KODA: Contrastive Representation Comparison and Alignment for Vision-Language Foundation Models

In three linesKODA is a kernel-based framework for comparing and aligning vision-language model representations (CLIP, SigLIP). The method identifies sample subsets weakly clustered under one representation but strongly clustered under another through constrained optimization and low-rank approximations. Code released.

Summary generated by Claude — human-verified