5 papers
Imaginative Perception Tokens Enhance Spatial Reasoning in Multimodal Language Models
Mahtab Bigverdi, Linjie Li, Weikai Huang +9
Vision language models (VLMs) excel at many tasks but still struggle with spatial reasoning when critical information is not directly observable. Many such problems require imagina…
Ablate-to-Validate: Are Vision-Language Models Really Using Continuous Thought Tokens?
Tianyi Zhang, Mahtab Bigverdi, Ranjay Krishna
Vision-language models (VLMs) are increasingly augmented with continuous or latent non-textual tokens intended to support "visual thinking." Despite improved task accuracy, this al…
MedBLINK: Probing Basic Perception in Multimodal Language Models for Medicine
Mahtab Bigverdi, Wisdom Ikezogwo, Kevin Zhang +5
Multimodal language models (MLMs) show promise for clinical decision support and diagnostic reasoning, raising the prospect of end-to-end automated medical image interpretation. Ho…
Unfolding Spatial Cognition: Evaluating Multimodal Models on Visual Simulations
Linjie Li, Mahtab Bigverdi, Jiawei Gu +5
Spatial cognition is essential for human intelligence, enabling problem-solving through visual simulations rather than solely relying on verbal reasoning. However, existing AI benc…
Perception Tokens Enhance Visual Reasoning in Multimodal Language Models
Mahtab Bigverdi, Zelun Luo, Cheng-Yu Hsieh +4
Multimodal language models (MLMs) still face challenges in fundamental visual perception tasks where specialized models excel. Tasks requiring reasoning about 3D structures benefit…