Jurafsky, Daniel & James H. Martin, N-gram Language Models., https://web.stanford.edu/~jurafsky/slp3/, 2022
Jurafsky, Daniel & James H. Martin, Vector Semantics and Embeddings, https://web.stanford.edu/~jurafsky/slp3/, 2022
Jurafsky, Daniel & James H. Martin, Neural Networks and Neural Language Models, https://web.stanford.edu/~jurafsky/slp3/, 2022
Jurafsky, Daniel & James H. Martin, Sequence Labeling for Parts of Speech and Named Entities, https://web.stanford.edu/~jurafsky/slp3/, 2022
Bibliografía Complementaria
Baroni, Marco, Raffaella Bernardi & Roberto Zamparelli, Frege in space: A program for compositional distributional semantics, Linguistic Issues in Language Technologies 9(6): 5-110, University of Colorado Boulder, 2014
Baroni, Marco, Georgiana Dinu & Germán Kruszewski, Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors, Proceedings of the 52nd Annual Meeting of the ACL (Vol. 1), Association for Computational Linguistics, 2014
Church, Kenneth Ward, Zeyu Chen & Yanjun Ma, Emerging trends: A gentle introduction to fine-tuning, Natural Language Engineering, 27, Cambridge University Press, 2021
Devlin, Jacob, Ming-Wei Chang, Kenton Lee & Kristina Toutanova, BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, Proceedings of the 2019 Conference of the NACL-HLT (Vol. 1), Association for Computational Linguistics, 2019
Erk, Katrin, Vector space models of word meaning and phrase meaning: A survey, Language and Linguistics Compass 6.10, Wiley & Sons, 2012
Linzen, Tal, Issues in evaluating semantic spaces using word analogies, Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP, Association for Computational Linguistics, 2016
Hirschberg, Julia & Manning, Christopher D., Advances in natural language processing, Science 349.6245, AAAS, 2015
Mikolov, Tomas, Wen-tau Yih & Zweig Geoffrey, Linguistic Regularities in Continuous Space Word Representations, Proceedings of the 2013 Conference of the NACL-HLT, Association for Computational Linguistics, 2013
Taher Pilehvar, Mohammad & Jose Camacho-Collados, José, Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning, Computational Linguistics, 47(3), MIT Press, 2021
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Jurafsky, Daniel & James H. Martin, N-gram Language Models., https://web.stanford.edu/~jurafsky/slp3/, 2022