2 Papers at Neurips'23.
Both our submitted papers were accepted to Neurips this year! Come join us in New Orleans! Congrats to Alvin and Shuyue. Find out more about the papers below...
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The Best of Both Worlds in Network Population Games: Reaching Consensus and Convergence to Equilibrium
We study a model of multi-population learning with heterogenous beliefs.
3 Papers at IROS'23.
CLeAR had three papers accepted to IROS this year! Come join us in Detroit! Congrats to Tasbolat, Bowen, and Kaiqi. Find out more about the papers below: ...
Latent Emission-Augmented Perspective-Taking (LEAPT) for Human-Robot Interaction
We construct a decomposed latent state space model for perspective-taking for human robot interaction.
Large Language Models as Zero-Shot Human Models for Human-Robot Interaction
We explore the potential of LLMs to act as zero-shot human models for HRI. We contribute an empirical study and case studies on a simulated table-clearing task and a new robot utensil-passing experiment.
Refining 6-DoF Grasps with Context-Specific Classifiers
We propose a sampling-based grasp synthesis framework, GraspFlow, to generate context-specific grasps. We test GraspFlow in a real-world table-top grasping task.
Introducing Dr. Sreejith Balakrishnan!
Congratulations Sreejith on successfully defending his thesis! Sreejith’s work was on value alignment in human-centric AI/robots. Check out his Neurips pap...