| VisCo: Leveraging Large Language Models as Intrinsic Encoders for Visual Token Compression | ACM MM 2026 | 2026-07-14 |  | - |
| TableDART: Dynamic Adaptive Multi-Modal Routing for Table Understanding | ICLR 2026 | 2025-09-18 |  | - |
| Adaptive MLP Pruning for Large Vision Transformers (AMP) | arXiv | 2026-03-10 |  |  |
| MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning | CVPR 2026 | 2026-02-23 |  | - |
| Diversity-Guided MLP Reduction for Efficient Large Vision Transformers (DGMR) | arXiv | 2025-06-10 |  |  |
| Learning Compact Vision Tokens for Efficient Large Multimodal Models (LLaVA-STF) | arXiv | 2025-06-08 |  |  |
| ✨ InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models | arXiv | 2025-04-14 |  | 
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| InternVL-X: Advancing and Accelerating InternVL Series with Efficient Visual Token Compression (Baidu) | arXiv | 2025-03-27 |  | - |
| M-LLM Based Video Frame Selection for Efficient Video Understanding (CMU) | arXiv | 2025-02-27 | - | - |
| MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMs | ICLR 2025 | 2025-02-24 |  | - |
| ✨ Qwen2.5 VL | - | 2025-01-26 |  |  |
| InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling | arXiv | 2025-01-21 |  | - |
| LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding (Spatial-Temporal Compression) | arXiv | 2025-01-14 |  | - |
| LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding | arXiv | 2025-01-09 |  | - |
| Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos | arXiv | 2025-01-07 |  |  |
| FrameFusion: Combining Similarity and Importance for Video Token Reduction on Large Visual Language Models (Video Token Compression) | arXiv | 2024-12-30 |  |  |
| ✨ Apollo: An Exploration of Video Understanding in Large Multimodal Models (Exploration) (Meta) | arXiv | 2024-12-13 |  |  |
| CompCap: Improving Multimodal Large Language Models with Composite Captions (Meta) | arXiv | 2024-12-09 | - | - |
| ✨ Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling (InternVL 2.5) | arXiv | 2024-12-06 |  |  |
| xGen-MM-Vid (BLIP-3-Video): You Only Need 32 Tokens to Represent a Video Even in VLMs | arXiv | 2024-10-21 | - |  |
| [Model, Dataset] Personalized Visual Instruction Tuning (PVIT, PVIT-3M) | arXiv | 2024-10-09 |  |  |
| ✨ Video Instruction Tuning With Synthetic Data (LLaVA-Video, LLaVA-NeXT Series) | arXiv | 2024-10-03 |  | 
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| EMOVA: Empowering Language Models to See, Hear and Speak with Vivid Emotions | arXiv | 2024-09-26 | - |  |
| Instruction-guided Multi-Granularity Segmentation and Captioning with Large Multimodal Model (MGLMM, Alibaba) | arXiv | 2024-09-20 |  |  |
| POINTS: Improving Your Vision-language Model with Affordable Strategies (WeChat) | arXiv | 2024-09-07 |  | - |
| ✨ xGen-MM (BLIP-3): A Family of Open Large Multimodal Models | arXiv | 2024-08-16 |  | 
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| ✨ LLaVA-OneVision: Easy Visual Task Transfer (LLaVA-NeXT Series) | arXiv | 2024-08-06 |  | 
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| Tarsier: Recipes for Training and Evaluating Large Video Description Models (Tarsier, Dream1k, by ByteDance) | arXiv | 2024-07-30 |  |  |
| ✨ InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output | arXiv | 2024-07-03 |  | - |
| TokenPacker: Efficient Visual Projector for Multimodal LLM | arXiv | 2024-07-02 |  | - |
| ✨ Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs (Cambrian, Data Rationing) | arXiv | 2024-06-24 |  | 
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| ✨ Long Context Transfer from Language to Vision (LongVA, by Ziwei Liu, Chunyuan Li) | arXiv | 2024-06-24 |  |  |
| Generative Visual Instruction Tuning | arXiv | 2024-06-17 |  | - |
| ✨ VideoGPT+: Integrating Image and Video Encoders for Enhanced Video Understanding | arXiv | 2024-06-13 |  |  |
| ✨ 4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities (Apple) | arXiv | 2024-06-13 |  | 
