Learning to summarize from human feedback · HackerPapers discussions

Learning to summarize from human feedback — mentioned by godelski

Mon, 11 Aug 2025 01:11:29 GMT

Jack has a lot of really bad takes and frequently makes lots of mistakes. Honestly, I don't know why people take him seriously. I mean you can go read his blog post that's pinned where he argues that there's no new ideas and it is all data. He makes the argument that architecture doesn't matter, which is just so demonstrably false that it is laughable. He's a scale maximalist. I also expect an AI researcher from a top university to not make such wild mistakes > 3. RLHF: first proposed (to my knowledge) in the InstructGPT paper from OpenAI in 2022 I mean if you go read the instruct paper on…

Paper and discussion history. A mention is not an endorsement.

Learning to summarize from human feedback — mentioned by moyix

Thu, 20 Apr 2023 19:01:12 GMT

RLHF is from Google? The reference I know of is OpenAI: https://arxiv.org/pdf/2009.01325.pdf CLIP also seems novel?

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Learning to summarize from human feedback — mentioned by jefftk

Tue, 14 Mar 2023 12:51:01 GMT

Reinforcement learning in general didn't come out of AI alignment work, but RHLF in particular did. The initial idea and paper [1] were from AI alignment folks, as was most of the later development [2][3][4][5]. Overview: https://www.alignmentforum.org/posts/vwu4kegAEZTBtpT6p/thoug... [1] Deep Reinforcement Learning from Human Preferences https://arxiv.org/abs/1706.03741 [2] Fine-Tuning Language Models from Human Preferences https://arxiv.org/abs/1909.08593 [3] Learning to summarize from human feedback https://arxiv.org/abs/2009.01325 [4] Recursively Summarizing Books with Human Feedback…

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Learning to summarize from human feedback — HN submission

Sat, 04 Mar 2023 22:41:17 GMT

Learning to summarize from human feedback (2022)

56 points; 12 discussion replies on HN. Paper and source history. A submission is not an endorsement.

Learning to summarize from human feedback — mentioned by alibero

Wed, 04 Jan 2023 01:00:54 GMT

> Finally, RLHF, or "RL with Human Feedback". This is a fancy way of saying that the model now observes two humans in a conversation, one playing the role of a user, and another playing the role of "the AI", demonstrating how the AI should respond in different situations. This clearly helps the model learn how dialogs work, and how to keep track of information across dialog states (something that is very hard to learn from just "found" data). And the instructions to the humans are also the source of all the "It is not appropriate to..." and other formulaic / templatic responses we observe…

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Learning to summarize from human feedback — HN submission

Wed, 16 Sep 2020 13:10:32 GMT

Learning to Summarize from Human Feedback

2 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.