16 citations · 23 across the 11 of their papers we have counts for
10 papers · 1 filter
MoASE++: Mixture of Activation Sparsity Experts with Domain-Adaptive On-policy Distillation for Continual Test Time Adaptation
Ronyu Zhang, Aosong Cheng, Gaole Dai +8
Continual test-time adaptation adapts a source-pretrained model to non-stationary, unlabeled target streams while retaining past competence, yet texture-biased backbones risk error…
Look Before Acting: Enhancing Vision Foundation Representations for Vision-Language-Action Models
Yulin Luo, Hao Chen, Zhuangzhe Wu +10
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for robotic manipulation, in which reliable action prediction critically depends on accurately int…
MC-LLaVA: Multi-Concept Personalized Vision-Language Model
Ruichuan An, Sihan Yang, Ming Lu +9
Current vision-language models (VLMs) show exceptional abilities across diverse tasks, such as visual question answering. To enhance user experience, recent studies investigate VLM…
SCBench: A Sports Commentary Benchmark for Video LLMs
Kuangzhi Ge, Lingjun Chen, Kevin Zhang +6
Recently, significant advances have been made in Video Large Language Models (Video LLMs) in both academia and industry. However, methods to evaluate and benchmark the performance…
MC-LLaVA: Multi-Concept Personalized Vision-Language Model
Ruichuan An, Sihan Yang, Renrui Zhang +10
Current vision-language models (VLMs) show exceptional abilities across diverse tasks, such as visual question answering. To enhance user experience, recent studies have investigat…
Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation
Xiaohong Liu, Guoxing Yang, Yulin Luo +8
Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in medicine have shown potential in p…