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20172024
most citedNeural Wikipedian: Generating Textual Summaries from Knowledge Base Triples

68 citations · 241 across the 19 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.LG2021★ 2 cited

Sampling from Discrete Energy-Based Models with Quality/Efficiency Trade-offs

Bryan Eikema, Germán Kruszewski, Hady Elsahar +1

Energy-Based Models (EBMs) allow for extremely flexible specifications of probability distributions. However, they do not provide a mechanism for obtaining exact samples from these…

cs.LG2021★ 6 cited

Controlling Conditional Language Models without Catastrophic Forgetting

Tomasz Korbak, Hady Elsahar, German Kruszewski +1

Machine learning is shifting towards general-purpose pretrained generative models, trained in a self-supervised manner on large amounts of data, which can then be applied to solve…

cs.CL2021★ 8 cited

Unsupervised and Distributional Detection of Machine-Generated Text

Matthias Gallé, Jos Rozen, Germán Kruszewski +1

The power of natural language generation models has provoked a flurry of interest in automatic methods to detect if a piece of text is human or machine-authored. The problem so far…

cs.LG2021★ 5 cited

Energy-Based Models for Code Generation under Compilability Constraints

Tomasz Korbak, Hady Elsahar, Marc Dymetman +1

Neural language models can be successfully trained on source code, leading to applications such as code completion. However, their versatile autoregressive self-supervision objecti…

cs.CL2021

References in Wikipedia: The Editors' Perspective

Lucie-Aimée Kaffee, Hady Elsahar

References are an essential part of Wikipedia. Each statement in Wikipedia should be referenced. In this paper, we explore the creation and collection of references for new Wikiped…