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| VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs | arXiv | 2024-06-11 |  | - |
| Wings: Learning Multimodal LLMs without Text-only Forgetting | arXiv | 2024-06-05 | - | - |
| Enhancing Multimodal Large Language Models with Multi-instance Visual Prompt Generator for Visual Representation Enrichment (MIVPG) | arXiv | 2024-06-05 | - | - |
| PosterLLaVa: Constructing a Unified Multi-modal Layout Generator with LLM | arXiv | 2024-06-05 |  | - |
| OLIVE: Object Level In-Context Visual Embeddings | ACL 2024 | 2024-06-02 |  | - |
| X-VILA: Cross-Modality Alignment for Large Language Model (by NVIDIA) | arXiv | 2024-05-29 | - |  |
| ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal Models | arXiv | 2024-05-24 |  | - |
| Prompt-Aware Adapter: Towards Learning Adaptive Visual Tokens for Multimodal Large Language Models | arXiv | 2024-05-24 | - | - |
| LOVA3: Learning to Visual Question Answering, Asking and Assessment | arXiv | 2024-05-23 |  | - |
| AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability | arXiv | 2024-05-23 |  |  |
| Chameleon: Mixed-Modal Early-Fusion Foundation Models (Meta) | arXiv | 2024-05-16 |  |  |
| CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts | arXiv | 2024-05-09 |  | 

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| ImageInWords: Unlocking Hyper-Detailed Image Descriptions (Google) | arXiv | 2024-05-05 |  | 
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| ✨ What matters when building vision-language models? (Idefics2) | arXiv | 2024-05-03 | - |
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| MANTIS: Interleaved Multi-Image Instruction Tuning | arXiv | 2024-05-02 |  |  |
| Wiki-LLaVA: Hierarchical Retrieval-Augmented Generation for Multimodal LLMs | CVPR 2024 Workshop | 2024-04-23 | - |  |
| Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models | arXiv | 2024-04-19 |  | 
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| MoVA: Adapting Mixture of Vision Experts to Multimodal Context | arXiv | 2024-04-19 |  | - |
| Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models | arXiv | 2024-04-18 | - | 
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| LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation? (LaDiC) | NAACL 2024 | 2024-04-16 |  | - |
| AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception (AesExpert, AesMMIT Dataset) | arXiv | 2024-04-15 |  | - |
| Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models (Ferret-v2) | arXiv | 2024-04-11 | - | - |
| MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies (MiniCPM series) | arXiv | 2024-04-09 | 
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| Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs (Ferret-UI) | arXiv | 2024-04-08 | - | - |
| MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding | CVPR 2024 | 2024-04-08 |  |  |
| Koala: Key frame-conditioned long video-LLM | CVPR 2024 | 2024-04-05 |  |  |
| MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens | arXiv | 2024-04-04 |  |  |
| LongVLM: Efficient Long Video Understanding via Large Language Models | arXiv | 2024-04-04 |  | - |
| InternVideo2: Scaling Foundation Models for Multimodal Video Understanding | ECCV 2024 | 2024-03-22 |  | - |
| VideoAgent: Long-form Video Understanding with Large Language Model as Agent (key frame) | arXiv | 2024-03-15 | - | - |
| ✨ MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training (Apple) | arXiv | 2024-03-14 | - | - |
| UniCode: Learning a Unified Codebook for Multimodal Large Language Models | arXiv | 2024-03-14 | - | - |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context | arXiv | 2024-03-08 | - |  |
| Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models | arXiv | 2023-03-05 |  | - |
| RegionGPT: Towards Region Understanding Vision Language Model | CVPR 2024 | 2024-03-04 | - |  |
| All in an Aggregated Image for In-Image Learning | arXiv | 2024-02-28 |  | - |
| Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners | CVPR 2024 | 2024-02-27 |  |  |
