148 citations · 272 across the 17 of their papers we have counts for
10 papers · 1 filter
To what extent do human explanations of model behavior align with actual model behavior?
Grusha Prasad, Yixin Nie, Mohit Bansal +3
Given the increasingly prominent role NLP models (will) play in our lives, it is important for human expectations of model behavior to align with actual model behavior. Using Natur…
ANLIzing the Adversarial Natural Language Inference Dataset
Adina Williams, Tristan Thrush, Douwe Kiela
We perform an in-depth error analysis of Adversarial NLI (ANLI), a recently introduced large-scale human-and-model-in-the-loop natural language inference dataset collected over mul…
Intrinsic Probing through Dimension Selection
Lucas Torroba Hennigen, Adina Williams, Ryan Cotterell
Most modern NLP systems make use of pre-trained contextual representations that attain astonishingly high performance on a variety of tasks. Such high performance should not be pos…
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Ekaterina Vylomova, Jennifer White, Elizabeth Salesky +25
A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from…
Predicting Declension Class from Form and Meaning
Adina Williams, Tiago Pimentel, Arya D. McCarthy +3
The noun lexica of many natural languages are divided into several declension classes with characteristic morphological properties. Class membership is far from deterministic, but…
Information-Theoretic Probing for Linguistic Structure
Tiago Pimentel, Josef Valvoda, Rowan Hall Maudslay +3
The success of neural networks on a diverse set of NLP tasks has led researchers to question how much these networks actually ``know'' about natural language. Probes are a natural…
A Tale of a Probe and a Parser
Rowan Hall Maudslay, Josef Valvoda, Tiago Pimentel +2
Measuring what linguistic information is encoded in neural models of language has become popular in NLP. Researchers approach this enterprise by training "probes" - supervised mode…
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs
Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin +2
We use large-scale corpora in six different gendered languages, along with tools from NLP and information theory, to test whether there is a relationship between the grammatical ge…
Multi-Dimensional Gender Bias Classification
Emily Dinan, Angela Fan, Ledell Wu +3
Machine learning models are trained to find patterns in data. NLP models can inadvertently learn socially undesirable patterns when training on gender biased text. In this work, we…
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition
Paloma Jeretic, Alex Warstadt, Suvrat Bhooshan +1
Natural language inference (NLI) is an increasingly important task for natural language understanding, which requires one to infer whether a sentence entails another. However, the…