168 citations · 514 across the 32 of their papers we have counts for
4 papers · 2 filters
Specializing Word Embeddings (for Parsing) by Information Bottleneck
Xiang Lisa Li, Jason Eisner
Pre-trained word embeddings like ELMo and BERT contain rich syntactic and semantic information, resulting in state-of-the-art performance on various tasks. We propose a very fast v…
A Generative Model for Punctuation in Dependency Trees
Xiang Lisa Li, Dingquan Wang, Jason Eisner
Treebanks traditionally treat punctuation marks as ordinary words, but linguists have suggested that a tree's "true" punctuation marks are not observed (Nunberg, 1990). These laten…
What Kind of Language Is Hard to Language-Model?
Sabrina J. Mielke, Ryan Cotterell, Kyle Gorman +2
How language-agnostic are current state-of-the-art NLP tools? Are there some types of language that are easier to model with current methods? In prior work (Cotterell et al., 2018)…
Contextualization of Morphological Inflection
Ekaterina Vylomova, Ryan Cotterell, Timothy Baldwin +2
Critical to natural language generation is the production of correctly inflected text. In this paper, we isolate the task of predicting a fully inflected sentence from its partiall…