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Discover the best community collections!

Collections including paper arXiv:2510.13515

about 9 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 28
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

microsoft/bitnet-b1.58-2B-4T

Text Generation • 0.8B • Updated May 1 • 10.4k • 1.22k
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models

Paper • 2504.10449 • Published Apr 14 • 15
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct

Text Generation • 8B • Updated Apr 17 • 104 • 15
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Paper • 2504.11536 • Published Apr 15 • 63

UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning

Paper • 2510.13515 • Published 28 days ago • 11
TianchengGu/UniME-V2-LLaVA-OneVision-8B

Image-Text-to-Text • 8B • Updated 28 days ago • 20 • 2
TianchengGu/UniME-V2-Qwen2VL-7B

Image-Text-to-Text • 8B • Updated 28 days ago • 105 • 2
TianchengGu/UniME-V2-Qwen2VL-2B

Image-Text-to-Text • 2B • Updated 28 days ago • 205 • 2

UniME

Collection

UniME is a series of multimodal large language models trained for learning universal multimodal embedding. • 4 items • Updated May 16 • 4
GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Paper • 2412.16855 • Published Dec 22, 2024 • 5
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks

Paper • 2410.05160 • Published Oct 7, 2024 • 4
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 173 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

DLER: Doing Length pEnalty Right - Incentivizing More Intelligence per Token via Reinforcement Learning

Paper • 2510.15110 • Published 27 days ago • 15
PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model

Paper • 2510.14528 • Published 27 days ago • 89
Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs

Paper • 2510.13795 • Published 28 days ago • 56
UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning

Paper • 2510.13515 • Published 28 days ago • 11

The collections of UniME-V2's data and Model Weights

TianchengGu/UniME-V2-Qwen2VL-2B

Image-Text-to-Text • 2B • Updated 28 days ago • 205 • 2
TianchengGu/UniME-V2-Qwen2VL-7B

Image-Text-to-Text • 8B • Updated 28 days ago • 105 • 2
TianchengGu/UniME-V2-LLaVA-OneVision-8B

Image-Text-to-Text • 8B • Updated 28 days ago • 20 • 2
TianchengGu/UniME-V2-reranker-Qwen25VL-7B

Image-Text-to-Text • 8B • Updated 28 days ago • 33 • 2

CoRAG: Collaborative Retrieval-Augmented Generation

Paper • 2504.01883 • Published Apr 2 • 9
SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning

Paper • 2504.08600 • Published Apr 11 • 31
Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL

Paper • 2503.23157 • Published Mar 29 • 10
AI Agents: Evolution, Architecture, and Real-World Applications

Paper • 2503.12687 • Published Mar 16 • 2

about 9 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 28
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 173 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

microsoft/bitnet-b1.58-2B-4T

Text Generation • 0.8B • Updated May 1 • 10.4k • 1.22k
M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models

Paper • 2504.10449 • Published Apr 14 • 15
nvidia/Llama-3.1-Nemotron-8B-UltraLong-2M-Instruct

Text Generation • 8B • Updated Apr 17 • 104 • 15
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Paper • 2504.11536 • Published Apr 15 • 63

DLER: Doing Length pEnalty Right - Incentivizing More Intelligence per Token via Reinforcement Learning

Paper • 2510.15110 • Published 27 days ago • 15
PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model

Paper • 2510.14528 • Published 27 days ago • 89
Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs

Paper • 2510.13795 • Published 28 days ago • 56
UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning

Paper • 2510.13515 • Published 28 days ago • 11

UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning

Paper • 2510.13515 • Published 28 days ago • 11
TianchengGu/UniME-V2-LLaVA-OneVision-8B

Image-Text-to-Text • 8B • Updated 28 days ago • 20 • 2
TianchengGu/UniME-V2-Qwen2VL-7B

Image-Text-to-Text • 8B • Updated 28 days ago • 105 • 2
TianchengGu/UniME-V2-Qwen2VL-2B

Image-Text-to-Text • 2B • Updated 28 days ago • 205 • 2

The collections of UniME-V2's data and Model Weights

TianchengGu/UniME-V2-Qwen2VL-2B

Image-Text-to-Text • 2B • Updated 28 days ago • 205 • 2
TianchengGu/UniME-V2-Qwen2VL-7B

Image-Text-to-Text • 8B • Updated 28 days ago • 105 • 2
TianchengGu/UniME-V2-LLaVA-OneVision-8B

Image-Text-to-Text • 8B • Updated 28 days ago • 20 • 2
TianchengGu/UniME-V2-reranker-Qwen25VL-7B

Image-Text-to-Text • 8B • Updated 28 days ago • 33 • 2

UniME

Collection

UniME is a series of multimodal large language models trained for learning universal multimodal embedding. • 4 items • Updated May 16 • 4
GME: Improving Universal Multimodal Retrieval by Multimodal LLMs

Paper • 2412.16855 • Published Dec 22, 2024 • 5
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks

Paper • 2410.05160 • Published Oct 7, 2024 • 4
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16

CoRAG: Collaborative Retrieval-Augmented Generation

Paper • 2504.01883 • Published Apr 2 • 9
SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning

Paper • 2504.08600 • Published Apr 11 • 31
Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQL

Paper • 2503.23157 • Published Mar 29 • 10
AI Agents: Evolution, Architecture, and Real-World Applications

Paper • 2503.12687 • Published Mar 16 • 2

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