513 citations · 583 across the 6 of their papers we have counts for
4 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…
Ontology Alignment in the Biomedical Domain Using Entity Definitions and Context
Lucy Lu Wang, Chandra Bhagavatula, Mark Neumann +3
Ontology alignment is the task of identifying semantically equivalent entities from two given ontologies. Different ontologies have different representations of the same entity, re…
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…