C-TRAIL combines LLM commonsense with a dual-trust mechanism and Dirichlet-weighted Monte Carlo Tree Search to improve trajectory planning accuracy and safety in autonomous driving.
Code as policies: Language model programs for embodied control
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AnyUser translates free-form sketches on images plus optional language into executable robot actions for domestic tasks using multimodal fusion and a hierarchical policy.
A dual-LLM hierarchical framework for robotic task and motion planning, integrating object detection, achieves 86% success across 24 test scenarios ranging from simple spatial commands to infeasible requests.
citing papers explorer
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C-TRAIL: A Commonsense World Framework for Trajectory Planning in Autonomous Driving
C-TRAIL combines LLM commonsense with a dual-trust mechanism and Dirichlet-weighted Monte Carlo Tree Search to improve trajectory planning accuracy and safety in autonomous driving.
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AnyUser: Translating Sketched User Intent into Domestic Robots
AnyUser translates free-form sketches on images plus optional language into executable robot actions for domestic tasks using multimodal fusion and a hierarchical policy.
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Hierarchical Prompting with Dual LLM Modules for Robotic Task and Motion Planning
A dual-LLM hierarchical framework for robotic task and motion planning, integrating object detection, achieves 86% success across 24 test scenarios ranging from simple spatial commands to infeasible requests.