5 papers
Act-With-Think: Chunk Auto-Regressive Modeling for Generative Recommendation
Yifan Wang, Weinan Gan, Longtao Xiao +7
Generative recommendation (GR) typically encodes behavioral or semantic aspects of item information into discrete tokens, leveraging the standard autoregressive (AR) generation par…
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation
Jintao Tong, Ran Ma, Yixiong Zou +3
Cross-domain few-shot segmentation (CD-FSS) is proposed to pre-train the model on a source-domain dataset with sufficient samples, and then transfer the model to target-domain data…
Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning
Shuai Yi, Yixiong Zou, Yuhua Li +1
Vision Transformer (ViT) has achieved remarkable success due to its large-scale pretraining on general domains, but it still faces challenges when applying it to downstream distant…
Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
Jintao Tong, Yixiong Zou, Guangyao Chen +2
Cross-Domain Few-Shot Segmentation (CD-FSS) aims to transfer knowledge from a source-domain dataset to unseen target-domain datasets with limited annotations. Current methods typic…
The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
Yuhan Liu, Yixiong Zou, Yuhua Li +1
Cross-Domain Few-Shot Segmentation (CDFSS) is proposed to transfer the pixel-level segmentation capabilities learned from large-scale source-domain datasets to downstream target-do…