Author

Han-Ding Wang

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#natural language process... Preprint May 2025

Decoding One Safety Trigger Token for Balancing Safety and Usability in Large Language Models

D-STT, a simple yet effective defense algorithm that identifies and explicitly decodes safety trigger tokens of the given safety-aligned LLM to activate the model's learned safety patterns, effectively preserves model usability by introducing minimum intervention in the decoding process.

Hao-Ran Gu, Han-Ding Wang, Yi Mei et al. · 0 citations

Preprint Aug 2026

CRIP: Channel Level Representation Injection for Personalized One-Shot Federated Learning

CRIP, a personalized OSFL framework that operates in the representation space via channel-level feature alignment, consistently outperforms local models and state-of-the-art baselines, validating the effectiveness of representation-space personalization under extreme domain heterogeneity.

Zijian Jiang, Chaoli Sun, Han-Ding Wang et al. · 0 citations