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Multimodal Large Language Models (MLLMs) are experiencing rapid growth, yielding a plethora of noteworthy contributions in recent months.
Kazemzadeh, S., Ordonez, V., Matten, M., Berg, T.: Referitgame: Referring to objects in photographs of natural scenes. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). pp. 787–798 (2014)
2014
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2015
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Mao, J., Huang, J., Toshev, A., Camburu, O., Yuille, A.L., Murphy, K.: Generation and comprehension of unambiguous object descriptions. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 11–20 (2016)
2016
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Yu, L., Poirson, P., Yang, S., Berg, A.C., Berg, T.L.: Modeling context in referring expressions. In: Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II 14. pp. 69–85. Springer (2016)
2016
Earlier work this paper cites.
Goyal, Y., Khot, T., Summers-Stay, D., Batra, D., Parikh, D.: Making the v in vqa matter: Elevating the role of image understanding in visual question answering. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 6904–6913 (2017)
2017
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Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.J., Shamma, D.A., et al.: Visual genome: Connecting language and vision using crowdsourced dense image annotations. International journal of computer vision 123
2017
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2017
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Radford, A., Narasimhan, K., Salimans, T., Sutskever, I., et al.: Improving language understanding by generative pre-training (2018)
2018
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Berant, J., Deutch, D., Globerson, A., Milo, T., Wolfson, T.: Explaining queries over web tables to non-experts. In: 2019 IEEE 35th international conference on data engineering (ICDE). pp. 1570–1573. IEEE (2019)
2019
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Hudson, D.A., Manning, C.D.: Gqa: A new dataset for real-world visual reasoning and compositional question answering. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 6700–6709 (2019)
2019
Earlier work this paper cites.
Li, X., Xu, C., Wang, X., Lan, W., Jia, Z., Yang, G., Xu, J.: Coco-cn for cross-lingual image tagging, captioning, and retrieval. IEEE Transactions on Multimedia 21
2019
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Marino, K., Rastegari, M., Farhadi, A., Mottaghi, R.: Ok-vqa: A visual question answering benchmark requiring external knowledge. In: Proceedings of the IEEE/cvf conference on computer vision and pattern recognition. pp. 3195–3204 (2019)
2019
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Mishra, A., Shekhar, S., Singh, A.K., Chakraborty, A.: Ocr-vqa: Visual question answering by reading text in images. In: 2019 international conference on document analysis and recognition (ICDAR). pp. 947–952. IEEE (2019)
2019
Earlier work this paper cites.
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I., et al.: Language models are unsupervised multitask learners. OpenAI blog 1
2019
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Shah, S., Mishra, A., Yadati, N., Talukdar, P.P.: Kvqa: Knowledge-aware visual question answering. In: Proceedings of the AAAI conference on artificial intelligence. vol. 33, pp. 8876–8884 (2019)
2019
Earlier work this paper cites.
Singh, A., Natarajan, V., Shah, M., Jiang, Y., Chen, X., Batra, D., Parikh, D., Rohrbach, M.: Towards vqa models that can read. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 8317–8326 (2019)
2019
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2019
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Chen, Y.C., Li, L., Yu, L., El Kholy, A., Ahmed, F., Gan, Z., Cheng, Y., Liu, J.: Uniter: Universal image-text representation learning. In: European conference on computer vision. pp. 104–120. Springer (2020)
2020
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2020
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JaidedAI: Easyocr. https://github.com/JaidedAI/EasyOCR (2020)
2020
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Li, X., Yin, X., Li, C., Zhang, P., Hu, X., Zhang, L., Wang, L., Hu, H., Dong, L., Wei, F., et al.: Oscar: Object-semantics aligned pre-training for vision-language tasks. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXX 16. pp. 121–137. Springer (2020)
2020
Cited alongside, same era.
Esser, P., Rombach, R., Ommer, B.: Taming transformers for high-resolution image synthesis. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. pp. 12873–12883 (2021)
2021
Cited alongside, same era.
2021
Cited alongside, same era.
Lee, K., Joshi, M., Turc, I.R., Hu, H., Liu, F., Eisenschlos, J.M., Khandelwal, U., Shaw, P., Chang, M.W., Toutanova, K.: Pix2struct: Screenshot parsing as pretraining for visual language understanding. In: International Conference on Machine Learning. pp. 18893–18912. PMLR (2023)
2023
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2023
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LinkSoul: Chinese-llava-vision-instructions. https://huggingface.co/datasets/LinkSoul/Chinese-LLaVA-Vision-Instructions (2023)
2023
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2023
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2021
Cited alongside, same era.
Mathew, M., Karatzas, D., Jawahar, C.: Docvqa: A dataset for vqa on document images. In: Proceedings of the IEEE/CVF winter conference on applications of computer vision. pp. 2200–2209 (2021)
2021
Cited alongside, same era.
Radford, A., Kim, J.W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.: Learning transferable visual models from natural language supervision. In: International conference on machine learning. pp. 8748–8763. PMLR (2021)
2021
Cited alongside, same era.
Alayrac, J.B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al.: Flamingo: a visual language model for few-shot learning. Advances in Neural Information Processing Systems 35
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Kim, G., Hong, T., Yim, M., Nam, J., Park, J., Yim, J., Hwang, W., Yun, S., Han, D., Park, S.: Ocr-free document understanding transformer. In: European Conference on Computer Vision. pp. 498–517. Springer (2022)
2022
Cited alongside, same era.
Li, J., He, X., Wei, L., Qian, L., Zhu, L., Xie, L., Zhuang, Y., Tian, Q., Tang, S.: Fine-grained semantically aligned vision-language pre-training. Advances in neural information processing systems 35
2022
Cited alongside, same era.
2022
Cited alongside, same era.
Mu, N., Kirillov, A., Wagner, D., Xie, S.: Slip: Self-supervision meets language-image pre-training. In: European Conference on Computer Vision. pp. 529–544. Springer (2022)
2022
Cited alongside, same era.
2023
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2023
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2023
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OpenAI: ChatGPT. https://openai.com/blog/chatgpt/ (2023)
2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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2023
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