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Collections including paper arxiv:2504.07951

Scaling Laws for Native Multimodal Models Scaling Laws for Native Multimodal Models

Paper • 2504.07951 • Published Apr 10 • 30
Have we unified image generation and understanding yet? An empirical study of GPT-4o's image generation ability

Paper • 2504.08003 • Published Apr 9 • 49
SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models

Paper • 2504.11468 • Published Apr 10 • 30
Towards Learning to Complete Anything in Lidar

Paper • 2504.12264 • Published Apr 16 • 9

Qwen2.5-VL Technical Report

Paper • 2502.13923 • Published Feb 19 • 211
Scaling Laws for Native Multimodal Models Scaling Laws for Native Multimodal Models

Paper • 2504.07951 • Published Apr 10 • 30
LLM-I: LLMs are Naturally Interleaved Multimodal Creators

Paper • 2509.13642 • Published Sep 17 • 8

iVideoGPT: Interactive VideoGPTs are Scalable World Models

Paper • 2405.15223 • Published May 24, 2024 • 17
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24, 2024 • 55
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27, 2024 • 90
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27, 2024 • 34

LM Capabilities and Scaling

Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15, 2024 • 28
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9, 2024 • 24
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2, 2024 • 37
Are large language models superhuman chemists?

Paper • 2404.01475 • Published Apr 1, 2024 • 19

Vision Language Models

BLINK: Multimodal Large Language Models Can See but Not Perceive

Paper • 2404.12390 • Published Apr 18, 2024 • 26
TextSquare: Scaling up Text-Centric Visual Instruction Tuning

Paper • 2404.12803 • Published Apr 19, 2024 • 30
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models

Paper • 2404.13013 • Published Apr 19, 2024 • 31
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD

Paper • 2404.06512 • Published Apr 9, 2024 • 30

Scientific papers

Scaling Laws for Native Multimodal Models Scaling Laws for Native Multimodal Models

Paper • 2504.07951 • Published Apr 10 • 30

Multimodal Analysis

Analyzing The Language of Visual Tokens

Paper • 2411.05001 • Published Nov 7, 2024 • 24
Large Multi-modal Models Can Interpret Features in Large Multi-modal Models

Paper • 2411.14982 • Published Nov 22, 2024 • 19
Rethinking Token Reduction in MLLMs: Towards a Unified Paradigm for Training-Free Acceleration

Paper • 2411.17686 • Published Nov 26, 2024 • 20
On the Limitations of Vision-Language Models in Understanding Image Transforms

Paper • 2503.09837 • Published Mar 12 • 10

LM Architectures

Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length

Paper • 2404.08801 • Published Apr 12, 2024 • 66
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Paper • 2404.07839 • Published Apr 11, 2024 • 47
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence

Paper • 2404.05892 • Published Apr 8, 2024 • 40
Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Paper • 2312.00752 • Published Dec 1, 2023 • 148

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11, 2024 • 93
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Paper • 2404.10667 • Published Apr 16, 2024 • 23
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20, 2024 • 26
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14, 2024 • 30

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

Paper • 2402.04252 • Published Feb 6, 2024 • 29
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

Scaling Laws for Native Multimodal Models Scaling Laws for Native Multimodal Models

Paper • 2504.07951 • Published Apr 10 • 30
Have we unified image generation and understanding yet? An empirical study of GPT-4o's image generation ability

Paper • 2504.08003 • Published Apr 9 • 49
SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models

Paper • 2504.11468 • Published Apr 10 • 30
Towards Learning to Complete Anything in Lidar

Paper • 2504.12264 • Published Apr 16 • 9

Scientific papers

Scaling Laws for Native Multimodal Models Scaling Laws for Native Multimodal Models

Paper • 2504.07951 • Published Apr 10 • 30

Qwen2.5-VL Technical Report

Paper • 2502.13923 • Published Feb 19 • 211
Scaling Laws for Native Multimodal Models Scaling Laws for Native Multimodal Models

Paper • 2504.07951 • Published Apr 10 • 30
LLM-I: LLMs are Naturally Interleaved Multimodal Creators

Paper • 2509.13642 • Published Sep 17 • 8

Multimodal Analysis

Analyzing The Language of Visual Tokens

Paper • 2411.05001 • Published Nov 7, 2024 • 24
Large Multi-modal Models Can Interpret Features in Large Multi-modal Models

Paper • 2411.14982 • Published Nov 22, 2024 • 19
Rethinking Token Reduction in MLLMs: Towards a Unified Paradigm for Training-Free Acceleration

Paper • 2411.17686 • Published Nov 26, 2024 • 20
On the Limitations of Vision-Language Models in Understanding Image Transforms

Paper • 2503.09837 • Published Mar 12 • 10

iVideoGPT: Interactive VideoGPTs are Scalable World Models

Paper • 2405.15223 • Published May 24, 2024 • 17
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24, 2024 • 55
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27, 2024 • 90
Matryoshka Multimodal Models

Paper • 2405.17430 • Published May 27, 2024 • 34

LM Architectures

Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length

Paper • 2404.08801 • Published Apr 12, 2024 • 66
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Paper • 2404.07839 • Published Apr 11, 2024 • 47
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence

Paper • 2404.05892 • Published Apr 8, 2024 • 40
Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Paper • 2312.00752 • Published Dec 1, 2023 • 148

LM Capabilities and Scaling

Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15, 2024 • 28
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9, 2024 • 24
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2, 2024 • 37
Are large language models superhuman chemists?

Paper • 2404.01475 • Published Apr 1, 2024 • 19

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11, 2024 • 93
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Paper • 2404.10667 • Published Apr 16, 2024 • 23
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20, 2024 • 26
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14, 2024 • 30

Vision Language Models

BLINK: Multimodal Large Language Models Can See but Not Perceive

Paper • 2404.12390 • Published Apr 18, 2024 • 26
TextSquare: Scaling up Text-Centric Visual Instruction Tuning

Paper • 2404.12803 • Published Apr 19, 2024 • 30
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models

Paper • 2404.13013 • Published Apr 19, 2024 • 31
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD

Paper • 2404.06512 • Published Apr 9, 2024 • 30

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

Paper • 2402.04252 • Published Feb 6, 2024 • 29
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

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