Through the Looking Glass: A Dual Perspective on Weakly-Supervised Few-Shot Segmentation
arXiv:2508.16159v2 Announce Type: replace-cross Abstract: Meta-learning aims to uniformly sample homogeneous support-query pairs, characterized by the same categories and similar attributes, and extract useful inductive biases through identical network architectures. However, this identical network design results in ov
The thing to notice is Through the Looking Glass; decide whether it changes your next build. For researchers and builders, this is an early signal to fold into evaluation, model choice, or agent design.