Yu Wang, Yaorui Shi, Yi Zhang, Qi Gu, Xunliang Cai, Xiang Wang, An Zhang, Tat-Seng Chua

CoRR, May, 2026

UniVLR: Unifying Text and Vision in Visual Latent Reasoning for Multimodal LLMs.

Houcheng Jiang, Jiajun Fu, Junfeng Fang, Chen Gao, Xiang Wang, Xiangnan He, Yong Li

CoRR, May, 2026

Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation.

Yuchen Cai, Ding Cao, Liang Lin, Chunxi Luo, Xin Xu, Kai Yang, Weijie Liu, Saiyong Yang, Tianxiang Zhao, Guangzhong Sun, Guiquan Liu, Junfeng Fang

CoRR, May, 2026

SOD: Step-wise On-policy Distillation for Small Language Model Agents.

Qiyong Zhong, Mao Zheng, Mingyang Song, Xin Lin, Jie Sun, Houcheng Jiang, Xiang Wang, Junfeng Fang

CoRR, May, 2026

SimCT: Recovering Lost Supervision for Cross-Tokenizer On-Policy Distillation.

Jie Sun, Mao Zheng, Mingyang Song, Qiyong Zhong, Yilin Cheng, Bichuan Feng, Pengfei Liu, Junfeng Fang, Xiang Wang

CoRR, May, 2026

Rubric-based On-policy Distillation.

Junfeng Fang, Zhepei Hong, Mao Zheng, Mingyang Song, Gengsheng Li, Houcheng Jiang, Dan Zhang, Haiyun Guo, Xiang Wang, Tat-Seng Chua

CoRR, May, 2026

On the Implicit Reward Overfitting and the Low-rank Dynamics in RLVR.

Hao Ye, Jisheng Dang, Junfeng Fang, Bimei Wang, Yizhou Zhang, Ning Lv, Wencan Zhang, Hong Peng, Bin Hu, Tat-Seng Chua

CoRR, May, 2026

MIRL: Mutual Information-Guided Reinforcement Learning for Vision-Language Models.

Yin Zhang, Jiaxuan Zhao, Zonghan Wu, Zengxiang Li, Junfeng Fang, Kun Wang, Qingsong Wen, Yilei Shao

CoRR, May, 2026

DRAFT: Task Decoupled Latent Reasoning for Agent Safety.

Lin Wang, Junfeng Fang, Dan Zhang, Fei Shen, Xiang Wang, Tat-Seng Chua

CoRR, April, 2026

Unifying Group-Relative and Self-Distillation Policy Optimization via Sample Routing.

Gengsheng Li, Tianyu Yang, Junfeng Fang, Mingyang Song, Mao Zheng, Haiyun Guo, Dan Zhang, Jinqiao Wang, Tat-Seng Chua

CoRR, April, 2026

Principled Steering via Null-space Projection for Jailbreak Defense in Vision-Language Models.

Xingyu Zhu, Beier Zhu, Shuo Wang, Junfeng Fang, Kesen Zhao, Hanwang Zhang, Xiangnan He

CoRR, March, 2026

NExT-Guard: Training-Free Streaming Safeguard without Token-Level Labels.

Junfeng Fang, Nachuan Chen, Houcheng Jiang, Dan Zhang, Fei Shen, Xiang Wang, Xiangnan He, Tat-Seng Chua

CoRR, March, 2026

GuardAlign: Test-time Safety Alignment in Multimodal Large Language Models.

Xingyu Zhu, Beier Zhu, Junfeng Fang, Shuo Wang, Yin Zhang, Xiang Wang, Xiangnan He

CoRR, February, 2026

Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization.

Jinghan Li, Junfeng Fang, Jinda Lu, Yuan Wang, Xiaoyan Guo, Tianyu Zhang, Xiang Wang, Xiangnan He

CoRR, February, 2026

R-Diverse: Mitigating Diversity Illusion in Self-Play LLM Training.

Gengsheng Li, Jinghan He, Shijie Wang, Dan Zhang, Ruiqi Liu, Renrui Zhang, Zijun Yao, Junfeng Fang, Haiyun Guo, Jinqiao Wang

CoRR, February, 2026

SafeNeuron: Neuron-Level Safety Alignment for Large Language Models.

Zhaoxin Wang, Jiaming Liang, Fengbin Zhu, Weixiang Zhao, Junfeng Fang, Jiayi Ji, Handing Wang, Tat-Seng Chua

CoRR, February, 2026

AgentNoiseBench: Benchmarking Robustness of Tool-Using LLM Agents Under Noisy Condition.

