Author

Shu-Jian Huang

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#artificial intelligence Preprint Sep 2026

Drift-Constrained Optimization: Only Direction Matters in Fine-Tuning Instruct Models

Fine-tuning instruct models often improves target performance while inducing behavioral drift from the reference model, which can degrade existing capabilities. Rather than treating this drift as an uncontrolled consequence of optimization, we specify a behavioral drift budget before optimization and ask how to boost t...

Fei Yuan, Changjiang Gao, Yi-Le Tu et al. · 0 citations

#natural language process... Preprint May 2026

Unlocking Fine-Grained Translation Quality Estimation in LRMs through Mutually Boosting Implicit and Explicit Reasoning

This paper proposes a simple two-stage training framework that enables the mutually boosting of implicit (layer-wise) and explicit (token-wise) reasoning capabilities, and provides evidence for the mutually boosting between implicit and explicit reasoning.

R. Dang, X. Wang, Zhejian Lai et al. · 0 citations