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Jian Luo

AwardACL 2026×2ICLR 2026×2推理强化学习与后训练可解释性数据与预训练多模态
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0 一作 · 4 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

4
作者位次 #3/9ACL 2026Poster· Natural Language Processing

R e C reate: Reasoning and Creating Domain Agents Driven by Experience

Zhezheng Hao · Hong Wang · Jian Luo · Jianqing Zhang · Yuyan Zhou · Qiang Lin · Can Wang · Hande Dong · Jiawei Chen

摘要

Large Language Model (LLM) agents are reshaping the industrial landscape. However, most practical agents remain human-designed because tasks differ widely, making them labor-intensive to build. This situation poses a central question: can we automatically create and adapt domain agents in the wil...

推理智能体与工具可解释性OpenReview 项目页
作者位次 #4/9ACL 2026OralOutstanding Paper· Natural Language Processing

Rethinking Entropy Interventions in RLVR : An Entropy Change Perspective

Zhezheng Hao · Hong Wang · Haoyang Liu · Jian Luo · Jiarui Yu · Hande Dong · Qiang Lin · Can Wang · Jiawei Chen

摘要

Reinforcement Learning with Verifiable Rewards (RLVR) serves as a cornerstone technique for enhancing the reasoning capabilities of Large Language Models (LLMs). However, its training is often plagued by entropy collapse , a rapid decline in policy entropy that limits exploration and undermines t...

强化学习与后训练推理可解释性OpenReview 项目页

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