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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 26 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 43 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22
Collections
Discover the best community collections!
Collections including paper arxiv:2502.12084
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Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages
Paper • 2410.16153 • Published • 44 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 59 -
The Curse of Multi-Modalities: Evaluating Hallucinations of Large Multimodal Models across Language, Visual, and Audio
Paper • 2410.12787 • Published • 31 -
LEOPARD : A Vision Language Model For Text-Rich Multi-Image Tasks
Paper • 2410.01744 • Published • 26
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 58 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 52 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 42 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 57
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Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Paper • 2407.07053 • Published • 45 -
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
Paper • 2407.12772 • Published • 34 -
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models
Paper • 2407.11691 • Published • 14 -
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
Paper • 2408.02718 • Published • 61
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Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Paper • 2403.09029 • Published • 55 -
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 25 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 69 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 77