4 papers · 1 filter
Perception or Reasoning? Diagnosing and Tackling Reinforcement Learning Bottlenecks in VLMs
Zeyuan Yang, Zhuohao Chen, Jiaben Chen +3
Reinforcement learning has brought strong gains to language model reasoning, but its improvements on visual tasks remain less consistent. One difficulty is that visual task failure…
SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators
Yuncong Yang, Zhengtao Han, Furkan Ozyurt +6
World models are increasingly used as policy-in-the-loop imagination environments, where reliable rollouts require fine-grained controllability with respect to low-level robot acti…
Reasoning Knowledge-Gap in Drone Planning via LLM-based Active Elicitation
Zeyu Fang, Beomyeol Yu, Cheng Liu +5
Human-AI joint planning in Unmanned Aerial Vehicles (UAVs) typically relies on control handover when facing environmental uncertainties, which is often inefficient and cognitively…
Knowing When to Ask: Resolving Uncertainty in Human-Robot Joint Planning via Explicit Dialogue and Implicit Intent Cues
Zeyu Fang, Yuxin Lin, Cheng Liu +6
Effective human-robot collaboration in open-world environments requires joint planning under uncertainty about the task, the environment, and the human teammate. Communication is t…