2 citations · 6 across the 11 of their papers we have counts for
7 papers · 1 filter
Which Knowledge Should LLMs Trust? Uncovering a Generalizable Steering Direction Across Knowledge Conflicts
Yibin Lou, Yi Hu, Jianhui Chen +3
Large Language Models (LLMs) frequently encounter conflicts between internal parametric knowledge and external contextual knowledge, yet the mechanisms governing this selection rem…
Knowledge Interaction in Hypernetwork-based Continual Learning: Conflict and Composition
Jiaqi Zheng, Yi Hu, Yadong Mu +1
Continual learning aims to adapt pretrained large language models (LLMs) to evolving data while preserving their pretrained capabilities. A central challenge is catastrophic forget…
ContinualSkillBench: Can LLM Agents Truly Evolve Their Capabilities?
Tianyi Guan, Yiding Wang, Haotong Yang +5
Modern agent frameworks equip large language models with external skill libraries to solve complex tasks. However, it remains unclear whether these systems can effectively evolve t…
Position: How can Graphs Help Large Language Models?
Xiyuan Wang, Yi Hu, Yanbo Wang +2
With the rapid advancement of large language models (LLMs), classic graph learning tasks have greatly benefited from LLMs, including improved encoding of textual features, more eff…
ProofVerifier: A Scalable, Diversity-Driven Framework for Natural-Language Proof Verification
Haotong Yang, Zitong Wang, Shijia Kang +7
While large language models (LLMs) have achieved strong performance on mathematical problems with verifiable answers, many advanced problems are proof-based and require evaluating…
SubTokenTest: A Practical Benchmark for Real-World Sub-token Understanding
Shuyang Hou, Yi Hu, Muhan Zhang
Recent advancements in large language models (LLMs) have significantly enhanced their reasoning capabilities. However, they continue to struggle with basic character-level tasks, s…
Towards a Mechanistic Understanding of Large Reasoning Models: A Survey of Training, Inference, and Failures
Yi Hu, Jiaqi Gu, Ruxin Wang +6
Reinforcement learning (RL) has catalyzed the emergence of Large Reasoning Models (LRMs) that have pushed reasoning capabilities to new heights. While their performance has garnere…