Shuo He

According to our database, Shuo He authored at least 26 papers between 2017 and 2026.

Collaborative distances:

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

2026

Beyond Trajectory-Level Attribution: Graph-Based Credit Assignment for Agentic Reinforcement Learning.

Xin Cheng, Shuo He, Lang Feng, Haiyang Xu, Ming Yan, Lei Feng, Bo An

CoRR, May, 2026

Test-Time Attention Purification for Backdoored Large Vision Language Models.

Zhifang Zhang, Bojun Yang, Shuo He, Weitong Chen, Wei Emma Zhang, Olaf Maennel, Lei Feng, Miao Xu

CoRR, March, 2026

Hierarchy-of-Groups Policy Optimization for Long-Horizon Agentic Tasks.

Shuo He, Lang Feng, Qi Wei, Xin Cheng, Lei Feng, Bo An

CoRR, February, 2026

Phase-Aware Mixture of Experts for Agentic Reinforcement Learning.

Shengtian Yang, Yu Li, Shuo He, Yewen Li, Qingpeng Cai, Peng Jiang, Lei Feng

CoRR, February, 2026

Online Causal Kalman Filtering for Stable and Effective Policy Optimization.

Shuo He, Lang Feng, Xin Cheng, Lei Feng, Bo An

CoRR, February, 2026

Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems.

Lang Feng, Longtao Zheng, Shuo He, Fuxiang Zhang, Bo An

CoRR, February, 2026

2025

Improving Generalizability and Undetectability for Targeted Adversarial Attacks on Multimodal Pre-trained Models.

Zhifang Zhang, Jiahan Zhang, Shengjie Zhou, Qi Wei, Shuo He, Feng Liu, Lei Feng

CoRR, September, 2025

Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning.

Zhifang Zhang, Shuo He, Haobo Wang, Bingquan Shen, Lei Feng

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

Test-Time Multimodal Backdoor Detection by Contrastive Prompting.

Yuwei Niu, Shuo He, Qi Wei, Zongyu Wu, Feng Liu, Lei Feng

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

Representation Surgery in Model Merging with Probabilistic Modeling.

Qi Wei, Shuo He, Enneng Yang, Tingcong Liu, Haobo Wang, Lei Feng, Bo An

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

A Closer Look at Backdoor Attacks on CLIP.

Shuo He, Zhifang Zhang, Feng Liu, Roy Ka-Wei Lee, Bo An, Lei Feng

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

Influence-Based Fair Selection for Sample-Discriminative Backdoor Attack.

Qi Wei, Shuo He, Jiahan Zhang, Lei Feng, Bo An

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning.

Zhifang Zhang, Shuo He, Bingquan Shen, Lei Feng

CoRR, 2024

BDetCLIP: Multimodal Prompting Contrastive Test-Time Backdoor Detection.

Yuwei Niu, Shuo He, Qi Wei, Feng Liu, Lei Feng

CoRR, 2024

Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning.

Shuo He, Chaojie Wang, Guowu Yang, Lei Feng

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Partial-label Learning with Mixed Closed-set and Open-set Out-of-candidate Examples.

Shuo He, Lei Feng, Guowu Yang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Candidate-aware Selective Disambiguation Based On Normalized Entropy for Instance-dependent Partial-label Learning.

Shuo He, Guowu Yang, Lei Feng

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A Generalized Unbiased Risk Estimator for Learning with Augmented Classes.

Senlin Shu, Shuo He, Haobo Wang, Hongxin Wei, Tao Xiang, Lei Feng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Incorporating multiple cluster centers for multi-label learning.

Senlin Shu, Fengmao Lv, Yan Yan, Li Li, Shuo He, Jun He

Inf. Sci., 2022

Partial Label Learning with Semantic Label Representations.

Shuo He, Lei Feng, Fengmao Lv, Wen Li, Guowu Yang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2020

Incorporating Multiple Cluster Centers for Multi-Label Learning.

Senlin Shu, Fengmao Lv, Lei Feng, Jun Huang, Shuo He, Jun He, Li Li

CoRR, 2020

2019

Discriminatively Relabel for Partial Multi-label Learning.

Shuo He, Ke Deng, Li Li, Senlin Shu, Li Liu

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Collaboration Based Multi-Label Learning.

Lei Feng, Bo An, Shuo He

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Content tracking by leveraging hashtag and time information in Twitter social media.

Xiaofei Xu, Li Li, Jinjing Zhang, Jing Wang, Shuo He

Web Intell., 2018

Estimating Latent Relative Labeling Importances for Multi-label Learning.

Shuo He, Lei Feng, Li Li

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

IIRank: Co-Ranking Scientific Articles by Characterizing their Innovativeness and Importance.

Fan Li, Zili Zhang, Li Li, Xiaofei Xu, Shuo He

Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing, 2017