Agents & Tool Use · 2021

WebGPT: Browser-assisted Question-answering with Human Feedback

Reiichiro Nakano, Jacob Hilton, Suchir Balaji, John Schulman

Fine-tuned a language model to answer questions by browsing the web and citing sources, using human feedback to reward well-supported answers and reducing unsupported claims.

Editorial record

Plain-language summary

WebGPT gives GPT-3 a text-based browser and trains it with human comparisons to search, navigate, and quote evidence, then optimizes against a learned reward model. The result answers long-form questions with references that raters prefer, at the cost of sometimes over-trusting sources. It was an early demonstration of tool use and retrieval-augmented answering with RLHF.

Knowledge graph

Relationships

Antecedents

Descendants

Source record

Provenance

Record ID
P-520
Record created
2026-07-13
Last reviewed
2026-07-14
Record version
2

Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.