His primary areas of investigation include Natural language processing, Artificial intelligence, Machine translation, Word and Representation. His Part of speech and Language model study in the realm of Natural language processing connects with subjects such as Process, Identity and Encoder. His research in the fields of Character overlaps with other disciplines such as Layer.
Yonatan Belinkov has included themes like Speech recognition, Translation, Convolutional neural network and Robustness in his Machine translation study. His Word study combines topics from a wide range of disciplines, such as Context, Word order, Classifier, Sentence and Deep learning. Representation is often connected to Recurrent neural network in his work.
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Artificial neural network, Machine translation and Machine learning. His Artificial intelligence study frequently draws parallels with other fields, such as Speech recognition. His Natural language processing research includes elements of Representation, Context, Word and Arabic.
Yonatan Belinkov works mostly in the field of Artificial neural network, limiting it down to topics relating to Ranking and, in certain cases, F1 score. His Machine translation research incorporates elements of Interpretability, Rule-based machine translation and Robustness. His Machine learning research is multidisciplinary, incorporating elements of Adversarial system, Training set and Natural language inference.
Yonatan Belinkov spends much of his time researching Artificial intelligence, Natural language processing, Language model, Machine learning and Transfer of learning. His Artificial intelligence study focuses mostly on Transformer, Sentence, Artificial neural network, Machine translation and Interpretability. His work investigates the relationship between Sentence and topics such as Word that intersect with problems in Encoding.
His research investigates the connection between Artificial neural network and topics such as Deep learning that intersect with problems in Algorithm and Dependency. Yonatan Belinkov has researched Natural language processing in several fields, including Interpretation and Representation. His studies deal with areas such as Schema, Cognitive psychology and Task as well as Language model.
Yonatan Belinkov mainly focuses on Artificial intelligence, Natural language processing, Causal mediation, Gender bias and Language model. His work on Machine translation, Interpretability and Deep neural networks is typically connected to Power and Similarity analysis as part of general Artificial intelligence study, connecting several disciplines of science. His studies in Natural language processing integrate themes in fields like Word, Representation, Relevance and Set.
Yonatan Belinkov undertakes multidisciplinary investigations into Causal mediation and Cognitive psychology in his work.
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Synthetic and Natural Noise Both Break Neural Machine Translation
Yonatan Belinkov;Yonatan Bisk.
international conference on learning representations (2018)
Linguistic Knowledge and Transferability of Contextual Representations
Nelson F. Liu;Matt Gardner;Yonatan Belinkov;Matthew E. Peters.
north american chapter of the association for computational linguistics (2019)
Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks
Yossi Adi;Einat Kermany;Yonatan Belinkov;Ofer Lavi.
international conference on learning representations (2016)
What do neural machine translation models learn about morphology
Yonatan Belinkov;Nadir Durrani;Fahim Dalvi;Hassan Sajjad.
meeting of the association for computational linguistics (2017)
Analysis Methods in Neural Language Processing: A Survey
Yonatan Belinkov;James R. Glass.
Transactions of the Association for Computational Linguistics (2019)
Analyzing the Structure of Attention in a Transformer Language Model
Jesse Vig;Yonatan Belinkov.
meeting of the association for computational linguistics (2019)
Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks
Yonatan Belinkov;Lluís Màrquez;Hassan Sajjad;Nadir Durrani.
international joint conference on natural language processing (2017)
End-to-End Bias Mitigation by Modelling Biases in Corpora
Rabeeh Karimi Mahabadi;Yonatan Belinkov;James Henderson.
meeting of the association for computational linguistics (2020)
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models.
Fahim Dalvi;Nadir Durrani;Hassan Sajjad;Yonatan Belinkov.
national conference on artificial intelligence (2019)
Analyzing Hidden Representations in End-to-End Automatic Speech Recognition Systems
Yonatan Belinkov;James R. Glass.
neural information processing systems (2017)
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