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Yong Li

AwardICLR 2026×6KDD 2026×6ACL 2026×3UbiComp 2026×2AAAI 2026CHI 2026CVPR 2026SIGIR 2026多模态检索与知识评测与基准推理智能体与工具
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0 一作 · 21 篇 · ICLR 2026 / KDD 2026 / ACL 2026 / UbiComp 2026 / AAAI 2026 / CHI 2026 / CVPR 2026 / SIGIR 2026

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2026 顶会论文

21
作者位次 #3/4UbiComp 2026Journal· Ubiquitous & Pervasive Computing

Act2Intention: A Benchmark For Developing Active Mobile Agents Through Inferring User Intention From GUI Actions

Xiaokai Yan · Jingtao Ding · Yong Li · Zhiwen Yu

智能体与工具评测与基准OpenReview
作者位次 #4/4ICLR 2026Poster· Reinforcement Learning / Deep RL

Reinforcement Learning Fine-Tuning Enhances Activation Intensity and Diversity in the Internal Circuitry of LLMs

Honglin Zhang · Qianyue Hao · Fengli Xu · Yong Li

强化学习与后训练可解释性OpenReview
作者位次 #4/4ICLR 2026Poster· Reinforcement Learning / Deep RL

RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning

Qianyue Hao · Sibo Li · Jian Yuan · Yong Li

强化学习与后训练推理效率与系统OpenReview
作者位次 #10/10ACL 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
作者位次 #4/4ACL 2026Poster· Natural Language Processing

Diffuse Thinking: Exploring Diffusion Language Models as Efficient Thought Proposers for Reasoning

Chenyang Shao · Sijian Ren · Fengli Xu · Yong Li

摘要

Large language models (LLMs) have demonstrated strong capabilities in complex reasoning tasks, yet their autoregressive generation paradigm makes it computationally expensive to explore diverse reasoning paths. In contrast, diffusion language models (DLMs) adopt a parallel, non-autoregressive gen...

推理效率与系统评测与基准OpenReview 项目页
作者位次 #8/8ACL 2026Findings· Findings of ACL

Identifying Collective Intelligence Factor in LLM Agent Groups for Generalizable Multi-Agent System Design

Zhilun Zhou · Zihan Liu · Jiahe Liu · Yihan Wang · Qingyu Shao · Fengli Xu · Depeng Jin · Yong Li

摘要

Large language model (LLM)-based multi-agent systems (MASs) have shown impressive performance in solving a wide range of complex problems. However, previous studies mainly focus on designing customized MAS for specific tasks, while a critical research problem remains unclear: Do LLM agent groups...

智能体与工具检索与知识评测与基准OpenReview 项目页
作者位次 #4/4KDD 2026Oral· Knowledge Discovery & Data Mining

RAPID: A Scalable and Controllable Physics-Informed Diffusion Framework for Real-Time Pedestrian Trajectory Generation

Zihan Yu · Huandong Wang · Jingtao Ding · Yong Li

检索与知识OpenReview
作者位次 #2/2CHI 2026Oral· Human-Computer Interaction

On the Open Access of SIGCHI

Zhilong Chen · Yong Li

社会与人本OpenReview

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