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Navigation with Large Language Models: LLM Heuristics for Goal-Directed Exploration

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In this paper we study how the “semantic guesswork” produced by language models can be utilized as a guiding heuristic for planning algorithms.

This is paper is available on arxiv under CC 4.0 DEED license. Authors: Dhruv Shah, UC Berkeley and he contributed equally; Michael Equi, UC Berkeley and he contributed equally; Blazej Osinski, University of Warsaw; Fei Xia, Google DeepMind; Brian Ichter, Google DeepMind; Sergey Levine, UC Berkeley and Google DeepMind.

Authors: Authors: Dhruv Shah, UC Berkeley and he contributed equally; Michael Equi, UC Berkeley and he contributed equally; Blazej Osinski, University of Warsaw; Fei Xia, Google DeepMind; Brian Ichter, Google DeepMind; Sergey Levine, UC Berkeley and Google DeepMind. Table of Links Abstract & Introduction Related Work Problem Formulation and Overview LFG: Scoring Subgoals by Polling LLMs LLM Heuristics for Goal-Directed Exploration System Evaluation Discussion and References A.

 

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