Охота на электроовец. Большая книга искусственного интеллекта - Сергей Сергеевич Марков

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Kalchbrenner N., Blunsom P. (2014). Recurrent Continuous Translation Models / Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, pp. 1700—1709 // https://www.aclweb.org/anthology/D13-1176/

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Sutskever I., Vinyals O., Le Q. V. (2014). Sequence to Sequence Learning with Neural Networks / Proceedings of the 27th International Conference on Neural Information Processing Systems, Vol. 2, pp. 3104–3112 // https://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf

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Bahdanau D., Cho K., Bengio Y. (2015). Neural Machine Translation by Jointly Learning to Align and Translate / International Conference on Learning Representations (ICLR-2015) // https://arxiv.org/abs/1409.0473

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«В Минске пытался прибиться хоть куда-нибудь». Дима Богданов изобрёл механизм attention и работает с лауреатом премии Тьюринга. Говорим про ML и Монреаль (2019). / Dev.BY, 3 апреля 2019 // https://devby.io/news/dmitry-bogdanov

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Mnih V., Heess N., Graves A., Kavukcuoglu K. (2014). Recurrent Models of Visual Attention / Proceedings of the 27th International Conference on Neural Information Processing Systems, Vol. 2, pp. 2204–2212 // https://papers.nips.cc/paper/5542-recurrent-models-of-visual-attention.pdf

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Ba J. L., Mnih V., Kavukcuoglu K. (2015). Multiple object recognition with visual attention / International Conference on Learning Representations (ICLR-2015) // https://arxiv.org/abs/1412.7755

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Vinyals V., Toshev A., Bengio S., Erhan D. (2015). Show and Tell: A Neural Image Caption Generator / 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) // https://doi.org/10.1109/CVPR.2015.7298935

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Vaswani A., Shazeer N., Parmar N., Uszkoreit J., Jones L., Gomez A. N., Kaiser L., Polosukhin I. (2017). Attention Is All You Need / Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017) // https://papers.nips.cc/paper/7181-attention-is-all-you-need.pdf

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Schmidhuber J. (1991). Learning to control fast-weight memories: An alternative to recurrent nets. Technical Report FKI147-91, Institut für Informatik, Technische Universität München, March 1991 // https://people.idsia.ch/~juergen/FKI-147-91ocr.pdf

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Schlag I., Irie K., Schmidhuber J. (2021). Linear Transformers Are Secretly Fast Weight Programmers // https://arxiv.org/abs/2102.11174

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Devlin J., Chang M.-W., Lee K., Toutanova K. (2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding // https://arxiv.org/abs/1810.04805

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Huang C.-Z. A., Vaswani A., Uszkoreit J., Shazeer N., Simon I., Hawthorne C., Dai A. M., Hoffman M. D., Dinculescu M., Eck D. (2018). Music Transformer // https://arxiv.org/abs/1809.04281

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Liu Y., Ott M., Goyal N., Du J., Joshi M., Chen D., Levy O., Lewis M., Zettlemoyer L., Stoyanov V. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach // https://arxiv.org/abs/1907.11692

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McCann B., Bradbury J., Xiong C., Socher R. (2017). Learned in Translation: Contextualized Word Vectors // https://arxiv.org/abs/1708.00107

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Peters M. E., Neumann M., Iyyer M., Gardner M., Clark C., Lee K., Zettlemoyer L. (2018). Deep contextualized word representations // https://arxiv.org/abs/1802.05365

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Howard J., Ruder S. (2018). Universal Language Model Fine-tuning for Text Classification // https://arxiv.org/abs/1801.06146

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Radford A., Wu J., Child R., Luan D., Amodei D., Sutskever I. (2019). Language Models are Unsupervised Multitask Learners // https://paperswithcode.com/paper/language-models-are-unsupervised-multitask

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Brown T. B., Mann B., Ryder N., Subbiah M., Kaplan J., Dhariwal P., Neelakantan A., Shyam P., Sastry G., Askell A., Agarwal S., Herbert-Voss A., Krueger G., Henighan T., Child R., Ramesh A., Ziegler D. M., Wu J., Winter C., Hesse C., Chen M., Sigler E., Litwin M., Gray S., Chess B., Clark J., Berner C., McCandlish S., Radford A., Sutskever I., Amodei D. (2020). Language Models are Few-Shot Learners // https://arxiv.org/abs/2005.14165

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Raffel C., Shazeer N., Roberts A., Lee K., Narang S., Matena M., Zhou Y., Li