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OBC-Prune: Outcome-Based Calibration for Large Reasoning Model Pruning

This story is from 2026-09-17. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.17890v1 Announce Type: new Abstract: Large reasoning models (LRMs) generate long chain-of-thought traces before answering, creating significant inference overhead. Pruning can reduce this cost, but its effectiveness depends on the calibration data used to estimate parameter importance. R…

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  1. 2026-09-17 04:00 · arXiv cs.AI
    OBC-Prune: Outcome-Based Calibration for Large Reasoning Model Pruning

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