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News/Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression
arxiv
PublishedJune 15, 2026 at 4:00 AM
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Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression

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arXiv:2602.08324v5 Announce Type: replace Abstract: Chain-of-Thought (CoT) reasoning successfully enhances the reasoning capabilities of Large Language Models (LLMs), yet it incurs substantial computational overhead for inference. Existing CoT compression methods often suffer from a critical loss of

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