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Haizhong Zheng

ICLR 2026×3ACL 2026强化学习与后训练对齐与偏好安全智能体与工具评测与基准
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一作贡献30
核心/参与15
方向广度13
合作网络9
1 一作 · 4 篇 · ICLR 2026 / ACL 2026

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2026 顶会论文

4
作者位次 #4/5ICLR 2026Poster· Reinforcement Learning / Everything Else

OPPO: Accelerating PPO-based RLHF via Pipeline Overlap

Kaizhuo Yan · YingJie Yu · Yifan Yu · Haizhong Zheng · Fan Lai

强化学习与后训练对齐与偏好OpenReview
一作ICLR 2026Poster

Prosperity before Collapse: How Far Can Off-Policy RL Reach with Stale Data on LLMs?

Haizhong Zheng · Jiawei Zhao · Beidi Chen

强化学习与后训练OpenReview
作者位次 #8/9ACL 2026Poster· Natural Language Processing

When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?

Yibo Peng · James Song · Lei Li · Xinyu Yang · Mihai Christodorescu · Ravi Mangal · Corina S. Pasareanu · Haizhong Zheng · Beidi Chen

摘要

Code agents are increasingly trusted to autonomously fix bugs on platforms such as GitHub, yet their security evaluation focuses almost exclusively on functional correctness. In this paper, we reveal a novel type of threat to real-world code-agents: functionally correct yet vulnerable (FCV) patch...

安全智能体与工具评测与基准OpenReview 项目页

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