Vision-Language Models

RotBench: Evaluating Multimodal Large Language Models on Identifying Image Rotation
a benchmark evaluating MLLMs’ ability to identify image rotation
Tianyi Niu, Jaemin Cho, Elias Stengel-Eskin, Mohit Bansal
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RotBench: Evaluating Multimodal Large Language Models on Identifying Image Rotation
Bifrost-1: Bridging Multimodal LLMs and Diffusion Models with Patch-level CLIP Latents
a unified framework that bridges multimodal LLMs and diffusion models with patch-level CLIP latents
Han Lin, Jaemin Cho, Amir Zadeh, Chuan Li, Mohit Bansal
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Bifrost-1: Bridging Multimodal LLMs and Diffusion Models with Patch-level CLIP Latents
CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting
a VLM benchmark testing spatial reasoning by making the models count objects under occlusion
Atin Pothiraj, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal
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CAPTURe: Evaluating Spatial Reasoning in Vision Language Models via Occluded Object Counting