activity
20222024
most citedmPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video

50 citations · 73 across the 12 of their papers we have counts for

collaborators

12 papers

cs.LG2024

Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning

Jiawei Yao, Qi Qian, Juhua Hu

Multiple clustering aims to discover various latent structures of data from different aspects. Deep multiple clustering methods have achieved remarkable performance by exploiting c…

cs.CV2024

SeA: Semantic Adversarial Augmentation for Last Layer Features from Unsupervised Representation Learning

Qi Qian, Yuanhong Xu, Juhua Hu

Deep features extracted from certain layers of a pre-trained deep model show superior performance over the conventional hand-crafted features. Compared with fine-tuning or linear p…

cs.CV2024

Online Zero-Shot Classification with CLIP

Qi Qian, Juhua Hu

Vision-language pre-training such as CLIP enables zero-shot transfer that can classify images according to the candidate class names. While CLIP demonstrates an impressive zero-sho…

cs.CL20246 cited

Searching for Best Practices in Retrieval-Augmented Generation

Xiaohua Wang, Zhenghua Wang, Xuan Gao +11

Retrieval-augmented generation (RAG) techniques have proven to be effective in integrating up-to-date information, mitigating hallucinations, and enhancing response quality, partic…

cs.CV2024

Multi-Modal Proxy Learning Towards Personalized Visual Multiple Clustering

Jiawei Yao, Qi Qian, Juhua Hu

Multiple clustering has gained significant attention in recent years due to its potential to reveal multiple hidden structures of data from different perspectives. The advent of de…

cs.CV20233 cited

Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP

Qi Qian, Yuanhong Xu, Juhua Hu

Vision-language pre-training methods, e.g., CLIP, demonstrate an impressive zero-shot performance on visual categorizations with the class proxy from the text embedding of the clas…