1 citations · 1 across the 3 of their papers we have counts for
3 papers
Interactive and Expressive Code-Augmented Planning with Large Language Models
Anthony Z. Liu, Xinhe Wang, Jacob Sansom +5
Large Language Models (LLMs) demonstrate strong abilities in common-sense reasoning and interactive decision-making, but often struggle with complex, long-horizon planning tasks. R…
Code Models are Zero-shot Precondition Reasoners
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu +5
One of the fundamental skills required for an agent acting in an environment to complete tasks is the ability to understand what actions are plausible at any given point. This work…
A Picture is Worth a Thousand Words: Language Models Plan from Pixels
Anthony Z. Liu, Lajanugen Logeswaran, Sungryull Sohn +1
Planning is an important capability of artificial agents that perform long-horizon tasks in real-world environments. In this work, we explore the use of pre-trained language models…