OBC-Prune: Outcome-Based Calibration for Large Reasoning Model Pruning
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. Recent work calibrates on the…
- 01.Large reasoning models (LRMs) generate long chain-of-thought traces before answering, creating significant inference overhead
- 02.Pruning can reduce this cost, but its effectiveness depends on the calibration data used to estimate parameter importance
- 03.Recent work calibrates on the…
This material is provided as an extended analytical summary.
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