Ruipeng Wang, Yuxin Chen, Yukai Wang, Chang Wu, Junfeng Fang, Xiaodong Cai, Qi Gu, Hui Su, An Zhang, Xiang Wang, Xunliang Cai, Tat-Seng Chua

CoRR, February, 2026

Active Zero: Self-Evolving Vision-Language Models through Active Environment Exploration.

Jinghan He, Junfeng Fang, Feng Xiong, Zijun Yao, Fei Shen, Haiyun Guo, Jinqiao Wang, Tat-Seng Chua

CoRR, February, 2026

Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control.

Yonghui Yang, Wenjian Tao, Jilong Liu, Xingyu Zhu, Junfeng Fang, Weibiao Huang, Le Wu, Richang Hong, Tat-Seng Chua

CoRR, February, 2026

From Data to Behavior: Predicting Unintended Model Behaviors Before Training.

Mengru Wang, Zhenqian Xu, Junfeng Fang, Yunzhi Yao, Shumin Deng, Huajun Chen, Ningyu Zhang

CoRR, February, 2026

The Missing Half: Unveiling Training-time Implicit Safety Risks Beyond Deployment.

Zhexin Zhang, Yida Lu, Junfeng Fang, Junxiao Yang, Shiyao Cui, Hao Zhou, Fandong Meng, Jie Zhou, Hongning Wang, Minlie Huang, Tat-Seng Chua

CoRR, February, 2026

LPEdit: Locality-Preserving Knowledge Editing for MultiModal Large Language Models.

Tianyu Zhang, Junfeng Fang, Houcheng Jiang, Xingyu Zhu, Xiang Wang, Xiangnan He

Proceedings of the ACM Web Conference 2026, 2026

Task-Aligned Unlearning for Multimodal Large Language Models.

Tianyu Zhang, Chenlu Ding, Junfeng Fang, Jiancan Wu, Xiang Wang

Proceedings of the Companion Proceedings of the ACM Web Conference 2026, 2026

RMBRec: Robust Multi-Behavior Recommendation towards Target Behaviors.

Miaomiao Cai, Zhijie Zhang, Junfeng Fang, Zhiyong Cheng, Xiang Wang, Meng Wang

Proceedings of the ACM Web Conference 2026, 2026

Privacy-Constrained Low-Bit Representation Learning for Person Image Retrieval.

Junfeng Fang, Yan Zhang, Manzhou Li, Xinjin Ge, Yan Li, Weiyuan Cui

Proceedings of the 2026 International Conference on Multimedia Retrieval, 2026

An Energy-Efficient Multimodal Retrieval Framework for Inference on Heterogeneous Edge Nodes.

Junfeng Fang, Yan Zhang, Mingyu Liu, Zhaoxi Feng, Manzhou Li, Yan Li

Proceedings of the 2026 International Conference on Multimedia Retrieval, 2026

Mitigating Hallucinations in Large Vision-Language Models without Performance Degradation.

Xingyu Zhu, Junfeng Fang, Shuo Wang, Beier Zhu, Zhicai Wang, Yonghui Yang, Xiangnan He

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Hierarchical Semantic Alignment for Image Clustering.

Xingyu Zhu, Beier Zhu, Yunfan Li, Junfeng Fang, Shuo Wang, Kesen Zhao, Hanwang Zhang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

3D-GSRD: 3D Molecular Graph Auto-Encoder with Selective Re-mask Decoding.

Chang Wu, Zhiyuan Liu, Wen Shu, Liang Wang, Yanchen Luo, Wenqiang Lei, Yatao Bian, Junfeng Fang, Xiang Wang

CoRR, October, 2025

Contrastive Weak-to-strong Generalization.

Houcheng Jiang, Junfeng Fang, Jiaxin Wu, Tianyu Zhang, Chen Gao, Yong Li, Xiang Wang, Xiangnan He, Yang Deng

CoRR, October, 2025

On Predictability of Reinforcement Learning Dynamics for Large Language Models.

Yuchen Cai, Ding Cao, Xin Xu, Zijun Yao, Yuqing Huang, Zhenyu Tan, Benyi Zhang, Guiquan Liu, Junfeng Fang

CoRR, October, 2025

Temporal Self-Rewarding Language Models: Decoupling Chosen-Rejected via Past-Future.

