Show Your Work: Scratchpads for Intermediate Computation with Language Models · HackerPapers discussions

Show Your Work: Scratchpads for Intermediate Computation with Language Models — mentioned by Chance-Device

Sun, 05 Apr 2026 13:12:44 GMT

Let’s see, I think these pretty much map out a little chronology of the research: https://arxiv.org/abs/2112.00114 https://arxiv.org/abs/2406.06467 https://arxiv.org/abs/2404.15758 https://arxiv.org/abs/2512.12777 First that scratchpads matter, then why they matter, then that they don’t even need to be meaningful tokens, then a conceptual framework for the whole thing.

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Show Your Work: Scratchpads for Intermediate Computation with Language Models — mentioned by sync

Mon, 24 Nov 2025 20:38:57 GMT

Does anyone here understand "interleaved scratchpads" mentioned at the very bottom of the footnotes: > All evals were run with a 64K thinking budget, interleaved scratchpads, 200K context window, default effort (high), and default sampling settings (temperature, top_p). I understand scratchpads (e.g. [0] Show Your Work: Scratchpads for Intermediate Computation with Language Models) but not sure about the "interleaved" part, a quick Kagi search did not lead to anything relevant other than Claude itself :) [0] https://arxiv.org/abs/2112.00114

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Show Your Work: Scratchpads for Intermediate Computation with Language Models — mentioned by jncraton

Wed, 08 Mar 2023 03:58:24 GMT

This can certainly be done. Here's one example from 2021 demonstrating training an LLM to use a scratchpad ("talking to itself") to greatly improve accuracy on arithmetic problems: https://arxiv.org/pdf/2112.00114.pdf

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Show Your Work: Scratchpads for Intermediate Computation with Language Models — HN submission

Mon, 18 Jul 2022 11:50:52 GMT

Show Your Work: Scratchpads For Intermediate Computation With Language Models

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

Show Your Work: Scratchpads for Intermediate Computation with Language Models — mentioned by moyix

Fri, 11 Feb 2022 19:33:34 GMT

Yup, quite possible that this has something to do with it. There is other work showing that giving LMs a "scratchpad" for intermediate computations allows them to do much better not just at arithmetic but also things like predicting the output of some code: https://arxiv.org/abs/2112.00114

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Show Your Work: Scratchpads for Intermediate Computation with Language Models — mentioned by moyix

Tue, 08 Feb 2022 03:58:18 GMT

Sure, I think this would be a really interesting study to do! I have been meaning to scrape a big chunk of GitHub in order to do this kind of analysis. I think I would be surprised (just based on my own use of Codex and Copilot) if they were copying at the level of "same code but renamed variables" either. Past that I think comparisons get pretty difficult, and to some degree I would actually be more impressed if it understood enough about programs to be able to mimic higher-level structure without just memorizing text. Why do you think Python isn't good for comparing program structure?…

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