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Multimodal large language models (MLLMs) have shown impressive reasoning abilities.
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Gurari, D., Li, Q., Stangl, A.J., Guo, A., Lin, C., Grauman, K., Luo, J., Bigham, J.P.: Vizwiz grand challenge: Answering visual questions from blind people. In: CVPR (2018)
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Chen, K., Hong, L., Xu, H., Li, Z., Yeung, D.Y.: Multisiam: Self-supervised multi-instance siamese representation learning for autonomous driving. In: ICCV (2021)
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Li, J., Li, D., Xiong, C., Hoi, S.: Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation. In: ICML (2022)
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Liu, Z., Han, J., Chen, K., Hong, L., Xu, H., Xu, C., Li, Z.: Task-customized self-supervised pre-training with scalable dynamic routing. In: AAAI (2022)
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Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al.: Training language models to follow instructions with human feedback. In: NeruIPS (2022)
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Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: CVPR (2022)
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Chen, K., Liu, Z., Hong, L., Xu, H., Li, Z., Yeung, D.Y.: Mixed autoencoder for self-supervised visual representation learning. In: CVPR (2023)
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Chiang, W.L., Li, Z., Lin, Z., Sheng, Y., Wu, Z., Zhang, H., Zheng, L., Zhuang, S., Zhuang, Y., Gonzalez, J.E., Stoica, I., Xing, E.P.: Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality (March 2023), https://lmsys.org/blog/2023-03-30-vicuna/
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Dubois, Y., Li, X., Taori, R., Zhang, T., Gulrajani, I., Ba, J., Guestrin, C., Liang, P., Hashimoto, T.B.: Alpacafarm: A simulation framework for methods that learn from human feedback (2023)
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2023
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2023
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2023
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Gou, Y., Ko, T., Yang, H., Kwok, J., Zhang, Y., Wang, M.: Leveraging per image-token consistency for vision-language pre-training. In: CVPR (2023)
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2023
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2023
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2023
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Zhili, L., Chen, K., Han, J., Lanqing, H., Xu, H., Li, Z., Kwok, J.: Task-customized masked autoencoder via mixture of cluster-conditional experts. In: ICLR (2023)
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2024
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Luo, H., Gu, J., Liu, F., Torr, P.: An image is worth 1000 lies: Transferability of adversarial images across prompts on vision-language models. In: ICLR (2024)
2024
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Zhao, Y., Pang, T., Du, C., Yang, X., Li, C., Cheung, N.M.M., Lin, M.: On evaluating adversarial robustness of large vision-language models. Advances in Neural Information Processing Systems 36
2024
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