collaborators

6 papers

cs.CV2026

First Things First: Teaching LLM-Based Agents to Prioritize Must-Haves before Nice-to-Haves

Tianjie Ju, Xinyue Xu, Wanxuan Sun +4

Recent progress in multimodal large language models (MLLMs) has fueled significant enthusiasm in their potential to act as autonomous agents for real-world tasks. However, scenario…

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.CL2026

MineExplorer: Evaluating Open-World Exploration of MLLM Agents in Minecraft

Tianjie Ju, Yueqing Sun, Zheng Wu +7

Multimodal large language models (MLLMs) have shown strong capabilities in perception, reasoning, and action generation. However, their ability to sustain exploration in dynamic op…

cs.CL2025

Do Latent Tokens Think? A Causal and Adversarial Analysis of Chain-of-Continuous-Thought

Yuyi Zhang, Boyu Tang, Tianjie Ju +2

Latent tokens are gaining attention for enhancing reasoning in large language models (LLMs), yet their internal mechanisms remain unclear. This paper examines the problem from a re…

cs.AI2025

Training High-Level Schedulers with Execution-Feedback Reinforcement Learning for Long-Horizon GUI Automation

Zehao Deng, Tianjie Ju, Zheng Wu +2

The rapid development of large vision-language model (VLM) has greatly promoted the research of GUI agent. However, GUI agents still face significant challenges in handling long-ho…

cs.AI2025

Reasoning or Rambling? Exploring the Effect of Thinking on Agent Persuasion

Haodong Zhao, Jidong Li, Zhaomin Wu +4

Understanding persuasion is critical for the safety and reliability of multi-agent systems built on large language models (LLMs). This paper studies persuasion dynamics by contrast…