Minghui Zheng
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126
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ML×1NLP×1
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2026
HMPO: Hybrid Median-length Policy Optimization for Chain-of-Thought Compression
HMPO introduces a single-stage, cost-effective reinforcement learning framework that achieves significant token compression of Chain-of-Thought reasoning with minimal loss of accuracy, applicable across various large language model architectures.
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Papers
cs.LGcs.CLRecentJun 1, 2026
HMPO: Hybrid Median-length Policy Optimization for Chain-of-Thought Compression
Minghui Zheng, Hongxu Chen, Huimin Ren, Hongsheng Xin +7 more
HMPO introduces a single-stage, cost-effective reinforcement learning framework that achieves significant token compression of Chain-of-Thought reasoning with minimal loss of accuracy, applicable acro…
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