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Jia Li

ACL 2026×2推理智能体与工具代码强化学习与后训练多模态
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #3/5ACL 2026Findings· Findings of ACL

V ul A gent: Hypothesis-Validation Driven Multi-Agent Architecture for Vulnerability Detection

Ziliang Wang · Ge Li · Jia Li · Hao Zhu · Zhi Jin

摘要

Vulnerability detection with language models is challenging: it requires (i) precisely localizing security-sensitive code and (ii) reasoning about potential vulnerability conditions under complex, partially observed program context. We present VulAgent, a multi-agent vulnerability detection frame...

智能体与工具代码推理OpenReview 项目页
作者位次 #2/9ACL 2026Findings· Findings of ACL

E vo C o T : Overcoming the Exploration Bottleneck in Reinforcement Learning for LLM s

Huanyu Liu · Jia Li · Yihong Dong · Chang Yu · Taozhi Chen · Lecheng Wang · Yongding Tao · Bin Gu · Ge Li

摘要

Reinforcement learning with verifiable reward (RLVR) has become a promising paradigm for post-training large language models (LLMs) to improve their reasoning capability. However, when the rollout accuracy is low on hard problems, the reward becomes sparse, limiting learning efficiency and causin...

强化学习与后训练推理多模态OpenReview 项目页

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