4 papers
PORTool: Importance-Aware Policy Optimization with Rewarded Tree for Multi-Tool-Integrated Reasoning
Feijie Wu, Weiwu Zhu, Yuxiang Zhang +5
Multi-tool-integrated reasoning enables LLM-empowered tool-use agents to solve complex tasks by interleaving natural-language reasoning with calls to external tools. However, train…
Towards Privacy-Preserving and Heterogeneity-aware Split Federated Learning via Probabilistic Masking
Xingchen Wang, Feijie Wu, Chenglin Miao +5
Split Federated Learning (SFL) has emerged as an efficient alternative to traditional Federated Learning (FL) by reducing client-side computation through model partitioning. Howeve…
SUV: Scalable Large Language Model Copyright Compliance with Regularized Selective Unlearning
Tianyang Xu, Xiaoze Liu, Feijie Wu +2
Large Language Models (LLMs) have transformed natural language processing by learning from massive datasets, yet this rapid progress has also drawn legal scrutiny, as the ability t…
Talk to Right Specialists: Iterative Routing in Multi-agent Systems for Question Answering
Feijie Wu, Zitao Li, Fei Wei +3
Retrieval-augmented generation (RAG) agents are increasingly deployed to answer questions over local knowledge bases that cannot be centralized due to knowledge-sovereignty constra…