Buffer of Thoughts: keep a library of reusable thought-templates, not past answers — retrieve, instantiate, distil back
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Ask a language model a fresh word problem and plain chain-of-thought works it out from zero every single time, re-deriving the same method and re-making the same slips. Few-shot does a little better — it pastes a couple of look-alike question→answer pairs — but it transfers surface form, not method, so a problem that reads differently yet needs the same reasoning slips right past the match. Buffer of Thoughts (Yang et al., 2024) keeps a meta-buffer of reusable thought-templates distilled from…
1Key Takeaways
- Ask a language model a fresh word problem and plain chain-of-thought works it out from zero every single time, re-deriving the same method and re-making the same slips.
- Few-shot does a little better — it pastes a couple of look-alike question→answer pairs — but it transfers surface form, not method, so a problem that reads differently yet needs the same reasoning slips right past the match.
- Buffer of Thoughts (Yang et al., 2024) keeps a meta-buffer of reusable thought-templates distilled from….
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3Why it matters
Prompt and agent patterns spread fast; staying current saves time and token cost. DEV — Prompt Engineering reports that ask a language model a fresh word problem and plain chain-of-thought works it out from zero every single time, re-deriving the same method and re-making the same slips.
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