diff History for Neural Language Agents

arXiv:2312.07540v2 Announce Type: replace-cross
Abstract: Neural Language Models (LMs) offer an exciting solution for general-purpose embodied control. However, a key technical issue arises when using an LM-based controller: environment observations must be converted to text, which coupled with history, results in long and verbose textual prompts. As a result, prior work in LM agents is limited to restricted domains with small observation size as well as minimal needs for interaction history or instruction tuning. In this paper, we introduce diff …

agents arxiv cs.ai cs.cl cs.lg diff history language type