4 papers
Beyond Attention Masks: Instruction Anchoring for Efficient In-Context Diffusion Generation
Yangshuai Liu, Zheming Li, Jiaao Li +4
In-context diffusion transformers concatenate instruction, target, and reference tokens into a single sequence for joint attention. Reference-side computation must therefore be rep…
Color as the Impetus: Transforming Few-Shot Learner
Chaofei Qi, Zhitai Liu, Jianbin Qiu
Humans possess innate meta-learning capabilities, partly attributable to their exceptional color perception. In this paper, we pioneer an innovative viewpoint on few-shot learning…
MetaLab: Few-Shot Game Changer for Image Recognition
Chaofei Qi, Zhitai Liu, Jianbin Qiu
Difficult few-shot image recognition has significant application prospects, yet remaining the substantial technical gaps with the conventional large-scale image recognition. In thi…
Shallow Deep Learning Can Still Excel in Fine-Grained Few-Shot Learning
Chaofei Qi, Chao Ye, Zhitai Liu +2
Deep learning has witnessed the extensive utilization across a wide spectrum of domains, including fine-grained few-shot learning (FGFSL) which heavily depends on deep backbones. N…