8 citations · 12 across the 6 of their papers we have counts for
19 papers
Low-Rank Softmax Can Have Unargmaxable Classes in Theory but Rarely in Practice
Andreas Grivas, Nikolay Bogoychev, Adam Lopez
Classifiers in natural language processing (NLP) often have a large number of output classes. For example, neural language models (LMs) and machine translation (MT) models both pre…
Intrinsic Bias Metrics Do Not Correlate with Application Bias
Seraphina Goldfarb-Tarrant, Rebecca Marchant, Ricardo Muñoz Sanchez +2
Natural Language Processing (NLP) systems learn harmful societal biases that cause them to amplify inequality as they are deployed in more and more situations. To guide efforts at…
LemMED: Fast and Effective Neural Morphological Analysis with Short Context Windows
Aibek Makazhanov, Sharon Goldwater, Adam Lopez
We present LemMED, a character-level encoder-decoder for contextual morphological analysis (combined lemmatization and tagging). LemMED extends and is named after two other attenti…
LSTMs Compose (and Learn) Bottom-Up
Naomi Saphra, Adam Lopez
Recent work in NLP shows that LSTM language models capture hierarchical structure in language data. In contrast to existing work, we consider the \textit{learning} process that lea…
Inflecting when there's no majority: Limitations of encoder-decoder neural networks as cognitive models for German plurals
Kate McCurdy, Sharon Goldwater, Adam Lopez
Can artificial neural networks learn to represent inflectional morphology and generalize to new words as human speakers do? Kirov and Cotterell (2018) argue that the answer is yes:…
Word Interdependence Exposes How LSTMs Compose Representations
Naomi Saphra, Adam Lopez
Recent work in NLP shows that LSTM language models capture compositional structure in language data. For a closer look at how these representations are composed hierarchically, we…