5 papers
Boosting Large Language Models with Mask Fine-Tuning
Mingyuan Zhang, Yue Bai, Huan Wang +4
The large language model (LLM) is typically integrated into the mainstream optimization protocol. No work has questioned whether maintaining the model integrity is \textit{indispen…
Slicing Vision Transformer for Flexible Inference
Yitian Zhang, Huseyin Coskun, Xu Ma +6
Vision Transformers (ViT) is known for its scalability. In this work, we target to scale down a ViT to fit in an environment with dynamic-changing resource constraints. We observe…
Accessing Vision Foundation Models via ImageNet-1K
Yitian Zhang, Xu Ma, Yue Bai +2
Vision foundation models are renowned for the generalization ability due to massive training data. Nevertheless, they demand tremendous training resources, and the training data is…
Don't Judge by the Look: Towards Motion Coherent Video Representation
Yitian Zhang, Yue Bai, Huan Wang +2
Current training pipelines in object recognition neglect Hue Jittering when doing data augmentation as it not only brings appearance changes that are detrimental to classification,…
Latent Graph Inference with Limited Supervision
Jianglin Lu, Yi Xu, Huan Wang +2
Latent graph inference (LGI) aims to jointly learn the underlying graph structure and node representations from data features. However, existing LGI methods commonly suffer from th…