1 citations · 1 across the 12 of their papers we have counts for
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Do All Vision Transformers Need Registers? A Cross-Architectural Reassessment
Spiros Baxevanakis, Platon Karageorgis, Ioannis Dravilas +1
Training Vision Transformers (ViTs) presents significant challenges, one of which is the emergence of artifacts in attention maps, hindering their interpretability. Darcet et al. (…
CapGeo-Bench: Decoupling Visual Perception from Reasoning and Evaluating Geometric Understanding
Yuying Li, Siyi Qian, Hao Liang +6
While Multimodal Large Language Models (MLLMs) have achieved remarkable success in difficult purely textual mathematical reasoning tasks, even advanced closed-source models such as…
Seeing Across Views: Benchmarking Spatial Reasoning of Vision-Language Models in Robotic Scenes
Zhiyuan Feng, Zhaolu Kang, Qijie Wang +16
Vision-language models (VLMs) are essential to Embodied AI, enabling robots to perceive, reason, and act in complex environments. They also serve as the foundation for the recent V…