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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 38 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
Collections
Discover the best community collections!
Collections including paper arxiv:2406.02539
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An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85 -
Visual Instruction Tuning
Paper • 2304.08485 • Published • 13 -
Improved Baselines with Visual Instruction Tuning
Paper • 2310.03744 • Published • 37 -
PALO: A Polyglot Large Multimodal Model for 5B People
Paper • 2402.14818 • Published • 23
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Instruction Pre-Training: Language Models are Supervised Multitask Learners
Paper • 2406.14491 • Published • 85 -
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Paper • 2405.21060 • Published • 63 -
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
Paper • 2405.20541 • Published • 20 -
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark
Paper • 2406.01574 • Published • 42
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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 12 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 53 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 30
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Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation
Paper • 2404.19752 • Published • 22 -
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Paper • 2404.16821 • Published • 53 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 75 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 124
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 80 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 143 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25