| TMT: Tri-Modal Translation between Speech, Image, and Text by Processing Different Modalities as Different Languages | arXiv | 2024-02-25 | - | - |
| LLMBind: A Unified Modality-Task Integration Framework | arXiv | 2024-02-22 | - | - |
| ✨ ALLaVA: Harnessing GPT4V-synthesized Data for A Lite Vision-Language Model (ALLaVA) | arXiv | 2024-02-18 |  | 
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| MobileVLM V2: Faster and Stronger Baseline for Vision Language Model | arXiv | 2024-02-06 |  | - |
| MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices | arXiv | 2023-12-28 |  | - |
| Gemini: A Family of Highly Capable Multimodal Models | arXiv | 2023-12-19 | - |  |
| ✨ Osprey: Pixel Understanding with Visual Instruction Tuning | CVPR 2024 | 2023-12-15 |  | - |
| ✨ VILA: On Pre-training for Visual Language Models (NVIDIA, MIT) | CVPR 2024 | 2023-12-12 |  | - |
| Vary: Scaling up the Vision Vocabulary for Large Vision-Language Models | arXiv | 2023-12-11 |  |  |
| Prompt Highlighter: Interactive Control for Multi-Modal LLMs | CVPR 2024 | 2023-12-07 |  |  |
| PixelLM: Pixel Reasoning with Large Multimodal Model | CVPR 2024 | 2023-12-04 |  |  |
| APoLLo : Unified Adapter and Prompt Learning for Vision Language Models | EMNLP 2023 | 2023-12-04 |  |  |
| LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models | arXiv | 2023-11-28 |  | 
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| PG-Video-LLaVA: Pixel Grounding Large Video-Language Models | arXiv | 2023-11-22 |  | - |
| ShareGPT4V: Improving Large Multi-Modal Models with Better Captions | arXiv | 2023-11-21 |  |  |
| LION : Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge | CVPR 2024 | 2023-11-20 |  |  |
| Video-LLaVA: Learning United Visual Representation by Alignment Before Projection | arXiv | 2023-11-16 |  | - |
| mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration | arXiv | 2023-11-07 |  | - |
| MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning | arXiv | 2023-10-14 |  |  |
| Ferret: Refer and Ground Anything Anywhere at Any Granularity (Ferret) | ICLR 2024 | 2023-10-11 |  | - |
| ✨ Improved Baselines with Visual Instruction Tuning (LLaVA-1.5) | arXiv | 2023-10-05 |  |  |
| Aligning Large Multimodal Models with Factually Augmented RLHF (LLaVA-RLHF, MMHal-Bench (hallucination)) | arXiv | 2023-09-25 |  | 
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| MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning | ICLR 2024 | 2023-09-14 |  | - |
| Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond | arXiv | 2023-08-24 |  |  |
| Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages (VisCPM-Chat/Paint) | ICLR 2024 | 2023-08-23 |  | - |
| SVIT: Scaling up Visual Instruction Tuning | arXiv | 2023-07-09 |  |  |
| Kosmos-2: Grounding Multimodal Large Language Models to the World (Kosmos-2, GrIT Dataset) | arXiv | 2023-06-26 |  | 
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| M$^3$IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning | arXiv | 2023-06-07 | - | 
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| InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning | NeurIPS 2023 | 2023-05-11 |  | - |
| MultiModal-GPT: A Vision and Language Model for Dialogue with Humans | arXiv | 2023-05-08 |  | - |
| VPGTrans: Transfer Visual Prompt Generator across LLMs | NeurIPS 2023 | 2023-05-02 |  |  |
| mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality | arXiv | 2023-04-27 |  | - |
| ✨ MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models | ICLR 2024 | 2023-04-20 |  |  |
| ✨ Visual Instruction Tuning (LLaVA) | NeurIPS 2023 | 2023-04-17 |  | 
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| Language Is Not All You Need: Aligning Perception with Language Models (Kosmos-1) | NeurIPS 2023 | 2023-02-27 |  | - |
| Multimodal Chain-of-Thought Reasoning in Language Models | arXiv | 2023-02-02 |  | - |
| BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models | ICML 2023 | 2023-01-30 |  | - |
| Flamingo: a Visual Language Model for Few-Shot Learning | NeurIPS 2022 | 2022-04-29 |  | - |