Sebastian Gehrmann

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Harvard University

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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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