42 citations · 47 across the 12 of their papers we have counts for
4 papers · 1 filter
Looping Back to Move Forward: Recursive Transformers for Efficient and Flexible Large Multimodal Models
Ruihan Xu, Yuting Gao, Lan Wang +5
Large Multimodal Models (LMMs) have achieved remarkable success in vision-language tasks, yet their vast parameter counts are often underutilized during both training and inference…
OrdMoE: Preference Alignment via Hierarchical Expert Group Ranking in Multimodal Mixture-of-Experts LLMs
Yuting Gao, Weihao Chen, Lan Wang +2
Preference learning has recently emerged as a pivotal strategy for post-training alignment of Multimodal Large Language Models (MLLMs). However, existing approaches predominantly r…
AnyExperts: On-Demand Expert Allocation for Multimodal Language Models with Mixture of Expert
Yuting Gao, Wang Lan, Hengyuan Zhao +3
Multimodal Mixture-of-Experts (MoE) models offer a promising path toward scalable and efficient large vision-language systems. However, existing approaches rely on rigid routing st…
Sinkhorn Distance Minimization for Knowledge Distillation
Xiao Cui, Yulei Qin, Yuting Gao +7
Knowledge distillation (KD) has been widely adopted to compress large language models (LLMs). Existing KD methods investigate various divergence measures including the Kullback-Lei…