4 citations · 6 across the 8 of their papers we have counts for
9 papers
Relax: An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale
Liujie Zhang, Benzhe Ning, Rui Yang +8
Reinforcement learning (RL) post-training has proven effective at unlocking reasoning, self-reflection, and tool-use capabilities in large language models. As models extend to omni…
Towards Compositional Generalization of LLMs via Skill Taxonomy Guided Data Synthesis
Yifan Wei, Li Du, Xiaoyan Yu +2
Large Language Models (LLMs) and agent-based systems often struggle with compositional generalization due to a data bottleneck in which complex skill combinations follow a long-tai…
AutoTIR: Autonomous Tools Integrated Reasoning via Reinforcement Learning
Yifan Wei, Xiaoyan Yu, Yixuan Weng +3
Large Language Models (LLMs), when enhanced through reasoning-oriented post-training, evolve into powerful Large Reasoning Models (LRMs). Tool-Integrated Reasoning (TIR) further ex…
Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs
Yifan Wei, Xiaoyan Yu, Tengfei Pan +2
Large language models (LLMs) have achieved unprecedented performance by leveraging vast pretraining corpora, yet their performance remains suboptimal in knowledge-intensive domains…
SetKE: Knowledge Editing for Knowledge Elements Overlap
Yifan Wei, Xiaoyan Yu, Ran Song +2
Large Language Models (LLMs) excel in tasks such as retrieval and question answering but require updates to incorporate new knowledge and reduce inaccuracies and hallucinations. Tr…
Does Knowledge Localization Hold True? Surprising Differences Between Entity and Relation Perspectives in Language Models
Yifan Wei, Xiaoyan Yu, Yixuan Weng +4
Large language models encapsulate knowledge and have demonstrated superior performance on various natural language processing tasks. Recent studies have localized this knowledge to…
DAMe: Personalized Federated Social Event Detection with Dual Aggregation Mechanism
Xiaoyan Yu, Yifan Wei, Pu Li +5
Training social event detection models through federated learning (FedSED) aims to improve participants' performance on the task. However, existing federated learning paradigms are…
Assessing Knowledge Editing in Language Models via Relation Perspective
Yifan Wei, Xiaoyan Yu, Huanhuan Ma +4
Knowledge Editing (KE) for modifying factual knowledge in Large Language Models (LLMs) has been receiving increasing attention. However, existing knowledge editing methods are enti…
MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Models
Yifan Wei, Yisong Su, Huanhuan Ma +5
Large language models (LLMs) have shown nearly saturated performance on many natural language processing (NLP) tasks. As a result, it is natural for people to believe that LLMs hav…