BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper
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2404.12390
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Published
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26
Vision Language Models
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TextSquare: Scaling up Text-Centric Visual Instruction Tuning
Paper • 2404.12803 • Published • 30 -
Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
Paper • 2404.13013 • Published • 31 -
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Paper • 2404.06512 • Published • 30 -
Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs
Paper • 2404.05719 • Published • 82 -
MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding
Paper • 2404.05726 • Published • 21 -
MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens
Paper • 2404.03413 • Published • 26 -
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Paper • 2311.16502 • Published • 35 -
Kosmos-2: Grounding Multimodal Large Language Models to the World
Paper • 2306.14824 • Published • 34 -
CogVLM: Visual Expert for Pretrained Language Models
Paper • 2311.03079 • Published • 25 -
Pegasus-v1 Technical Report
Paper • 2404.14687 • Published • 31 -
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Paper • 2404.16821 • Published • 56 -
List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs
Paper • 2404.16375 • Published • 17 -
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Paper • 2404.16790 • Published • 8 -
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning
Paper • 2404.16994 • Published • 36 -
What matters when building vision-language models?
Paper • 2405.02246 • Published • 102 -
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Paper • 2405.21075 • Published • 22 -
ShareGPT4Video: Improving Video Understanding and Generation with Better Captions
Paper • 2406.04325 • Published • 73 -
An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels
Paper • 2406.09415 • Published • 51 -
OpenVLA: An Open-Source Vision-Language-Action Model
Paper • 2406.09246 • Published • 37 -
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Paper • 2406.09411 • Published • 20 -
Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
Paper • 2406.09403 • Published • 21 -
mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus
Paper • 2406.08707 • Published • 16 -
MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs
Paper • 2406.11833 • Published • 62 -
VideoLLM-online: Online Video Large Language Model for Streaming Video
Paper • 2406.11816 • Published • 24 -
ChartMimic: Evaluating LMM's Cross-Modal Reasoning Capability via Chart-to-Code Generation
Paper • 2406.09961 • Published • 55 -
Needle In A Multimodal Haystack
Paper • 2406.07230 • Published • 53 -
Wolf: Captioning Everything with a World Summarization Framework
Paper • 2407.18908 • Published • 32 -
Coarse Correspondence Elicit 3D Spacetime Understanding in Multimodal Language Model
Paper • 2408.00754 • Published • 22 -
OmniParser for Pure Vision Based GUI Agent
Paper • 2408.00203 • Published • 24 -
LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 51 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51 -
VideoLLaMB: Long-context Video Understanding with Recurrent Memory Bridges
Paper • 2409.01071 • Published • 27 -
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
Paper • 2409.12191 • Published • 76 -
NVLM: Open Frontier-Class Multimodal LLMs
Paper • 2409.11402 • Published • 73 -
LLaVA-3D: A Simple yet Effective Pathway to Empowering LMMs with 3D-awareness
Paper • 2409.18125 • Published • 34 -
OmniBench: Towards The Future of Universal Omni-Language Models
Paper • 2409.15272 • Published • 28 -
Progressive Multimodal Reasoning via Active Retrieval
Paper • 2412.14835 • Published • 73 -
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Paper • 2412.10360 • Published • 140 -
Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity Visual Descriptions
Paper • 2412.08737 • Published • 53 -
OmniFlow: Any-to-Any Generation with Multi-Modal Rectified Flows
Paper • 2412.01169 • Published • 13 -
PaliGemma 2: A Family of Versatile VLMs for Transfer
Paper • 2412.03555 • Published • 128 -
ShowUI: One Vision-Language-Action Model for GUI Visual Agent
Paper • 2411.17465 • Published • 80 -
VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained Video Reasoning via Core Frame Selection
Paper • 2411.14794 • Published • 13 -
Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
Paper • 2411.10442 • Published • 74 -
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
Paper • 2411.10440 • Published • 114 -
BLIP3-KALE: Knowledge Augmented Large-Scale Dense Captions
Paper • 2411.07461 • Published • 22 -
M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework
Paper • 2411.06176 • Published • 45 -
Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models
Paper • 2411.04996 • Published • 51 -
Analyzing The Language of Visual Tokens
Paper • 2411.05001 • Published • 24 -
DynaMem: Online Dynamic Spatio-Semantic Memory for Open World Mobile Manipulation
Paper • 2411.04999 • Published • 18 -
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 99 -
Virgo: A Preliminary Exploration on Reproducing o1-like MLLM
Paper • 2501.01904 • Published • 32 -
Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks
Paper • 2501.08326 • Published • 32 -
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Paper • 2501.06186 • Published • 61 -
OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?
Paper • 2501.05510 • Published • 39 -
Are VLMs Ready for Autonomous Driving? An Empirical Study from the Reliability, Data, and Metric Perspectives
Paper • 2501.04003 • Published • 25 -
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot
Paper • 2501.09012 • Published • 10 -
Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
Paper • 2501.09755 • Published • 34 -
Do generative video models learn physical principles from watching videos?
Paper • 2501.09038 • Published • 32 -
FAST: Efficient Action Tokenization for Vision-Language-Action Models
Paper • 2501.09747 • Published • 23 -
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Paper • 2501.12380 • Published • 82 -
InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model
Paper • 2501.12368 • Published • 42 -
VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding
Paper • 2501.13106 • Published • 83 -
Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos
Paper • 2501.13826 • Published • 24 -
Temporal Preference Optimization for Long-Form Video Understanding
Paper • 2501.13919 • Published • 22 -
PixelWorld: Towards Perceiving Everything as Pixels
Paper • 2501.19339 • Published • 16 -
Ola: Pushing the Frontiers of Omni-Modal Language Model with Progressive Modality Alignment
Paper • 2502.04328 • Published • 26 -
Scaling Laws in Patchification: An Image Is Worth 50,176 Tokens And More
Paper • 2502.03738 • Published • 10 -
Scaling Pre-training to One Hundred Billion Data for Vision Language Models
Paper • 2502.07617 • Published • 27 -
CoS: Chain-of-Shot Prompting for Long Video Understanding
Paper • 2502.06428 • Published • 10 -
EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents
Paper • 2502.09560 • Published • 32 -
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
Paper • 2502.09621 • Published • 26 -
Exploring the Potential of Encoder-free Architectures in 3D LMMs
Paper • 2502.09620 • Published • 25 -
mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data
Paper • 2502.08468 • Published • 13 -
ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models
Paper • 2502.09696 • Published • 38 -
PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC
Paper • 2502.14282 • Published • 14