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cs.AI2026
Seek Before You Move: Evidence Seeking for Progress Grounding in Vision-Language Navigation
Zhimin Wang, Meiyuan Zhu, Duo Wu +8
Vision-Language Navigation (VLN) requires agents to continuously ground task progress from long-horizon instructions and partial egocentric observations. Existing VLM-based navigat…
cs.AI2026
Learning with Challenges: Adaptive Difficulty-Aware Data Generation for Mobile GUI Agent Training
Linjia Kang, Zhimin Wang, Yongkang Zhang +5
Large-scale, high-quality interaction trajectories are essential for advancing mobile Graphical User Interface (GUI) agents. While existing methods typically rely on labor-intensiv…
cs.AI2025
Collaborative Belief Reasoning with LLMs for Efficient Multi-Agent Collaboration
Zhimin Wang, Duo Wu, Shaokang He +6
Effective real-world multi-agent collaboration requires not only accurate planning but also the ability to reason about collaborators' intents--a crucial capability for avoiding mi…