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09/05/2023
Substitution-based Semantic Change Detection using Contextual Embeddings
Measuring semantic change has thus far remained a task where methods usi...
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05/10/2022
Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words
Cosine similarity of contextual embeddings is used in many NLP tasks (e....
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04/26/2022
Modular Domain Adaptation
Off-the-shelf models are widely used by computational social science res...
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01/25/2022
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection
Language models increasingly rely on massive web dumps for diverse text ...
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10/01/2021
Expected Validation Performance and Estimation of a Random Variable's Maximum
Research in NLP is often supported by experimental results, and improved...
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06/29/2021
The Values Encoded in Machine Learning Research
Machine learning (ML) currently exerts an outsized influence on the worl...
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10/28/2020
DeSMOG: Detecting Stance in Media On Global Warming
Citing opinions is a powerful yet understudied strategy in argumentation...
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10/24/2020
Causal Effects of Linguistic Properties
We consider the problem of estimating the causal effects of linguistic p...
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10/13/2020
With Little Power Comes Great Responsibility
Despite its importance to experimental design, statistical power (the pr...
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01/02/2020
On Consequentialism and Fairness
Recent work on fairness in machine learning has primarily emphasized how...
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09/06/2019
Show Your Work: Improved Reporting of Experimental Results
Research in natural language processing proceeds, in part, by demonstrat...
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06/05/2019
Variational Pretraining for Semi-supervised Text Classification
We introduce VAMPIRE, a lightweight pretraining framework for effective ...
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11/06/2018
Deep Weighted Averaging Classifiers
Recent advances in deep learning have achieved impressive gains in class...
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05/25/2017
A Neural Framework for Generalized Topic Models
Topic models for text corpora comprise a popular family of methods that ...
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04/25/2017