5 papers
FormaTheoria: Constructing Large-Scale Lean Theories from Mathematical Literature Toward the Formalization of the Classification of Finite Simple Groups
Tianjiao Nie, Ao Zhang, Yusen Tang +4
Large-scale formalization of advanced mathematics requires more than translating individual statements: it must reconstruct a coherent theory distributed across heterogeneous sourc…
SF-AMS: Strategic Forgetting for Structured Memory in LLM Agent
Ning Yang, Siqi Li, Miaoxin Shen +4
Managing long-context dependencies remains a primary bottleneck in LLM agents, as redundant and irrelevant information can degrade multi-step reasoning. Strategic Forgetting for Ag…
Towards Intrinsic Interpretability of Large Language Models:A Survey of Design Principles and Architectures
Yutong Gao, Qinglin Meng, Yuan Zhou +1
While Large Language Models (LLMs) have achieved strong performance across many NLP tasks, their opaque internal mechanisms hinder trustworthiness and safe deployment. Existing sur…
Backdoors in RLVR: Jailbreak Backdoors in LLMs From Verifiable Reward
Weiyang Guo, Zesheng Shi, Zeen Zhu +3
Reinforcement Learning with Verifiable Rewards (RLVR) is an emerging paradigm that significantly boosts a Large Language Model's (LLM's) reasoning abilities on complex logical task…
A Neural Symbolic Model for Space Physics
Jie Ying, Haowei Lin, Chao Yue +7
In this study, we unveil a new AI model, termed PhyE2E, to discover physical formulas through symbolic regression. PhyE2E simplifies symbolic regression by decomposing it into sub-…