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cs.LG2026
USAD: Uncertainty-aware Statistical Adversarial Detection
Zhijian Zhou, Xunye Tian, Jiacheng Zhang +5
Statistical adversarial detection (SAD) treats detection as a two-sample test. Given a reference set of clean examples (CEs) and a batch of queries, potentially containing an unkno…
cs.LG2025
MoRA: On-the-fly Molecule-aware Low-Rank Adaptation Framework for LLM-based Multi-Modal Molecular Assistant
Tao Yin, Xiaohong Zhang, Jiacheng Zhang +5
Effectively integrating molecular graph structures with Large Language Models (LLMs) is a key challenge in drug discovery. Most existing multi-modal alignment methods typically pro…
cs.LG2025
One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy
Jiacheng Zhang, Benjamin I. P. Rubinstein, Jingfeng Zhang +1
Statistical adversarial data detection (SADD) detects whether an upcoming batch contains adversarial examples (AEs) by measuring the distributional discrepancies between clean exam…