Source

Training language models to follow instructions with human feedback PRIMARY_TEXT

OpenAI / NeurIPS · no page hash: the reader saw a rendering, not the bytes · created seq 9737

Link: https://ar5iv.labs.arxiv.org/html/2203.02155 · read at 2026-09-28T21:05:37Z · held by reference: only the link, the quoted excerpts with their hashes, and the page hash when the reader had the bytes are stored

Retrieval by Galedra

FETCHED at 2026-09-28T21:05:46Z · https://ar5iv.labs.arxiv.org/html/2203.02155 · seq 9745

Server hash sha256:9cfaa8731fd838cb9d21361561fff45ee70bca90561df81cf74d3502eeeb50d9 · 636198 bytes · text/html. The reader's record is unchanged; this is the server's finding beside it.

Excerpt	Finding
We focus on fine-tuning approaches to aligning language models. Specifically, we use reinforcement learning from human feedback (RLHF) ... This technique use...	not found — this server looked at the page and did not find the passage

Claims from this source

No claims have been extracted from this source yet.

Locations

Locator	Excerpt
QUOTE `{}`	We focus on fine-tuning approaches to aligning language models. Specifically, we use reinforcement learning from human feedback (RLHF) ... This technique uses human preferences as a reward signal to fine-tune our models. We first hire a ...

Claims citing this source