32 citations · 42 across the 3 of their papers we have counts for
3 papers
Robust Planning with Compound LLM Architectures: An LLM-Modulo Approach
Atharva Gundawar, Karthik Valmeekam, Mudit Verma +1
Previous work has attempted to boost Large Language Model (LLM) performance on planning and scheduling tasks through a variety of prompt engineering techniques. While these methods…
Can Large Language Models Really Improve by Self-critiquing Their Own Plans?
Karthik Valmeekam, Matthew Marquez, Subbarao Kambhampati
There have been widespread claims about Large Language Models (LLMs) being able to successfully verify or self-critique their candidate solutions in reasoning problems in an iterat…
On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)
Karthik Valmeekam, Sarath Sreedharan, Matthew Marquez +2
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 e…