Sebastian Gehrmann

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Harvard University

Automatic Construction of Evaluation Suites for Natural Language Generation Datasets

Machine learning approaches applied to NLP are often evaluated by summar...
06/16/2021 ∙ by Simon Mille, et al. ∙ 0 ∙ share

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Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models

Targeted syntactic evaluations have demonstrated the ability of language...
06/10/2021 ∙ by Matthew Finlayson, et al. ∙ 0 ∙ share

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The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

We introduce GEM, a living benchmark for natural language Generation (NL...
02/02/2021 ∙ by Sebastian Gehrmann, et al. ∙ 5 ∙ share

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Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task

The quality of machine translation systems has dramatically improved ove...
10/08/2020 ∙ by Thibault Sellam, et al. ∙ 0 ∙ share

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The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models

We present the Language Interpretability Tool (LIT), an open-source plat...
08/12/2020 ∙ by Ian Tenney, et al. ∙ 0 ∙ share

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Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics

De novo therapeutic design is challenged by a vast chemical repertoire a...
05/22/2020 ∙ by Payel Das, et al. ∙ 0 ∙ share

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ToTTo: A Controlled Table-To-Text Generation Dataset

We present ToTTo, an open-domain English table-to-text dataset with over...
04/29/2020 ∙ by Ankur P. Parikh, et al. ∙ 0 ∙ share

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Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias

Common methods for interpreting neural models in natural language proces...
04/26/2020 ∙ by Jesse Vig, et al. ∙ 0 ∙ share

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A Corpus for Detecting High-Context Medical Conditions in Intensive Care Patient Notes Focusing on Frequently Readmitted Patients

A crucial step within secondary analysis of electronic health records (E...
03/06/2020 ∙ by Edward T. Moseley, et al. ∙ 0 ∙ share

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Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages

We introduce three memory-augmented Recurrent Neural Networks (MARNNs) a...
11/08/2019 ∙ by Mirac Suzgun, et al. ∙ 23 ∙ share

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exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformers Models

Large language models can produce powerful contextual representations th...
10/11/2019 ∙ by Benjamin Hoover, et al. ∙ 0 ∙ share

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Encoder-Agnostic Adaptation for Conditional Language Generation

Large pretrained language models have changed the way researchers approa...
08/19/2019 ∙ by Zachary M. Ziegler, et al. ∙ 0 ∙ share

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Visual Interaction with Deep Learning Models through Collaborative Semantic Inference

Automation of tasks can have critical consequences when humans lose agen...
07/24/2019 ∙ by Sebastian Gehrmann, et al. ∙ 14 ∙ share

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Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation

Joint narratives are often used in the context of reconciliation interve...
06/27/2019 ∙ by Massimo Zancanaro, et al. ∙ 0 ∙ share

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GLTR: Statistical Detection and Visualization of Generated Text

The rapid improvement of language models has raised the specter of abuse...
06/10/2019 ∙ by Sebastian Gehrmann, et al. ∙ 0 ∙ share

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LSTM Networks Can Perform Dynamic Counting

In this paper, we systematically assess the ability of standard recurren...
06/09/2019 ∙ by Mirac Suzgun, et al. ∙ 0 ∙ share

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Improving Human Text Comprehension through Semi-Markov CRF-based Neural Section Title Generation

Titles of short sections within long documents support readers by guidin...
04/15/2019 ∙ by Sebastian Gehrmann, et al. ∙ 0 ∙ share

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End-to-End Content and Plan Selection for Data-to-Text Generation

Learning to generate fluent natural language from structured data with n...
10/10/2018 ∙ by Sebastian Gehrmann, et al. ∙ 2 ∙ share

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Very Highly Skilled Individuals Do Not Choke Under Pressure: Evidence from Professional Darts

Understanding and predicting how individuals perform in high-pressure si...
09/20/2018 ∙ by Christian Deutscher, et al. ∙ 0 ∙ share

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Bottom-Up Abstractive Summarization

Neural network-based methods for abstractive summarization produce outpu...
08/31/2018 ∙ by Sebastian Gehrmann, et al. ∙ 0 ∙ share

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Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models

Neural Sequence-to-Sequence models have proven to be accurate and robust...
04/25/2018 ∙ by Hendrik Strobelt, et al. ∙ 0 ∙ share

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Comparing Rule-Based and Deep Learning Models for Patient Phenotyping

Objective: We investigate whether deep learning techniques for natural l...
03/25/2017 ∙ by Sebastian Gehrmann, et al. ∙ 0 ∙ share

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LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks

Recurrent neural networks, and in particular long short-term memory (LST...
06/23/2016 ∙ by Hendrik Strobelt, et al. ∙ 0 ∙ share

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Sebastian Gehrmann

Featured Co-authors

Wei Xu

Pin-Yu Chen

Alexander M. Rush

Franck Dernoncourt

Hanspeter Pfister

Yonatan Belinkov

Tal Linzen

Bhuwan Dhingra

Ondřej Dušek

Payel Das

Antoine Bosselut

Automatic Construction of Evaluation Suites for Natural Language Generation Datasets

Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task

The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics

ToTTo: A Controlled Table-To-Text Generation Dataset

Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias

A Corpus for Detecting High-Context Medical Conditions in Intensive Care Patient Notes Focusing on Frequently Readmitted Patients

Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages

exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformers Models

Encoder-Agnostic Adaptation for Conditional Language Generation

Visual Interaction with Deep Learning Models through Collaborative Semantic Inference

Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation

GLTR: Statistical Detection and Visualization of Generated Text

LSTM Networks Can Perform Dynamic Counting

Improving Human Text Comprehension through Semi-Markov CRF-based Neural Section Title Generation

End-to-End Content and Plan Selection for Data-to-Text Generation

Very Highly Skilled Individuals Do Not Choke Under Pressure: Evidence from Professional Darts

Bottom-Up Abstractive Summarization

Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models

Comparing Rule-Based and Deep Learning Models for Patient Phenotyping

LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks