44 citations · 53 across the 11 of their papers we have counts for
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cs.AI2024
Language Models can Infer Action Semantics for Symbolic Planners from Environment Feedback
Wang Zhu, Ishika Singh, Robin Jia +1
Symbolic planners can discover a sequence of actions from initial to goal states given expert-defined, domain-specific logical action semantics. Large Language Models (LLMs) can di…
cs.AI2024★ 1 cited
TwoStep: Multi-agent Task Planning using Classical Planners and Large Language Models
David Bai, Ishika Singh, David Traum +1
Classical planning formulations like the Planning Domain Definition Language (PDDL) admit action sequences guaranteed to achieve a goal state given an initial state if any are poss…
cs.RO2024★ 1 cited
THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation
Wilbert Pumacay, Ishika Singh, Jiafei Duan +3
To realize effective large-scale, real-world robotic applications, we must evaluate how well our robot policies adapt to changes in environmental conditions. Unfortunately, a major…