5 papers
ProAct: Agentic Lookahead in Interactive Environments
Yangbin Yu, Mingyu Yang, Junyou Li +9
Existing Large Language Model (LLM) agents struggle in interactive environments requiring long-horizon planning, primarily due to compounding errors when simulating future states.…
SeeNav-Agent: Enhancing Vision-Language Navigation with Visual Prompt and Step-Level Policy Optimization
Zhengcheng Wang, Zichuan Lin, Yijun Yang +2
Existing Vision-Language Navigation (VLN) agents based on Large Vision-Language Models (LVLMs) often suffer from perception errors, reasoning errors, and planning errors, which sig…
Vul-R2: A Reasoning LLM for Automated Vulnerability Repair
Xin-Cheng Wen, Zirui Lin, Yijun Yang +2
The exponential increase in software vulnerabilities has created an urgent need for automatic vulnerability repair (AVR) solutions. Recent research has formulated AVR as a sequence…
Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning Data
Xin-Cheng Wen, Yijun Yang, Cuiyun Gao +2
Large language models (LLMs) demonstrate considerable proficiency in numerous coding-related tasks; however, their capabilities in detecting software vulnerabilities remain limited…
GTR: Guided Thought Reinforcement Prevents Thought Collapse in RL-based VLM Agent Training
Tong Wei, Yijun Yang, Junliang Xing +3
Reinforcement learning with verifiable outcome rewards (RLVR) has effectively scaled up chain-of-thought (CoT) reasoning in large language models (LLMs). Yet, its efficacy in train…