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

Weida Wang

KDD 2026×2ACL 2026ICLR 2026评测与基准推理检索与知识强化学习与后训练效率与系统
新星分新星
90
一作贡献80
核心/参与21
方向广度16
合作网络12
2 一作 · 4 篇 · KDD 2026 / ACL 2026 / ICLR 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

4
一作ICLR 2026Poster· Applications / Physics

CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

Weida Wang · Dongchen Huang · Jiatong LI · Tengchao Yang · Ziyang Zheng · Chuyi Peng · Di Zhang · Dong Han · Benteng Chen · Binzhao Luo · Zhiyu Liu · kunling liu · Zhiyuan Gao · Shiqigeng geng · Wei Ma · Jiaming Su · Xin Li · Shuchen Pu · Yuhan Shui · Qianjia Cheng · Zhihao Dou · Dongfei Cui · Changyong He · Jin Zeng · Zeke Xie · Mao Su · Dongzhan Zhou · Yuqiang Li · Wanli Ouyang · Yunqi Cai · Xi Dai · Shufei Zhang · LEI BAI · Jinguang Cheng · Zhong Fang · Hongming Weng

评测与基准OpenReview
作者位次 #2/5ACL 2026Poster· Natural Language Processing

Step- GRPO : Internalizing Dynamic Early Exit for Efficient Reasoning

Benteng Chen · Weida Wang · Shufei Zhang · Mingbao Lin · Min Zhang

摘要

Large reasoning models that use long chain-of-thought excel at problem-solving yet waste compute on redundant checks. Curbing this overthinking is hard: training-time length penalties can cripple ability, while inference-time early-exit adds system overhead. To bridge this gap, we propose Step-GR...

推理强化学习与后训练效率与系统OpenReview 项目页

常见合作者