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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
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 • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
Collections
Discover the best community collections!
Collections including paper arxiv:2503.13891
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PUMA: Empowering Unified MLLM with Multi-granular Visual Generation
Paper • 2410.13861 • Published • 57 -
JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation
Paper • 2411.07975 • Published • 31 -
Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
Paper • 2411.10442 • Published • 87 -
Multimodal Autoregressive Pre-training of Large Vision Encoders
Paper • 2411.14402 • Published • 47
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Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Paper • 2403.09029 • Published • 56 -
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 26 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 73 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 79
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Forget What You Know about LLMs Evaluations - LLMs are Like a Chameleon
Paper • 2502.07445 • Published • 11 -
ARR: Question Answering with Large Language Models via Analyzing, Retrieving, and Reasoning
Paper • 2502.04689 • Published • 7 -
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
Paper • 2502.03032 • Published • 61 -
Preference Leakage: A Contamination Problem in LLM-as-a-judge
Paper • 2502.01534 • Published • 42
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 29 -
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 • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
-
Forget What You Know about LLMs Evaluations - LLMs are Like a Chameleon
Paper • 2502.07445 • Published • 11 -
ARR: Question Answering with Large Language Models via Analyzing, Retrieving, and Reasoning
Paper • 2502.04689 • Published • 7 -
Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
Paper • 2502.03032 • Published • 61 -
Preference Leakage: A Contamination Problem in LLM-as-a-judge
Paper • 2502.01534 • Published • 42
-
PUMA: Empowering Unified MLLM with Multi-granular Visual Generation
Paper • 2410.13861 • Published • 57 -
JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation
Paper • 2411.07975 • Published • 31 -
Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
Paper • 2411.10442 • Published • 87 -
Multimodal Autoregressive Pre-training of Large Vision Encoders
Paper • 2411.14402 • Published • 47
-
Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Paper • 2403.09029 • Published • 56 -
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 26 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 73 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 79