Dyer, Chris

Moses: open source toolkit for statistical machine translation

Koehn, P., Zens, R., Dyer, C., Bojar, O., Constantin, A., Herbst, E., Hoang, H., Birch, A., Callison-Burch, C., Federico, M., et al. (2007) · Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions - ACL '07

Natural Language Processing TechniquesSpeech Recognition and Synthesis

Cited by 4,735

Neural Architectures for Named Entity Recognition

Lample, G., Ballesteros, M., Subramanian, S., Kawakami, K., & Dyer, C. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Topic ModelingNatural Language Processing Techniques

Cited by 4,401

Improving Vector Space Word Representations Using Multilingual Correlation

Faruqui, M., & Dyer, C. (2014) · Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 620

The NarrativeQA Reading Comprehension Challenge

Kočiský, T., Schwarz, J., Blunsom, P., Dyer, C., Hermann, K. M., Melis, G., & Grefenstette, E. (2018) · Transactions of the Association for Computational Linguistics

Topic ModelingMultimodal Machine Learning Applications

Cited by 596

Recurrent Neural Network Grammars

Dyer, C., Kuncoro, A., Ballesteros, M., & Smith, N. A. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Natural Language Processing TechniquesSyntax, Semantics, Linguistic Variation

Cited by 517

Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems

Ling, W., Yogatama, D., Dyer, C., & Blunsom, P. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 325

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Rae, J. W., Borgeaud, S., Cai, T., Millican, K., Hoffmann, J., Song, F., Aslanides, J., Henderson, S., Ring, R., Young, S., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 235

Localizing syntactic predictions using recurrent neural network grammars

Brennan, J. R., Dyer, C., Kuncoro, A., & Hale, J. T. (2020) · Neuropsychologia

Neurobiology of Language and BilingualismLanguage Development and Disorders

Cited by 58

Differentiable Scheduled Sampling for Credit Assignment

Goyal, K., Dyer, C., & Berg-Kirkpatrick, T. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 34