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Found 3 papers, 1 papers with code
World Modeling Makes a Better Planner: Dual Preference Optimization for Embodied Task Planning
Recent advances in large vision-language models (LVLMs) have shown promise for embodied task planning, yet they struggle with fundamental challenges like dependency constraints and efficiency.
VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks
General-purposed embodied agents are designed to understand the users' natural instructions or intentions and act precisely to complete universal tasks.
Large Trajectory Models are Scalable Motion Predictors and Planners
STR reformulates the motion prediction and motion planning problems by arranging observations, states, and actions into one unified sequence modeling task.
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