Sebastian Gehrmann

research

∙ 06/29/2023

Benchmarking Large Language Model Capabilities for Conditional Generation

Pre-trained large language models (PLMs) underlie most new developments ...

0 Joshua Maynez, et al. ∙

research

∙ 05/22/2023

SEAHORSE: A Multilingual, Multifaceted Dataset for Summarization Evaluation

Reliable automatic evaluation of summarization systems is challenging du...

0 Elizabeth Clark, et al. ∙

research

∙ 03/30/2023

BloombergGPT: A Large Language Model for Finance

The use of NLP in the realm of financial technology is broad and complex...

0 Shijie Wu, et al. ∙

research

∙ 12/20/2022

Needle in a Haystack: An Analysis of Finding Qualified Workers on MTurk for Summarization

The acquisition of high-quality human annotations through crowdsourcing ...

10 Lining Zhang, et al. ∙

research

∙ 11/16/2022

Towards Computationally Verifiable Semantic Grounding for Language Models

The paper presents an approach to semantic grounding of language models ...

0 Chris Alberti, et al. ∙

research

∙ 11/04/2022

Intriguing Properties of Compression on Multilingual Models

Multilingual models are often particularly dependent on scaling to gener...

1 Kelechi Ogueji, et al. ∙

research

∙ 11/02/2022

Dialect-robust Evaluation of Generated Text

Evaluation metrics that are not robust to dialect variation make it impo...

0 Jiao Sun, et al. ∙

research

∙ 10/31/2022

TaTa: A Multilingual Table-to-Text Dataset for African Languages

Existing data-to-text generation datasets are mostly limited to English....

0 Sebastian Gehrmann, et al. ∙

research

∙ 04/05/2022

PaLM: Scaling Language Modeling with Pathways

Large language models have been shown to achieve remarkable performance ...

6 Aakanksha Chowdhery, et al. ∙

research

∙ 02/14/2022

Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text

Evaluation practices in natural language generation (NLG) have many know...

0 Sebastian Gehrmann, et al. ∙

research

∙ 01/27/2022

Diagnosing AI Explanation Methods with Folk Concepts of Behavior

When explaining AI behavior to humans, how is the communicated informati...

0 Alon Jacovi, et al. ∙

research

∙ 11/11/2021

SynthBio: A Case Study in Human-AI Collaborative Curation of Text Datasets

NLP researchers need more, higher-quality text datasets. Human-labeled d...

0 Ann Yuan, et al. ∙

research

∙ 11/02/2021

LMdiff: A Visual Diff Tool to Compare Language Models

While different language models are ubiquitous in NLP, it is hard to con...

7 Hendrik Strobelt, et al. ∙

research

∙ 10/12/2021

Learning Compact Metrics for MT

Recent developments in machine translation and multilingual text generat...

0 Amy Pu, et al. ∙

research

∙ 08/16/2021

Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cards

Developing documentation guidelines and easy-to-use templates for datase...

0 Angelina McMillan-Major, et al. ∙

research

∙ 06/16/2021

Automatic Construction of Evaluation Suites for Natural Language Generation Datasets

Machine learning approaches applied to NLP are often evaluated by summar...

0 Simon Mille, et al. ∙

research

∙ 06/10/2021

Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models

Targeted syntactic evaluations have demonstrated the ability of language...

0 Matthew Finlayson, et al. ∙

research

∙ 02/02/2021

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

We introduce GEM, a living benchmark for natural language Generation (NL...

5 Sebastian Gehrmann, et al. ∙

research

∙ 10/08/2020

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...

0 Thibault Sellam, et al. ∙

research

∙ 08/12/2020

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

We present the Language Interpretability Tool (LIT), an open-source plat...

0 Ian Tenney, et al. ∙

research

∙ 05/22/2020

Accelerating Antimicrobial Discovery with Controllable Deep Generative Models and Molecular Dynamics

De novo therapeutic design is challenged by a vast chemical repertoire a...

0 Payel Das, et al. ∙

research

∙ 04/29/2020

ToTTo: A Controlled Table-To-Text Generation Dataset

We present ToTTo, an open-domain English table-to-text dataset with over...

0 Ankur P. Parikh, et al. ∙

research

∙ 04/26/2020

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

Common methods for interpreting neural models in natural language proces...

0 Jesse Vig, et al. ∙

research

∙ 03/06/2020

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...

0 Edward T. Moseley, et al. ∙

research

∙ 11/08/2019

Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages

We introduce three memory-augmented Recurrent Neural Networks (MARNNs) a...

23 Mirac Suzgun, et al. ∙

research

∙ 10/11/2019

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

Large language models can produce powerful contextual representations th...

0 Benjamin Hoover, et al. ∙

research

∙ 08/19/2019

Encoder-Agnostic Adaptation for Conditional Language Generation

Large pretrained language models have changed the way researchers approa...

0 Zachary M. Ziegler, et al. ∙

research

∙ 07/24/2019

Visual Interaction with Deep Learning Models through Collaborative Semantic Inference

Automation of tasks can have critical consequences when humans lose agen...

14 Sebastian Gehrmann, et al. ∙

research

∙ 06/27/2019

Evaluating an Automated Mediator for Joint Narratives in a Conflict Situation

Joint narratives are often used in the context of reconciliation interve...

0 Massimo Zancanaro, et al. ∙

research

∙ 06/10/2019

GLTR: Statistical Detection and Visualization of Generated Text

The rapid improvement of language models has raised the specter of abuse...

0 Sebastian Gehrmann, et al. ∙

research

∙ 06/09/2019

LSTM Networks Can Perform Dynamic Counting

In this paper, we systematically assess the ability of standard recurren...

0 Mirac Suzgun, et al. ∙

research

∙ 04/15/2019

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

Titles of short sections within long documents support readers by guidin...

0 Sebastian Gehrmann, et al. ∙

research

∙ 10/10/2018

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

Learning to generate fluent natural language from structured data with n...

2 Sebastian Gehrmann, et al. ∙

research

∙ 09/20/2018

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

Understanding and predicting how individuals perform in high-pressure si...

0 Christian Deutscher, et al. ∙

research

∙ 08/31/2018

Bottom-Up Abstractive Summarization

Neural network-based methods for abstractive summarization produce outpu...

0 Sebastian Gehrmann, et al. ∙

research

∙ 04/25/2018

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

Neural Sequence-to-Sequence models have proven to be accurate and robust...

0 Hendrik Strobelt, et al. ∙

research

∙ 03/25/2017

Comparing Rule-Based and Deep Learning Models for Patient Phenotyping

Objective: We investigate whether deep learning techniques for natural l...

0 Sebastian Gehrmann, et al. ∙

research

∙ 06/23/2016

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...

0 Hendrik Strobelt, et al. ∙

Sebastian Gehrmann

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