From Pixels to Prompts: Vision-Language Models

Vision Language Models (Better, faster, stronger)

Vision Language Models Explained

Fine-tuning Florence-2 - Microsoft's Cutting-edge Vision Language Models

A Dive into Vision-Language Models

Pix2Fact: When Vision Is Not Enough -- Benchmarking Fine-Grained VQA with Web Verification on High-Resolution Real-World Scenes

arXiv:2602. 00593v4 Announce Type: replace-cross Abstract: Despite progress on general tasks, vision-language models (VLMs) still struggle with challenges that demand both fine-grained visual grounding and external knowledge, a synergy overlooked by existing benchmarks that evaluate these abilities in isolation.

Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge

arXiv:2606. 27527v1 Announce Type: cross Abstract: Large Language Models (LLMs) possess broad conceptual knowledge acquired through large-scale text pretraining, yet their potential to supervise models in other modalities remains underexplored.

The Last Visible Pixel: Probing Fine-Scale Perception in Vision-Language Models

arXiv:2606. 07861v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) excel at multimodal understanding and reasoning, yet their fine-grained visual perception remains underexplored.

The Geometry of Representational Failures in Vision Language Models

arXiv:2602. 07025v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) exhibit puzzling failures in multi-object visual tasks, such as hallucinating non-existent elements or failing to identify the most similar objects among distractions.

Situation Perception: A Necessary Primitive to Artificial Superintelligence

arXiv:2606. 30481v1 Announce Type: cross Abstract: Current large language models are extraordinary statistical engines.

Accelerating Vision-Language Models: BridgeTower on Habana Gaudi2

Blind-Spots-Bench: Evaluating Blind Spots in Multimodal Models

arXiv:2607. 08317v1 Announce Type: new Abstract: Modern AI models achieve strong performance on many established benchmarks, yet they still fail on tasks that humans find almost trivial, such as manipulating a string or drawing a dog with five legs.

SmolVLM - small yet mighty Vision Language Model