7 papers · 1 filter
Red-TTT: Test-Time Training for Automated Jailbreaking Large Language Models
Tongyan Hu, Hao Li, Xiaogeng Liu +8
Large language models remain vulnerable to jailbreaks, and automated red teaming is the standard way to find jailbreaks in large language models at scale. Current methods either dr…
Diffusion-Proof: Recipe for Formal Theorem Proving Beyond Auto-Regressive Generation
Ruida Wang, Rui Pan, Pengcheng Wang +2
Enhancing the formal math reasoning capabilities of Large Language Models (LLMs) has become a key focus in both mathematical and computer science communities in recent years. While…
Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory
Ruida Wang, Jerry Huang, Pengcheng Wang +3
Equipping Large Language Models (LLMs) to execute reliable multi-step workflows has become a central challenge in artificial intelligence. Despite recent advances in LLMs' agentic…
Code as Agent Harness
Xuying Ning, Katherine Tieu, Dongqi Fu +39
Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to repository-level software engineerin…
AgentSPEX: An Agent SPecification and EXecution Language
Pengcheng Wang, Jerry Huang, Jiarui Yao +7
Language-model agent systems commonly rely on reactive prompting, in which a single instruction guides the model through an open-ended sequence of reasoning and tool-use steps, lea…
PhysProver: Advancing Automatic Theorem Proving for Physics
Hanning Zhang, Ruida Wang, Rui Pan +3
The combination of verifiable languages and LLMs has significantly influenced both the mathematical and computer science communities because it provides a rigorous foundation for t…
Future-KL Regularized GRPO: Process-Level Credit Assignment from -Divergence Regularization
Jiarui Yao, Ruida Wang, Hao Bai +1
Group Relative Policy Optimization (GRPO) is widely used for critic-free Large Language Model (LLM) post-training, but its KL regularization is usually implemented as a local loss-…