most citedSmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

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cs.AI2026

HARC: Coupling Harmfulness and Refusal Directions for Robust Safety Alignment

Shei Pern Chua, Hao Wu, Qianli Ma +1

Understanding how aligned LLMs internally represent safety is critical for diagnosing alignment vulnerabilities, as it explains why jailbreaks succeed and informs the design of rob…