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CellTrack-Bench introduces a microscopic cell tracking benchmark evaluating 22 vision-language models against specialized trackers across 15 datasets and 4 imaging modalities, revealing significant reasoning gaps in frontier models.
Lior announces the MMBU Challenge, a collaboration with Stanford to test whether vision-language models can truly recognize and localize biomedical images rather than guessing answers, featuring 3 tracks, $100K+ in prizes, running Oct 1 to Dec 31 with registration closing today.
This paper introduces an unsupervised framework for modeling acquisition-related variability in structural connectomes using hybrid latent space modeling, eliminating the need for manual capacity tuning by architecturally annealing encoder outputs.