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20162022
most citedUnderspecification Presents Challenges for Credibility in Modern Machine Learning

430 citations · 494 across the 12 of their papers we have counts for

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27 papers · 1 filter

cs.CL20221 cited

Predicting Long-Term Citations from Short-Term Linguistic Influence

Sandeep Soni, David Bamman, Jacob Eisenstein

A standard measure of the influence of a research paper is the number of times it is cited. However, papers may be cited for many reasons, and citation count offers limited informa…

cs.CL20222 cited

Pre-trained Sentence Embeddings for Implicit Discourse Relation Classification

Murali Raghu Babu Balusu, Yangfeng Ji, Jacob Eisenstein

Implicit discourse relations bind smaller linguistic units into coherent texts. Automatic sense prediction for implicit relations is hard, because it requires understanding the sem…

cs.CL20215 cited

Learning to Look Inside: Augmenting Token-Based Encoders with Character-Level Information

Yuval Pinter, Amanda Stent, Mark Dredze +1

Commonly-used transformer language models depend on a tokenization schema which sets an unchangeable subword vocabulary prior to pre-training, destined to be applied to all downstr…

cs.CL202137 cited

Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer

Iulia Turc, Kenton Lee, Jacob Eisenstein +2

Despite their success, large pre-trained multilingual models have not completely alleviated the need for labeled data, which is cumbersome to collect for all target languages. Zero…

cs.CL2021

Abolitionist Networks: Modeling Language Change in Nineteenth-Century Activist Newspapers

Sandeep Soni, Lauren Klein, Jacob Eisenstein

The abolitionist movement of the nineteenth-century United States remains among the most significant social and political movements in US history. Abolitionist newspapers played a…

cs.CL2020

Will it Unblend?

Yuval Pinter, Cassandra L. Jacobs, Jacob Eisenstein

Natural language processing systems often struggle with out-of-vocabulary (OOV) terms, which do not appear in training data. Blends, such as "innoventor", are one particularly chal…