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The rapid development of Multimodal Large Language Models (MLLMs), such as GPT-4o, marks a significant step toward artificial general intelligence.
Adaptive mixtures of local experts
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Visualizing data using t-sne
Van der Maaten, L. and Hinton, G · 2008
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Multi30k: Multilingual english-german image descriptions
Elliott, D., Frank, S., Sima’an, K., and Specia, L · 2016
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Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Elfwing, S., Uchibe, E., and Doya, K · 2018
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Improving language understanding by generative pre-training, 2018
Radford, A., Narasimhan, K., Salimans, T., Sutskever, I., et al · 2018
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Unsupervised cross-lingual representation learning at scale
Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzmán, F., Grave, E., Ott, M., Zettlemoyer, L., and Stoyanov, V · 2019
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Language models are few-shot learners
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Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts
Changpinyo, S., Sharma, P., Ding, N., and Soricut, R · 2021
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Lora: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 2021
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M3p: Learning universal representations via multitask multilingual multimodal pre-training
Ni, M., Huang, H., Su, L., Cui, E., Bharti, T., Wang, L., Zhang, D., and Duan, N · 2021
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Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al · 2021
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Share or not? learning to schedule language-specific capacity for multilingual translation
Zhang, B., Bapna, A., Sennrich, R., and Firat, O · 2021
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Uc2: Universal cross-lingual cross-modal vision-and-language pre-training
Zhou, M., Zhou, L., Wang, S., Cheng, Y., Li, L., Yu, Z., and Liu, J · 2021
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Flamingo: a visual language model for few-shot learning
Alayrac, J.-B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al · 2022
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Pali: A jointly-scaled multilingual language-image model
Chen, X., Wang, X., Changpinyo, S., Piergiovanni, A., Padlewski, P., Salz, D., Goodman, S., Grycner, A., Mustafa, B., Beyer, L., et al · 2022
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Glm: General language model pretraining with autoregressive blank infilling
Du, Z., Qian, Y., Liu, X., Ding, M., Qiu, J., Yang, Z., and Tang, J · 2022
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Learn to explain: Multimodal reasoning via thought chains for science question answering
Lu, P., Mishra, S., Xia, T., Qiu, L., Chang, K.-W., Zhu, S.-C., Tafjord, O., Clark, P., and Kalyan, A · 2022
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Multilingual neural machine translation with the right amount of sharing
Purason, T. and Tättar, A · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
Schuhmann, C., Beaumont, R., Vencu, R., Gordon, C., Wightman, R., Cherti, M., Coombes, T., Katta, A., Mullis, C., Wortsman, M., et al · 2022
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Chinese clip: Contrastive vision-language pretraining in chinese
Yang, A., Pan, J., Lin, J., Men, R., Zhang, Y., Zhou, J., and Zhou, C · 2022
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Dino: Detr with improved denoising anchor boxes for end-to-end object detection
Zhang, H., Li, F., Liu, S., Zhang, L., Su, H., Zhu, J., Ni, L. M., and Shum, H.-Y · 2022
Cited alongside, same era.
Introducing our multimodal models, 2023
Bavishi, R., Elsen, E., Hawthorne, C., Nye, M., Odena, A., Somani, A., and Taşırlar, S · 2023
Cited alongside, same era.
When is multilinguality a curse? language modeling for 250 high-and low-resource languages
Chang, T. A., Arnett, C., Tu, Z., and Bergen, B. K · 2023
Cited alongside, same era.
Vicuna: An open-source chatbot impressing gpt-4 with 90% chatgpt quality, 2023
Chiang, W.-L., Li, Z., Lin, Z., Sheng, Y., Wu, Z., Zhang, H., Zheng, L., Zhuang, S., Zhuang, Y., Gonzalez, J. E., et al · 2023
Cited alongside, same era.
Instructblip: Towards general-purpose vision-language models with instruction tuning
Breaking the curse of multilinguality with cross-lingual expert language models
Blevins, T., Limisiewicz, T., Gururangan, S., Li, M., Gonen, H., Smith, N. A., and Zettlemoyer, L · 2024
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Are we on the right way for evaluating large vision-language models?
