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

Chen Gao

AAAI 2026×4ICML 2026×3ACL 2026×2KDD 2026×2评测与基准多模态推理检索与知识智能体与工具
新星分贡献者
84
一作贡献0
核心/参与70
方向广度19
合作网络12
0 一作 · 11 篇 · AAAI 2026 / ICML 2026 / 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

11
作者位次 #3/7ACL 2026Poster· Natural Language Processing

Learn to Relax with Large Language Models: Solving Constraint Optimization Problems via Bidirectional Coevolution

Beidan Liu · Zhengqiu Zhu · Chen Gao · Tianle Pu · Yong Zhao · Wei Qi · Quanjun Yin

摘要

Large Language Model (LLM)-based optimization has recently shown promise for autonomous problem solving, yet most approaches still cast LLMs as passive constraint checkers rather than proactive strategy designers, limiting their effectiveness on complex Constraint Optimization Problems (COPs). To...

可解释性推理评测与基准OpenReview 项目页
作者位次 #4/10ACL 2026Poster· Natural Language Processing

C ity C ube: Benchmarking Cross-view Spatial Reasoning on Vision-Language Models in Urban Environments

Haotian Xu · Yue Hu · Zhengqiu Zhu · Chen Gao · Ziyou Wang · Junreng Rao · Wenhao Lu · Weishi Li · Quanjun Yin · Yong Li

摘要

Cross-view spatial reasoning is essential for embodied AI, underpinning spatial understanding, mental simulation and planning in complex environments. Existing benchmarks primarily emphasize indoor or street settings, overlooking the unique challenges of open-ended urban spaces characterized by r...

推理多模态评测与基准OpenReview 项目页

常见合作者