Chris Alberti

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NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

We review the EfficientQA competition from NeurIPS 2020. The competition...
01/01/2021 ∙ by Sewon Min, et al. ∙ 15 ∙ share

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QED: A Framework and Dataset for Explanations in Question Answering

A question answering system that in addition to providing an answer prov...
09/08/2020 ∙ by Matthew Lamm, et al. ∙ 0 ∙ share

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Data Weighted Training Strategies for Grammatical Error Correction

Recent progress in the task of Grammatical Error Correction (GEC) has be...
08/07/2020 ∙ by Jared Lichtarge, et al. ∙ 0 ∙ share

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Big Bird: Transformers for Longer Sequences

Transformers-based models, such as BERT, have been one of the most succe...
07/28/2020 ∙ by Manzil Zaheer, et al. ∙ 72 ∙ share

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ETC: Encoding Long and Structured Data in Transformers

Transformer-based models have pushed the state of the art in many natura...
04/17/2020 ∙ by Joshua Ainslie, et al. ∙ 46 ∙ share

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Fusion of Detected Objects in Text for Visual Question Answering

To advance models of multimodal context, we introduce a simple yet power...
08/14/2019 ∙ by Chris Alberti, et al. ∙ 6 ∙ share

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Synthetic QA Corpora Generation with Roundtrip Consistency

We introduce a novel method of generating synthetic question answering c...
06/12/2019 ∙ by Chris Alberti, et al. ∙ 0 ∙ share

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Corpora Generation for Grammatical Error Correction

Grammatical Error Correction (GEC) has been recently modeled using the s...
04/10/2019 ∙ by Jared Lichtarge, et al. ∙ 0 ∙ share

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A BERT Baseline for the Natural Questions

This technical note describes a new baseline for the Natural Questions. ...
01/24/2019 ∙ by Chris Alberti, et al. ∙ 0 ∙ share

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SyntaxNet Models for the CoNLL 2017 Shared Task

We describe a baseline dependency parsing system for the CoNLL2017 Share...
03/15/2017 ∙ by Chris Alberti, et al. ∙ 0 ∙ share

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DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks

In this work, we present a compact, modular framework for constructing n...
03/13/2017 ∙ by Lingpeng Kong, et al. ∙ 0 ∙ share

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Globally Normalized Transition-Based Neural Networks

We introduce a globally normalized transition-based neural network model...
03/19/2016 ∙ by Daniel Andor, et al. ∙ 0 ∙ share

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Structured Training for Neural Network Transition-Based Parsing

We present structured perceptron training for neural network transition-...
06/19/2015 ∙ by David Weiss, et al. ∙ 0 ∙ share

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Chris Alberti

Featured Co-authors

Jianfeng Gao

Sebastian Riedel

Hannaneh Hajishirzi

Xiaodong Liu

Manzil Zaheer

Edouard Grave

Jordan Boyd-Graber

Hao Cheng

Weizhu Chen

Wen-tau Yih

Noam Shazeer

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

QED: A Framework and Dataset for Explanations in Question Answering

Data Weighted Training Strategies for Grammatical Error Correction

Big Bird: Transformers for Longer Sequences

ETC: Encoding Long and Structured Data in Transformers

Fusion of Detected Objects in Text for Visual Question Answering

Synthetic QA Corpora Generation with Roundtrip Consistency

Corpora Generation for Grammatical Error Correction

A BERT Baseline for the Natural Questions

SyntaxNet Models for the CoNLL 2017 Shared Task

DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks

Globally Normalized Transition-Based Neural Networks

Structured Training for Neural Network Transition-Based Parsing