Improve Vision Language Model Chain-of-thought Reasoning Paper • 2410.16198 • Published Oct 21, 2024 • 26
NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples Paper • 2410.14669 • Published Oct 18, 2024 • 37
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models Paper • 2410.02740 • Published Oct 3, 2024 • 52
MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning Paper • 2409.20566 • Published Sep 30, 2024 • 56
How Well Do LLMs Represent Values Across Cultures? Empirical Analysis of LLM Responses Based on Hofstede Cultural Dimensions Paper • 2406.14805 • Published Jun 21, 2024 • 3
Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models Paper • 2404.07973 • Published Apr 11, 2024 • 32
Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs Paper • 2404.05719 • Published Apr 8, 2024 • 82
GLIPv2: Unifying Localization and Vision-Language Understanding Paper • 2206.05836 • Published Jun 12, 2022 • 1
Ferret: Refer and Ground Anything Anywhere at Any Granularity Paper • 2310.07704 • Published Oct 11, 2023 • 11
From Scarcity to Efficiency: Improving CLIP Training via Visual-enriched Captions Paper • 2310.07699 • Published Oct 11, 2023 • 2
How Easy is It to Fool Your Multimodal LLMs? An Empirical Analysis on Deceptive Prompts Paper • 2402.13220 • Published Feb 20, 2024 • 15
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training Paper • 2403.09611 • Published Mar 14, 2024 • 126
In-Context Pretraining: Language Modeling Beyond Document Boundaries Paper • 2310.10638 • Published Oct 16, 2023 • 30
Idea2Img: Iterative Self-Refinement with GPT-4V(ision) for Automatic Image Design and Generation Paper • 2310.08541 • Published Oct 12, 2023 • 18
MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities Paper • 2308.02490 • Published Aug 4, 2023 • 17