Multi-thinker CoT learning is hard passively under crypto assumptions but admits an efficient active algorithm with O(log 1/ε log log 1/ε) thinkers and O(1/ε poly log 1/ε) end-result data.
Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Learning to Think from Multiple Thinkers
Multi-thinker CoT learning is hard passively under crypto assumptions but admits an efficient active algorithm with O(log 1/ε log log 1/ε) thinkers and O(1/ε poly log 1/ε) end-result data.