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Collections including paper arxiv:2507.04590

about 6 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

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

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
ComfyUI-Copilot: An Intelligent Assistant for Automated Workflow Development

Paper • 2506.05010 • Published Jun 5 • 79
SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training

Paper • 2506.05301 • Published Jun 5 • 56
LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning

Paper • 2505.16933 • Published May 22 • 34

Qwen2.5-Omni Technical Report

Paper • 2503.20215 • Published Mar 26 • 166
Unsupervised Post-Training for Multi-Modal LLM Reasoning via GRPO

Paper • 2505.22453 • Published May 28 • 46
UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning

Paper • 2505.23380 • Published May 29 • 22
More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models

Paper • 2505.21523 • Published May 23 • 13

The VLM2Vec embedding models.

TIGER-Lab/VLM2Vec-LoRA

Text Generation • Updated Jul 13 • 4 • 11
TIGER-Lab/VLM2Vec-Full

Text Generation • 4B • Updated Apr 7 • 45.9k • 28
TIGER-Lab/MMEB-train

Viewer • Updated Jan 28 • 2.14M • 3.77k • 16
TIGER-Lab/MMEB-eval

Viewer • Updated Oct 28, 2024 • 37k • 4.11k • 11

VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16
Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning

Paper • 2507.05255 • Published Jul 7 • 74

ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation

Paper • 2506.18095 • Published Jun 22 • 66
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16
Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation

Paper • 2509.00428 • Published Aug 30 • 17

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

Text Generation • 0.8B • Updated May 1 • 11k • 1.21k
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 • 282 • 15
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Paper • 2504.11536 • Published Apr 15 • 62

Image-Text Alignment

QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation

Paper • 2502.05178 • Published Feb 7 • 10
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation

Paper • 2502.14846 • Published Feb 20 • 14
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Paper • 2502.14786 • Published Feb 20 • 153
Efficient LLaMA-3.2-Vision by Trimming Cross-attended Visual Features

Paper • 2504.00557 • Published Apr 1 • 15

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24, 2024 • 29
MoDE: CLIP Data Experts via Clustering

Paper • 2404.16030 • Published Apr 24, 2024 • 15
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Paper • 2405.12130 • Published May 20, 2024 • 50
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21, 2024 • 33

about 6 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

VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16
Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning

Paper • 2507.05255 • Published Jul 7 • 74

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

ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation

Paper • 2506.18095 • Published Jun 22 • 66
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents

Paper • 2507.04590 • Published Jul 7 • 16
Mixture of Global and Local Experts with Diffusion Transformer for Controllable Face Generation

Paper • 2509.00428 • Published Aug 30 • 17

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
ComfyUI-Copilot: An Intelligent Assistant for Automated Workflow Development

Paper • 2506.05010 • Published Jun 5 • 79
SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training

Paper • 2506.05301 • Published Jun 5 • 56
LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning

Paper • 2505.16933 • Published May 22 • 34

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

Text Generation • 0.8B • Updated May 1 • 11k • 1.21k
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 • 282 • 15
ReTool: Reinforcement Learning for Strategic Tool Use in LLMs

Paper • 2504.11536 • Published Apr 15 • 62

Qwen2.5-Omni Technical Report

Paper • 2503.20215 • Published Mar 26 • 166
Unsupervised Post-Training for Multi-Modal LLM Reasoning via GRPO

Paper • 2505.22453 • Published May 28 • 46
UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning

Paper • 2505.23380 • Published May 29 • 22
More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models

Paper • 2505.21523 • Published May 23 • 13

Image-Text Alignment

QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation

Paper • 2502.05178 • Published Feb 7 • 10
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation

Paper • 2502.14846 • Published Feb 20 • 14
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Paper • 2502.14786 • Published Feb 20 • 153
Efficient LLaMA-3.2-Vision by Trimming Cross-attended Visual Features

Paper • 2504.00557 • Published Apr 1 • 15

The VLM2Vec embedding models.

TIGER-Lab/VLM2Vec-LoRA

Text Generation • Updated Jul 13 • 4 • 11
TIGER-Lab/VLM2Vec-Full

Text Generation • 4B • Updated Apr 7 • 45.9k • 28
TIGER-Lab/MMEB-train

Viewer • Updated Jan 28 • 2.14M • 3.77k • 16
TIGER-Lab/MMEB-eval

Viewer • Updated Oct 28, 2024 • 37k • 4.11k • 11

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24, 2024 • 29
MoDE: CLIP Data Experts via Clustering

Paper • 2404.16030 • Published Apr 24, 2024 • 15
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Paper • 2405.12130 • Published May 20, 2024 • 50
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21, 2024 • 33

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