ICML 2026 [OpenReview arXiv]
Guowei Guan, Yurong Hao, Jiaming Zhang, Tiantong Wu, Fuyao Zhang, Tianxiang Chen, Longtao Huang, Cyril Leung, Wei Yang Bryan Lim
TL;DR: We expose a new poisoning vulnerability in multimodal LLM recommender systems, showing that coordinated text–image perturbations can reliably promote target items while preserving normal recommendation utility.
ICML 2026 [PDF]
Gong Zhiren, Yikun Hou, Fan Wu, Che Wang, Fuyao Zhang, Tiantong Wu, Yurong Hao, Jiaming Zhang, Yiyang Duan, Tiantong Wang, Fei Huang, Chau Yuen, Wei Yang Bryan Lim
TL;DR: We propose an inference-time pruning framework that maps domain-aligned representation subspaces to sparse model pathways, enabling scenario-specific LLM subnetworks with improved efficiency.
CVPR 2026 (Oral) [CVPR]
Tianxiang Chen, Wenjie Hou, Feng Wang, Tiantong Wu, Zhiming Zheng, Shaoting Tang, Wei Yang Bryan Lim
TL;DR: We introduce FedAdamom, which adapts server momentum instead of the learning rate, to keep fast saddle-point escape while better selecting flat minima, improving both convergence and test accuracy.