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Matthew Marquez

2 accepted papers

2023

On the Planning Abilities of Large Language Models - A Critical Investigation

NeurIPS 2023spotlight

Intrigued by the claims of emergent reasoning capabilities in LLMs trained on general web corpora, in this paper, we set out to investigate their planning capabilities. We aim to evaluate (1) the effectiveness of LLMs in generating plans autonomously in commonsense planning tasks and (2) the potenti…

Cited by 280SourcePDFScholar
2023

PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change

NeurIPS 2023poster

Generating plans of action, and reasoning about change have long been considered a core competence of intelligent agents. It is thus no surprise that evaluating the planning and reasoning capabilities of large language models (LLMs) has become a hot topic of research. Most claims about LLM planning…