Chen, L., Li, J., Dong, X., Zhang, P., Zang, Y., Chen, Z., Duan, H., Wang, J., Qiao, Y., Lin, D., et al · 2024
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Vlmevalkit: An open-source toolkit for evaluating large multi-modality models
Duan, H., Yang, J., Qiao, Y., Fang, X., Chen, L., Liu, Y., Dong, X., Zang, Y., Zhang, P., Wang, J., et al · 2024
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Chatglm: A family of large language models from glm-130b to glm-4 all tools
GLM, T., Zeng, A., Xu, B., Wang, B., Zhang, C., Yin, D., Rojas, D., Feng, G., Zhao, H., Lai, H., Yu, H., Wang, H., Sun, J., Zhang, J., Cheng, J., Gui, J., Tang, J., Zhang, J., Li, J., Zhao, L., Wu, L., Zhong, L., Liu, M., Huang, M., Zhang, P., Zheng, Q., Lu, R., Duan, S., Zhang, S., Cao, S., Yang, S., Tam, W. L., Zhao, W., Liu, X., Xia, X., Zhang, X., Gu, X., Lv, X., Liu, X., Liu, X., Yang, X., Song, X., Zhang, X., An, Y., Xu, Y., Niu, Y., Yang, Y., Li, Y., Bai, Y., Dong, Y., Qi, Z., Wang, Z., Yang, Z., Du, Z., Hou, Z., and Wang, Z · 2024
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Dai, W., Li, J., Li, D., Tiong, A. M. H., Zhao, J., Wang, W., Li, B., Fung, P., and Hoi, S · 2023
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Eva-02: A visual representation for neon genesis
Fang, Y., Sun, Q., Wang, X., Huang, T., Wang, X., and Cao, Y · 2023
Cited alongside, same era.
Mme: A comprehensive evaluation benchmark for multimodal large language models
Fu, C., Chen, P., Shen, Y., Qin, Y., Zhang, M., Lin, X., Qiu, Z., Lin, W., Qiu, Z., Lin, W., et al · 2023
Cited alongside, same era.
Large multilingual models pivot zero-shot multimodal learning across languages
Hu, J., Yao, Y., Wang, C., Wang, S., Pan, Y., Chen, Q., Yu, T., Wu, H., Zhao, Y., Zhang, H., et al · 2023
Cited alongside, same era.
Jiang, A. Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D. S., Casas, D. d. l., Bressand, F., Lengyel, G., Lample, G., Saulnier, L., et al · 2023
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Ziya-visual: Bilingual large vision-language model via multi-task instruction tuning
Lu, J., Zhang, D., Wu, X., Gao, X., Gan, R., Zhang, J., Song, Y., and Zhang, P · 2023
Cited alongside, same era.
Dinov2: Learning robust visual features without supervision
Oquab, M., Darcet, T., Moutakanni, T., Vo, H., Szafraniec, M., Khalidov, V., Fernandez, P., Haziza, D., Massa, F., El-Nouby, A., et al · 2023
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Learning language-specific layers for multilingual machine translation
Pires, T. P., Schmidt, R. M., Liao, Y.-H., and Peitz, S · 2023
Cited alongside, same era.
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Grattafiori, A., Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Vaughan, A., et al · 2024
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Why do llava vision-language models reply to images in english?
Hinck, M., Holtermann, C., Olson, M. L., Schneider, F., Yu, S., Bhiwandiwalla, A., Lauscher, A., Tseng, S., and Lal, V · 2024
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Building and better understanding vision-language models: insights and future directions
Laurençon, H., Marafioti, A., Sanh, V., and Tronchon, L · 2024
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Llava-next: Improved reasoning, ocr, and world knowledge, January 2024
Liu, H., Li, C., Li, Y., Li, B., Zhang, Y., Shen, S., and Lee, Y. J · 2024
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Mm1: Methods, analysis & insights from multimodal llm pre-training
McKinzie, B., Gan, Z., Fauconnier, J.-P., Dodge, S., Zhang, B., Dufter, P., Shah, D., Du, X., Peng, F., Weers, F., et al · 2024
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Gpt-4o: Hello gpt-4o
OpenAI · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Reid, M., Savinov, N., Teplyashin, D., Lepikhin, D., Lillicrap, T., Alayrac, J.-b., Soricut, R., Lazaridou, A., Firat, O., Schrittwieser, J., et al · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Wang, P., Bai, S., Tan, S., Wang, S., Fan, Z., Bai, J., Chen, K., Liu, X., Wang, J., Ge, W., Fan, Y., Dang, K., Du, M., Ren, X., Men, R., Liu, D., Zhou, C., Zhou, J., and Lin, J · 2024
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Realworldqa dataset
x.ai · 2024
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Yang, A., Yang, B., Zhang, B., Hui, B., Zheng, B., Yu, B., Li, C., Liu, D., Huang, F., Wei, H., et al · 2024
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Yi: Open foundation models by 01. ai
Young, A., Chen, B., Li, C., Huang, C., Zhang, G., Zhang, G., Li, H., Zhu, J., Chen, J., Chang, J., et al · 2024
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Sparse moe with language guided routing for multilingual machine translation
Zhao, X., Chen, X., Cheng, Y., and Chen, T · 2024
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Insight-v: Exploring long-chain visual reasoning with multimodal large language models
Dong, Y., Liu, Z., Sun, H.-L., Yang, J., Hu, W., Rao, Y., and Liu, Z · 2025
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Large language-geometry model: When llm meets equivariance
Li, Z., Cen, J., Su, B., Huang, W., Xu, T., Rong, Y., and Zhao, D · 2025
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Internvl3: Exploring advanced training and test-time recipes for open-source multimodal models
Zhu, J., Wang, W., Chen, Z., Liu, Z., Ye, S., Gu, L., Duan, Y., Tian, H., Su, W., Shao, J., et al · 2025
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