Yidong Wang, Xin Wang, Cunxiang Wang, Junfeng Fang, Qiufeng Wang, Jianing Chu, Xuran Meng, Shuxun Yang, Libo Qin, Yue Zhang, Wei Ye, Shikun Zhang

CoRR, August, 2025

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs.

Baolong Bi, Shenghua Liu, Xingzhang Ren, Dayiheng Liu, Junyang Lin, Yiwei Wang, Lingrui Mei, Junfeng Fang, Jiafeng Guo, Xueqi Cheng

CoRR, July, 2025

We Should Identify and Mitigate Third-Party Safety Risks in MCP-Powered Agent Systems.

Junfeng Fang, Zijun Yao, Ruipeng Wang, Haokai Ma, Xiang Wang, Tat-Seng Chua

CoRR, June, 2025

Mitigating Safety Fallback in Editing-based Backdoor Injection on LLMs.

Houcheng Jiang, Zetong Zhao, Junfeng Fang, Haokai Ma, Ruipeng Wang, Yang Deng, Xiang Wang, Xiangnan He

CoRR, June, 2025

AlphaSteer: Learning Refusal Steering with Principled Null-Space Constraint.

Leheng Sheng, Changshuo Shen, Weixiang Zhao, Junfeng Fang, Xiaohao Liu, Zhenkai Liang, Xiang Wang, An Zhang, Tat-Seng Chua

CoRR, June, 2025

Goal-Aware Identification and Rectification of Misinformation in Multi-Agent Systems.

Zherui Li, Yan Mi, Zhenhong Zhou, Houcheng Jiang, Guibin Zhang, Kun Wang, Junfeng Fang

CoRR, June, 2025

Are Reasoning Models More Prone to Hallucination?

Zijun Yao, Yantao Liu, Yanxu Chen, Jianhui Chen, Junfeng Fang, Lei Hou, Juanzi Li, Tat-Seng Chua

CoRR, May, 2025

Advanced long-term earth system forecasting by learning the small-scale nature.

Hao Wu, Yuan Gao, Ruiqi Shu, Kun Wang, Ruijian Gou, Chuhan Wu, Xinliang Liu, Juncai He, Shuhao Cao, Junfeng Fang, Xingjian Shi, Feng Tao, Qi Song, Shengxuan Ji, Yanfei Xiang, Yuze Sun, Jiahao Li, Fan Xu, Huanshuo Dong, Haixin Wang, Fan Zhang, Penghao Zhao, Xian Wu, Qingsong Wen, Deliang Chen, Xiaomeng Huang

CoRR, May, 2025

AudioTrust: Benchmarking the Multifaceted Trustworthiness of Audio Large Language Models.

Kai Li, Can Shen, Yile Liu, Jirui Han, Kelong Zheng, Xuechao Zou, Zhe Wang, Xingjian Du, Shun Zhang, Hanjun Luo, Yingbin Jin, Xinxin Xing, Ziyang Ma, Yue Liu, Xiaojun Jia, Yifan Zhang, Junfeng Fang, Kun Wang, Yibo Yan, Haoyang Li, Yiming Li, Xiaobin Zhuang, Yang Liu, Haibo Hu, Zhuo Chen, Zhizheng Wu, Xiaolin Hu, Eng-Siong Chng, XiaoFeng Wang, Wenyuan Xu, Wei Dong, Xinfeng Li

CoRR, May, 2025

UniErase: Unlearning Token as a Universal Erasure Primitive for Language Models.

Miao Yu, Liang Lin, Guibin Zhang, Xinfeng Li, Junfeng Fang, Ningyu Zhang, Kun Wang, Yang Wang

CoRR, May, 2025

Search and Refine During Think: Autonomous Retrieval-Augmented Reasoning of LLMs.

Yaorui Shi, Sihang Li, Chang Wu, Zhiyuan Liu, Junfeng Fang, Hengxing Cai, An Zhang, Xiang Wang

CoRR, May, 2025

GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning.

Yue Liu, Shengfang Zhai, Mingzhe Du, Yulin Chen, Tri Cao, Hongcheng Gao, Cheng Wang, Xinfeng Li, Kun Wang, Junfeng Fang, Jiaheng Zhang, Bryan Hooi

CoRR, May, 2025

Safety in Large Reasoning Models: A Survey.

Cheng Wang, Yue Liu, Baolong Li, Duzhen Zhang, Zhongzhi Li, Junfeng Fang

CoRR, April, 2025

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment.

