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

Chu-Ren Huang

ACL 2026×2可解释性社会与人本推理多模态数据与预训练
新星分资深
17
一作贡献0
核心/参与5
方向广度10
合作网络3
0 一作 · 2 篇 · ACL 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

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

Do LLM s Capture Embodied Cognition and Cultural Variation? Cross-Linguistic Evidence from Demonstratives

Yu Wang · Emmanuele Chersoni · Chu-Ren Huang

摘要

Do large language models (LLMs) truly acquire embodied cognition and cultural conventions from text? We introduce demonstratives, fundamental spatial expressions like “this/that” in English and “这/那” in Chinese, as a novel probe for grounded knowledge. Using 6,400 responses from 320 native speake...

可解释性社会与人本推理OpenReview 项目页
作者位次 #4/5ACL 2026Findings· Findings of ACL

New Compendium of a Myriad of Plants: A New Dataset Describing A ncient C hinese Plants

Xiaobin Shen · Zhongqing Wang · Shichen Li · Chu-Ren Huang · Guodong Zhou

摘要

In ancient China, a variety of datasets depicted humanistic scenes, geographical features, and plants. However, these datasets, compiled long ago, often contain errors, lack comprehensiveness, and are inconsistent with modern realities. To meet current demands, we aim to expand and improve ancien...

多模态数据与预训练检索与知识OpenReview 项目页

常见合作者