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

Xia Hu

ACL 2026×2KDD 2026强化学习与后训练推理效率与系统对齐与偏好安全
新星分资深
28
一作贡献0
核心/参与9
方向广度13
合作网络12
0 一作 · 3 篇 · ACL 2026 / KDD 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 #11/11ACL 2026Findings· Findings of ACL

A uto L 2 S : Auto Long-Short Reasoning for Efficient Large Language Models

Feng Luo · Yu-Neng Chuang · Guanchu Wang · Hoang Anh Duy Le · Shaochen Zhong · Hongyi Liu · Jiayi Yuan · Yang Sui · Vladimir Braverman · Vipin Chaudhary · Xia Hu

摘要

Reasoning-capable large language models (LLMs) achieve strong performance on complex tasks but often exhibit overthinking after distillation, generating unnecessarily long chain-of-thought (CoT) reasoning even for simple inputs and incurring high inference cost. However, naively shortening reason...

推理强化学习与后训练效率与系统OpenReview 项目页
作者位次 #3/3ACL 2026Findings· Findings of ACL

MASH : Evading Black-Box AI -Generated Text Detectors via Style Humanization

Yongtong Gu · Songze Li · Xia Hu

摘要

The increasing misuse of AI-generated texts (AIGT) has motivated the rapid development of AIGT detection methods. However, the reliability of these detectors remains fragile against adversarial evasions. Existing attack strategies often rely on white-box assumptions or demand prohibitively high c...

对齐与偏好安全强化学习与后训练OpenReview 项目页

常见合作者