activity
20232026
most citedStructured Chemistry Reasoning with Large Language Models

8 citations · 19 across the 38 of their papers we have counts for

collaborators

41 papers

cs.AI2026

Do GUI Agents Know When Not to Act? Enabling Conflict-Aware Termination for Multimodal GUI Agents

Zhaoyuan Huang, Tianjie Ju, Pengzhou Cheng +7

Graphical user interface (GUI) agents are increasingly used to execute natural-language instructions on user interfaces, yet real users may issue infeasible instructions due to ben…

cs.CV2026

UrbanGround: From Local Perception to Spatial Agency in a Real-Scale City

Tianjie Ju, Zheng Wu, Yueqing Sun +15

Multimodal large language models (MLLMs) can interpret a street view, but urban agency depends on whether such local evidence remains useful after the agent starts to move. In this…

cs.CL2026

Beyond a Single Judge: The Evidence-Grounded, Social-Weighted Persona Panel for Generative UI Evaluation

Zheng Wu, Yibo Luo, Pu Zhang +2

Generative UI (GenUI) lets large language models synthesize a complete, renderable interface directly from a natural-language instruction, but evaluating the quality of what they g…

cs.CL2026

Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning

Zheng Wu, Chenhao Xue, Shijie Zheng +3

As large language models (LLMs) continue to advance in complex reasoning tasks, they have learned to heavily prioritize explicit conditions provided in the input. However, in every…

cs.CL2026

Mobile-Aptus: Confidence-Driven Proactive and Robust Interaction in MLLM-based Mobile-Using Agents

Zheng Wu, Pengzhou Cheng, Zongru Wu +5

Recent advancements in multimodal large language models (MLLMs) have shown exceptional potential in enabling mobile-using agents to autonomously execute human instructions. However…

cs.CL2026

GUI-CIDER: Mid-training GUI Agents via Causal Internalization and Density-aware Exemplar Reselection

Zheng Wu, Chengcheng Han, Zhengxi Lu +5

Despite the rapid progress of multimodal large language models in building Graphical User Interface (GUI) agents, their real-world task completion is fundamentally bottlenecked by…