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Hai-Yang Xiang

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#artificial intelligence Preprint Aug 2026

SABER: Stability-Aware Early Exit for LLM Reasoning via Adversarial Branch Probing

This work proposes SABER, a training-free framework for stability-aware early exit via adversarial branch probing, and shows that SABER reduces reasoning token consumption by 30.2% on average while maintaining competitive accuracy with full-length reasoning.

Wanzhe Cheng, Hai-Yang Xiang, Jun-Tao Li et al. · 0 citations