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Researcher profile

Chris Alberti

7 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. Structured Training for Neural Network Transition-Based Parsing

    2015

    David Weiss, Chris Alberti, Michael Collins, Slav Petrov. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2015.

  2. Globally Normalized Transition-Based Neural Networks

    2016

    Daniel Andor, Chris Alberti, David Weiss, Aliaksei Severyn, Alessandro Presta, Kuzman Ganchev, Slav Petrov, Michael Collins. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2016.

  3. A BERT Baseline for the Natural Questions

    2019 · arXiv (Cornell University)

    This technical note describes a new baseline for the Natural Questions. Our model is based on BERT and reduces the gap between the model F1 scores reported in the original dataset paper and the human …

  4. Natural Questions: A Benchmark for Question Answering Research

    2019 · Transactions of the Association for Computational Linguistics

    We present the Natural Questions corpus, a question answering data set. Questions consist of real anonymized, aggregated queries issued to the Google search engine. An annotator is presented with a question along with a Wikipedia …

  5. Corpora Generation for Grammatical Error Correction

    2019

    Jared Lichtarge, Chris Alberti, Shankar Kumar, Noam Shazeer, Niki Parmar, Simon Tong. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and …

  6. Synthetic QA Corpora Generation with Roundtrip Consistency

    2019

    We introduce a novel method of generating synthetic question answering corpora by combining models of question generation and answer extraction, and by filtering the results to ensure roundtrip consistency. By pretraining on the resulting corpora …

  7. Big Bird: Transformers for Longer Sequences

    2020 · arXiv (Cornell University)

    Transformers-based models, such as BERT, have been one of the most successful deep learning models for NLP. Unfortunately, one of their core limitations is the quadratic dependency (mainly in terms of memory) on the sequence …