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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2509.11543
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Visual Representation Alignment for Multimodal Large Language Models
Paper • 2509.07979 • Published • 83 -
LatticeWorld: A Multimodal Large Language Model-Empowered Framework for Interactive Complex World Generation
Paper • 2509.05263 • Published • 10 -
Symbolic Graphics Programming with Large Language Models
Paper • 2509.05208 • Published • 46 -
OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling
Paper • 2509.12201 • Published • 104
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Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
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DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training
Paper • 2401.00849 • Published • 17 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Paper • 2311.00571 • Published • 43
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Gemini Robotics: Bringing AI into the Physical World
Paper • 2503.20020 • Published • 29 -
Magma: A Foundation Model for Multimodal AI Agents
Paper • 2502.13130 • Published • 58 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
Paper • 2410.23218 • Published • 49
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Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Paper • 2508.13167 • Published • 129 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 225 -
PRewrite: Prompt Rewriting with Reinforcement Learning
Paper • 2401.08189 • Published -
UI-S1: Advancing GUI Automation via Semi-online Reinforcement Learning
Paper • 2509.11543 • Published • 47
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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 • 14 -
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
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 23 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 85 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 151 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
-
Gemini Robotics: Bringing AI into the Physical World
Paper • 2503.20020 • Published • 29 -
Magma: A Foundation Model for Multimodal AI Agents
Paper • 2502.13130 • Published • 58 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
Paper • 2410.23218 • Published • 49
-
Visual Representation Alignment for Multimodal Large Language Models
Paper • 2509.07979 • Published • 83 -
LatticeWorld: A Multimodal Large Language Model-Empowered Framework for Interactive Complex World Generation
Paper • 2509.05263 • Published • 10 -
Symbolic Graphics Programming with Large Language Models
Paper • 2509.05208 • Published • 46 -
OmniWorld: A Multi-Domain and Multi-Modal Dataset for 4D World Modeling
Paper • 2509.12201 • Published • 104
-
Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL
Paper • 2508.13167 • Published • 129 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 225 -
PRewrite: Prompt Rewriting with Reinforcement Learning
Paper • 2401.08189 • Published -
UI-S1: Advancing GUI Automation via Semi-online Reinforcement Learning
Paper • 2509.11543 • Published • 47
-
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 54 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
-
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 • 14 -
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
-
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 189 -
COSMO: COntrastive Streamlined MultimOdal Model with Interleaved Pre-Training
Paper • 2401.00849 • Published • 17 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 51 -
LLaVA-Interactive: An All-in-One Demo for Image Chat, Segmentation, Generation and Editing
Paper • 2311.00571 • Published • 43