paper.dinq.meAI 与前沿科学顶会 · 学术新星雷达
登录 DINQ
返回新星榜
PL

Peizhuo Lv

ACL 2026×2CCS 2026安全强化学习与后训练对齐与偏好理论与学习动力学推理
新星分新星
75
一作贡献30
核心/参与21
方向广度13
合作网络12
1 一作 · 3 篇 · ACL 2026 / CCS 2026

获取完整研究档案

首次获取该候选人的完整档案及 StartLux 评估共 20 积分;每位用户单独解锁,之后查看免费。主动刷新 20 积分。

联系方式

实时查找电子邮箱,费用不超过20积分;未找到邮箱不扣费。

2026 顶会论文

3
作者位次 #2/3ACL 2026Poster· Natural Language Processing

PROMPRINT : Prompt Fingerprinting via First-Token Response for LLM App Cloning Detection

Jungmin Lee · Peizhuo Lv · Yeonjoon Lee

摘要

As Large Language Model applications (LLM apps) become widespread, system prompts that determine app behavior are increasingly regarded as intellectual property, raising concerns about leakage. Recent studies show that this threat is no longer theoretical, revealing the prevalence of cloned apps...

对齐与偏好安全理论与学习动力学OpenReview 项目页
一作ACL 2026Poster· Natural Language Processing

R eas M ark: A Robust Watermark for Attributing LLM Reasoning Under Knowledge Distillation Attacks

Peizhuo Lv · Ruihua Zhou · Yunpeng Li · Ruigang Liang · Xingshuo Han · XiaoFeng Wang · Wei Dong · Yuling Liu

摘要

Reasoning-enhanced large language models rely on intermediate reasoning signals to solve complex, multi-step tasks, making reasoning behavior a valuable form of intellectual property. Meanwhile, knowledge distillation enables an adversary to replicate this behavior in a realistic black-box settin...

安全推理强化学习与后训练OpenReview 项目页

常见合作者