Kun Wang, Guibin Zhang, Zhenhong Zhou, Jiahao Wu, Miao Yu, Shiqian Zhao, Chenlong Yin, Jinhu Fu, Yibo Yan, Hanjun Luo, Liang Lin, Zhihao Xu, Haolang Lu, Xinye Cao, Xinyun Zhou, Weifei Jin, Fanci Meng, Junyuan Mao, Hao Wu, Minghe Wang, Fan Zhang, Junfeng Fang, Chengwei Liu, Yifan Zhang, Qiankun Li, Chongye Guo, Yalan Qin, Yi Ding, Donghai Hong, Jiaming Ji, Xinfeng Li, Yifan Jiang, Dongxia Wang, Yihao Huang, Yufei Guo, Jen-tse Huang, Yanwei Yue, Wenke Huang, Guancheng Wan, Tianlin Li, Lei Bai, Jie Zhang, Qing Guo, Jingyi Wang, Tianlong Chen, Joey Tianyi Zhou, Xiaojun Jia, Weisong Sun, Cong Wu, Jing Chen, Xuming Hu, Yiming Li, Xiao Wang, Ningyu Zhang, Luu Anh Tuan, Guowen Xu, Tianwei Zhang, Xingjun Ma, Xiang Wang, Bo An, Jun Sun, Mohit Bansal, Shirui Pan, Yuval Elovici, Bhavya Kailkhura, Bo Li, Yaodong Yang, Hongwei Li, Wenyuan Xu, Yizhou Sun, Wei Wang, Qing Li, Ke Tang, Yu-Gang Jiang, Felix Juefei-Xu, Hui Xiong, Xiaofeng Wang, Shuicheng Yan, Dacheng Tao, Philip S. Yu, Qingsong Wen, Yang Liu

CoRR, April, 2025

REDEditing: Relationship-Driven Precise Backdoor Poisoning on Text-to-Image Diffusion Models.

Chongye Guo, Jinhu Fu, Junfeng Fang, Kun Wang, Guorui Feng

CoRR, April, 2025

SafeMLRM: Demystifying Safety in Multi-modal Large Reasoning Models.

Junfeng Fang, Yukai Wang, Ruipeng Wang, Zijun Yao, Kun Wang, An Zhang, Xiang Wang, Tat-Seng Chua

CoRR, April, 2025

Parameters vs. Context: Fine-Grained Control of Knowledge Reliance in Language Models.

Baolong Bi, Shenghua Liu, Yiwei Wang, Yilong Xu, Junfeng Fang, Lingrui Mei, Xueqi Cheng

CoRR, March, 2025

Multimodal Language Modeling for High-Accuracy Single Cell Transcriptomics Analysis and Generation.

Yaorui Shi, Jiaqi Yang, Sihang Li, Junfeng Fang, Cheng-Xiang Wang, Zhiyuan Liu, Yang Zhang

CoRR, March, 2025

AgentSafe: Safeguarding Large Language Model-based Multi-agent Systems via Hierarchical Data Management.

Junyuan Mao, Fanci Meng, Yifan Duan, Miao Yu, Xiaojun Jia, Junfeng Fang, Yuxuan Liang, Kun Wang, Qingsong Wen

CoRR, March, 2025

Addressing Delayed Feedback in Conversion Rate Prediction via Influence Functions.

Chenlu Ding, Jiancan Wu, Yancheng Yuan, Junfeng Fang, Cunchun Li, Xiang Wang, Xiangnan He

CoRR, February, 2025

LLM-Virus: Evolutionary Jailbreak Attack on Large Language Models.

Miao Yu, Junfeng Fang, Yingjie Zhou, Xing Fan, Kun Wang, Shirui Pan, Qingsong Wen

CoRR, January, 2025

Explainable and Efficient Editing for Large Language Models.

Tianyu Zhang, Junfeng Fang, Houcheng Jiang, Baolong Bi, Xiang Wang, Xiangnan He

Proceedings of the ACM on Web Conference 2025, 2025

A Comprehensive Security Evaluation Framework for Chinese Large Language Models.

Yuli Yang, Zhenhua Huang, Zhaohong Jia, Junfeng Fang

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Damage Analysis via Bidirectional Multi-Task Cascaded Multimodal Fusion.

Tao Liang, Siying Wu, Junfeng Fang, Guowu Yang, Wenya Wang, Fengmao Lv

Proceedings of the ACM on Web Conference 2025, 2025

SEHG: Bridging Interpretability and Prediction in Self-Explainable Heterogeneous Graph Neural Networks.

