16 citations · 51 across the 13 of their papers we have counts for
5 papers · 2 filters
Dissecting Contextual Word Embeddings: Architecture and Representation
Matthew E. Peters, Mark Neumann, Luke Zettlemoyer +1
Contextual word representations derived from pre-trained bidirectional language models (biLMs) have recently been shown to provide significant improvements to the state of the art…
Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples
Vidur Joshi, Matthew Peters, Mark Hopkins
We revisit domain adaptation for parsers in the neural era. First we show that recent advances in word representations greatly diminish the need for domain adaptation when the targ…
Construction of the Literature Graph in Semantic Scholar
Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula +20
We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery. The resulting…
Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer +4
We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses var…
AllenNLP: A Deep Semantic Natural Language Processing Platform
Matt Gardner, Joel Grus, Mark Neumann +6
This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. AllenNLP is designed to support researchers who want to build nov…