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Latent Chain-of-Thought Reasoning Fails Without Dual Supervision

Researchers identify why models struggle to learn from latent reasoning: outcome supervision alone causes gradient attenuation and representational drift. A new information-theoretic framework shows trajectory and space

1 min read

Latent Chain-of-Thought (CoT) reasoning internalizes problem-solving within continuous hidden states rather than generating verbose step-by-step traces. Researchers at EIT-NLP published an analysis showing that this approach fails systematically because outcome supervision provides insufficient lear...

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Method & sources
Source type
Primary publication (lab/vendor blog) — our analysis + implication
Source link
r/arxiv-compression
Published
UTC
Byline
By the gotcontext.ai team (editorial standards)
Correction?
corrections@gotcontext.ai

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