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cs.CV2026
ORCA: ORgan-Centroid Aggregation for Training-Free 3D CT Visual Token Compression
Renjie Liang, Zijian Xu, Jinqian Pan +6
A 3D CT scan entering a vision-language model produces a long sequence of visual tokens, often thousands to tens of thousands per volume, and this sequence must be compressed befor…
cs.CV2026
JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles
Shawn Li, Wei Yang, Jike Zhong +11
The paper introduces JigShape, a benchmark of interlocking jigsaw puzzles designed to test visual‑geometric reasoning in vision‑language models, and shows that current zero‑shot an…
cs.CV2026
BabyVLM-V2: Toward Developmentally Grounded Pretraining and Benchmarking of Vision Foundation Models
Shengao Wang, Wenqi Wang, Zecheng Wang +20
Early children's developmental trajectories set up a natural goal for sample-efficient pretraining of vision foundation models. We introduce BabyVLM-V2, a developmentally grounded…