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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 28 -
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:2504.07956
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MLLM-as-a-Judge for Image Safety without Human Labeling
Paper • 2501.00192 • Published • 30 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 107 -
Xmodel-2 Technical Report
Paper • 2412.19638 • Published • 27 -
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs
Paper • 2412.18925 • Published • 101
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Qwen2.5-Omni Technical Report
Paper • 2503.20215 • Published • 134 -
Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Paper • 2504.01990 • Published • 241 -
Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research
Paper • 2502.04644 • Published • 2 -
VCR-Bench: A Comprehensive Evaluation Framework for Video Chain-of-Thought Reasoning
Paper • 2504.07956 • Published • 42
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GATE OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation
Paper • 2411.18499 • Published • 18 -
VLSBench: Unveiling Visual Leakage in Multimodal Safety
Paper • 2411.19939 • Published • 10 -
AV-Odyssey Bench: Can Your Multimodal LLMs Really Understand Audio-Visual Information?
Paper • 2412.02611 • Published • 24 -
U-MATH: A University-Level Benchmark for Evaluating Mathematical Skills in LLMs
Paper • 2412.03205 • Published • 16
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What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
Paper • 2410.23743 • Published • 64 -
Large Language Models Orchestrating Structured Reasoning Achieve Kaggle Grandmaster Level
Paper • 2411.03562 • Published • 68 -
Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models
Paper • 2411.03884 • Published • 29 -
MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models
Paper • 2502.00698 • Published • 24
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Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Paper • 2407.07053 • Published • 47 -
LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
Paper • 2407.12772 • Published • 36 -
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 • 62
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 24 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 84 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 148 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25