Zhenhua Huang, Wenhao Zhou, Yufeng Li, Xiuyang Wu, Chengpei Xu, Junfeng Fang, Zhaohong Jia, Linyuan Lü, Feng Xia

Proceedings of the ACM on Web Conference 2025, 2025

LIFEBENCH: Evaluating Length Instruction Following in Large Language Models.

Wei Zhang, Zhenhong Zhou, Kun Wang, Junfeng Fang, Rongwu Xu, Yuanhe Zhang, Rui Wang, Ge Zhang, Xinfeng Li, Li Sun, Lingjuan Lyu, Yang Liu, Sen Su

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning.

Yaorui Shi, Sihang Li, Chang Wu, Zhiyuan Liu, Junfeng Fang, Hengxing Cai, An Zhang, Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

ACE: Concept Editing in Diffusion Models without Performance Degradation.

Ruipeng Wang, Junfeng Fang, Jiaqi Li, Hao Chen, Jie Shi, Kun Wang, Xiang Wang

Proceedings of the 33rd ACM International Conference on Multimedia, 2025

G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks.

Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Tianlong Chen, Dawei Cheng

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Multi-agent Architecture Search via Agentic Supernet.

Guibin Zhang, Luyang Niu, Junfeng Fang, Kun Wang, Lei Bai, Xiang Wang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

DAMA: Data- and Model-aware Alignment of Multi-modal LLMs.

Jinda Lu, Junkang Wu, Jinghan Li, Xiaojun Jia, Shuo Wang, Yifan Zhang, Junfeng Fang, Xiang Wang, Xiangnan He

Proceedings of the Forty-second International Conference on Machine Learning, 2025

AnyEdit: Edit Any Knowledge Encoded in Language Models.

Houcheng Jiang, Junfeng Fang, Ningyu Zhang, Mingyang Wan, Guojun Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Reinforced Lifelong Editing for Language Models.

Zherui Li, Houcheng Jiang, Hao Chen, Baolong Bi, Zhenhong Zhou, Fei Sun, Junfeng Fang, Xiang Wang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

On the Role of Attention Heads in Large Language Model Safety.

Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Kun Wang, Yang Liu, Junfeng Fang, Yongbin Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Iterative Substructure Extraction for Molecular Relational Learning with Interactive Graph Information Bottleneck.

Shuai Zhang, Junfeng Fang, Xuqiang Li, Hongxin Xiang, Alan Xia, Ye Wei, Wenjie Du, Yang Wang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation.

Zhiyuan Liu, Yanchen Luo, Han Huang, Enzhi Zhang, Sihang Li, Junfeng Fang, Yaorui Shi, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector.

Jinghan Li, Yuan Gao, Jinda Lu, Junfeng Fang, Congcong Wen, Hui Lin, Xiang Wang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models.

Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi, Xiang Wang, Xiangnan He, Tat-Seng Chua

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness.

Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Junfeng Fang, Hongcheng Gao, Shiyu Ni, Xueqi Cheng

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Dynamic Multimodal Prototype Learning in Vision-Language Models.

Xingyu Zhu, Shuo Wang, Beier Zhu, Miaoge Li, Yunfan Li, Junfeng Fang, Zhicai Wang, Dongsheng Wang, Hanwang Zhang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

Safety in Large Reasoning Models: A Survey.

Cheng Wang, Yue Liu, Baolong Bi, Duzhen Zhang, Zhong-Zhi Li, Yingwei Ma, Yufei He, Shengju Yu, Xinfeng Li, Junfeng Fang, Jiaheng Zhang, Bryan Hooi

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation.

Zhenglin Hua, Jinghan He, Zijun Yao, Tianxu Han, Haiyun Guo, Yuheng Jia, Junfeng Fang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Knowledge Graph-Driven Memory Editing with Directional Interventions.

Jinhu Fu, Kun Wang, Chongye Guo, Junfeng Fang, Wentao Zhang, Sen Su

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Forget the Token and Pixel: Rethinking Gradient Ascent for Concept Unlearning in Multimodal Generative Models.

Jiaqi Li, Chuanyi Zhang, Miaozeng Du, Hui Zhang, Yongrui Chen, Qianshan Wei, Junfeng Fang, Ruipeng Wang, Sheng Bi, Guilin Qi

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Neuron-Level Sequential Editing for Large Language Models.

Houcheng Jiang, Junfeng Fang, Tianyu Zhang, Baolong Bi, An Zhang, Ruipeng Wang, Tao Liang, Xiang Wang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Cracking the Code of Hallucination in LVLMs with Vision-aware Head Divergence.

