activity
20152026
most citedFebruus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems

250 citations · 532 across the 72 of their papers we have counts for

collaborators

76 papers

cs.LG2026

SAFEGuard: Detect Optimization-Based Jailbreak Attacks Through Harmful Semantic Analysis and Fluency Measurement

Quoc Viet Vo, Trung Le, Damith C. Ranasinghe +1

Despite the significant efforts devoted to aligning large language models (LLMs) with human values and ensuring safe deployment, recent work has revealed that LLMs remain vulnerabl…

cs.SI2026

Link prediction on multi-relational graphs from an influence propagation perspective

Zidu Yin, Yuankai Qi, Dong Gong +3

Predicting the existence and type of links (edges) between nodes in a multi-relational graph is key for applications from social interaction prediction to knowledge relationship id…

cs.CV2026

Multi-Hypothesis Test-Time Adaptation to Mitigate Underspecification

Afshar Shamsi, Xiao-Yu Guo, Hamid Alinejad-Rokny +3

Test-Time Adaptation (TTA) seeks to improve model robustness under distribution shifts by adapting parameters using unlabeled target data. However, in the absence of supervision, e…

cs.LG2026

Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction

Wenkang Jiang, Yuhang Liu, Erdun Gao +3

Single-cell perturbation prediction aims to infer how cells respond to unseen interventions and to achieve out-of-distribution (OOD) generalization, providing a computational route…

cs.LG2026

What Makes a Representation Good for Single-Cell Perturbation Prediction?

Wenkang Jiang, Yuhang Liu, Yichao Cai +5

Single-cell perturbation modeling is fundamental for understanding and predicting cellular responses to genetic perturbations. However, existing approaches, from causal representat…

cs.CV2026

Dual Strategies for Test-Time Adaptation

Nam Nguyen Phuong, Duc Nguyen The Minh, Phi Le Nguyen +2

Conventional test-time adaptation (TTA) approaches typically adapt the model using only a small fraction of test samples, often those with low-entropy predictions, thereby failing…