6 citations · 6 across the 12 of their papers we have counts for
7 papers · 1 filter
Learning What to Remember and What to Internalize in LLM Self-Evolution via Adaptive Memory-Parameter Coordination
Tianyun Ji, Zhenya Huang, Jiayu Liu +3
Large language model agents increasingly operate in dynamic environments where tool interfaces, APIs, and user requirements change after deployment. Existing self-evolution methods…
MathCoPilot: An Interactive System for Human-AI Symbiotic Paradigm of Mathematical Research
Junjie Zhang, Jiayu Liu, Wenbin Liu +11
Existing LLM-based theorem provers have achieved impressive results on formal mathematics benchmarks, yet they remain confined to acting as autonomous agents that prove a stated pr…
What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code
Yuze Zhao, Junpeng Fang, Lu Yu +6
Code has become a standard component of modern foundation language model (LM) training, yet its role beyond programming remains unclear. We revisit the claim that code improves rea…
UniCog: Uncovering Cognitive Abilities of LLMs through Latent Mind Space Analysis
Jiayu Liu, Yinhe Long, Zhenya Huang +1
A growing body of research suggests that the cognitive processes of large language models (LLMs) differ fundamentally from those of humans. However, existing interpretability metho…
Verifying Large Language Models' Reasoning Paths via Correlation Matrix Rank
Jiayu Liu, Wei Dai, Zhenya Huang +2
Despite the strong reasoning ability of large language models~(LLMs), they are prone to errors and hallucinations. As a result, how to check their outputs effectively and efficient…
Foundation of Intelligence: Review of Math Word Problems from Human Cognition Perspective
Zhenya Huang, Jiayu Liu, Xin Lin +6
Math word problem (MWP) serves as a fundamental research topic in artificial intelligence (AI) dating back to 1960s. This research aims to advance the reasoning abilities of AI by…