March 14, 2024, 4:48 a.m. | Shikhar Murty, Christopher Manning, Peter Shaw, Mandar Joshi, Kenton Lee

cs.CL updates on

arXiv:2403.08140v1 Announce Type: new
Abstract: Following natural language instructions by executing actions in digital environments (e.g. web-browsers and REST APIs) is a challenging task for language model (LM) agents. Unfortunately, LM agents often fail to generalize to new environments without human demonstrations. This work presents BAGEL, a method for bootstrapping LM agents without human supervision. BAGEL converts a seed set of randomly explored trajectories or synthetic instructions, into demonstrations, via round-trips between two noisy LM components: an LM labeler which …

abstract agents apis arxiv bootstrapping browsers digital environments exploration human language language model natural natural language rest type web work

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