1 citations · 2 across the 13 of their papers we have counts for
4 papers · 1 filter
Hypergraph-based Multimodal Retrieval-Augmented Generation with Incremental Refinement
Shenao Chen, Yidan Xu, Xiangmin Han +5
Modern Multimodal Retrieval-Augmented Generation (M-RAG) systems are fundamentally limited by the binary connectivity paradigm of traditional simple graphs, which fails to capture…
Cluster-Aware Neural Collapse Prompt Tuning for Long-Tailed Generalization of Vision-Language Models
Boyang Guo, Liang Li, Lin Peng +3
Prompt learning has emerged as an efficient alternative to fine-tuning pre-trained vision-language models (VLMs). Despite its promise, current methods still struggle to maintain ta…
HAM: A Training-Free Style Transfer Approach via Heterogeneous Attention Modulation for Diffusion Models
Yeqi He, Liang Li, Zhiwen Yang +3
Diffusion models have demonstrated remarkable performance in image generation, particularly within the domain of style transfer. Prevailing style transfer approaches typically leve…
Few-Shot Generative Model Adaption via Identity Injection and Preservation
Yeqi He, Liang Li, Jiehua Zhang +4
Training generative models with limited data presents severe challenges of mode collapse. A common approach is to adapt a large pretrained generative model upon a target domain wit…