Jinghan He, Kuan Zhu, Haiyun Guo, Junfeng Fang, Zhenglin Hua, Yuheng Jia, Ming Tang, Tat-Seng Chua, Jinqiao Wang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Decoding by Contrasting Knowledge: Enhancing Large Language Model Confidence on Edited Facts.

Baolong Bi, Shenghua Liu, Lingrui Mei, Yiwei Wang, Junfeng Fang, Pengliang Ji, Xueqi Cheng

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Context-DPO: Aligning Language Models for Context-Faithfulness.

Baolong Bi, Shaohan Huang, Yiwei Wang, Tianchi Yang, Zihan Zhang, Haizhen Huang, Lingrui Mei, Junfeng Fang, Zehao Li, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang, Shenghua Liu

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Modeling Spatio-Temporal Dynamical Systems With Neural Discrete Learning and Levels-of-Experts.

Kun Wang, Hao Wu, Guibin Zhang, Junfeng Fang, Yuxuan Liang, Yuankai Wu, Roger Zimmermann, Yang Wang

IEEE Trans. Knowl. Data Eng., 2024

Fortune favors the invariant: Enhancing GNNs' generalizability with Invariant Graph Learning.

Guibin Zhang, Yiqiao Chen, Shiyu Wang, Kun Wang, Junfeng Fang

Knowl. Based Syst., 2024

Optimizing Multispectral Object Detection: A Bag of Tricks and Comprehensive Benchmarks.

Chen Zhou, Peng Cheng, Junfeng Fang, Yifan Zhang, Yibo Yan, Xiaojun Jia, Yanyan Xu, Kun Wang, Xiaochun Cao

CoRR, 2024

On the Role of Attention Heads in Large Language Model Safety.

Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Kun Wang, Yang Liu, Junfeng Fang, Yongbin Li

CoRR, 2024

G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks.

Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Dawei Cheng

CoRR, 2024

Neuron-Level Sequential Editing for Large Language Models.

Houcheng Jiang, Junfeng Fang, Tianyu Zhang, An Zhang, Ruipeng Wang, Tao Liang, Xiang Wang

CoRR, 2024

Text-guided Diffusion Model for 3D Molecule Generation.

Yanchen Luo, Junfeng Fang, Sihang Li, Zhiyuan Liu, Jiancan Wu, An Zhang, Wenjie Du, Xiang Wang

CoRR, 2024

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models.

Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua

CoRR, 2024

Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia.

Miao Yu, Junyuan Mao, Guibin Zhang, Jingheng Ye, Junfeng Fang, Aoxiao Zhong, Yang Liu, Yuxuan Liang, Kun Wang, Qingsong Wen

CoRR, 2024

StruEdit: Structured Outputs Enable the Fast and Accurate Knowledge Editing for Large Language Models.

Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Hongcheng Gao, Junfeng Fang, Xueqi Cheng

CoRR, 2024

EXGC: Bridging Efficiency and Explainability in Graph Condensation.

Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He

CoRR, 2024

Invariant Graph Learning for Causal Effect Estimation.

Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang

Proceedings of the ACM on Web Conference 2024, 2024

Graph Anomaly Detection with Bi-level Optimization.

Yuan Gao, Junfeng Fang, Yongduo Sui, Yangyang Li, Xiang Wang, Huamin Feng, Yongdong Zhang

Proceedings of the ACM on Web Conference 2024, 2024

EXGC: Bridging Efficiency and Explainability in Graph Condensation.

Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He

Proceedings of the ACM on Web Conference 2024, 2024

Towards Neuron Attributions in Multi-Modal Large Language Models.

Junfeng Fang, Zac Bi, Ruipeng Wang, Houcheng Jiang, Yuan Gao, Kun Wang, An Zhang, Jie Shi, Xiang Wang, Tat-Seng Chua

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs.

Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field.

Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Junfeng Fang, Xiaojiang Peng, Yuxuan Liang, Yang Wang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction.

Wenjie Du, Shuai Zhang, Di Wu, Jun Xia, Ziyuan Zhao, Junfeng Fang, Yang Wang

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness.

Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MolTC: Towards Molecular Relational Modeling In Language Models.

Junfeng Fang, Shuai Zhang, Chang Wu, Zhengyi Yang, Zhiyuan Liu, Sihang Li, Kun Wang, Wenjie Du, Xiang Wang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Cooperative Explanations of Graph Neural Networks.

Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis.

Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective.

Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang

Proceedings of the Eleventh International Conference on Learning Representations, 2023