3 papers
cs.SE2025
ReVeal: Self-Evolving Code Agents via Reliable Self-Verification
Yiyang Jin, Kunzhao Xu, Hang Li +4
Reinforcement learning with verifiable rewards (RLVR) has advanced the reasoning capabilities of large language models. However, existing methods rely solely on outcome rewards, wi…
cs.LG2025
Vulnerability-Aware Alignment: Mitigating Uneven Forgetting in Harmful Fine-Tuning
Liang Chen, Xueting Han, Li Shen +2
Harmful fine-tuning (HFT), performed directly on open-source LLMs or through Fine-tuning-as-a-Service, breaks safety alignment and poses significant threats. Existing methods aim t…
cs.AI2024
CPL: Critical Plan Step Learning Boosts LLM Generalization in Reasoning Tasks
Tianlong Wang, Junzhe Chen, Xueting Han +1
Post-training, particularly reinforcement learning (RL) using self-play-generated data, has become a new learning paradigm for large language models (LLMs). However, scaling RL to…