• Publications
  • Influence
AllenNLP: A Deep Semantic Natural Language Processing Platform
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 novel languageExpand
  • 464
  • 65
  • Open Access
Linguistic Knowledge and Transferability of Contextual Representations
Contextual word representations derived from large-scale neural language models are successful across a diverse set of NLP tasks, suggesting that they encode useful and transferable features ofExpand
  • 171
  • 49
  • Open Access
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets
Several datasets have recently been constructed to expose brittleness in models trained on existing benchmarks. While model performance on these challenge datasets is significantly lower compared toExpand
  • 39
  • 10
  • Open Access
Crowdsourcing Multiple Choice Science Questions
We present a novel method for obtaining high-quality, domain-targeted multiple choice questions from crowd workers. Generating these questions can be difficult without trading away originality,Expand
  • 41
  • 7
  • Open Access
Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning
Machine comprehension of texts longer than a single sentence often requires coreference resolution. However, most current reading comprehension benchmarks do not contain complex coreferentialExpand
  • 29
  • 7
  • Open Access
Barack's Wife Hillary: Using Knowledge-Graphs for Fact-Aware Language Modeling
Modeling human language requires the ability to not only generate fluent text but also encode factual knowledge. However, traditional language models are only capable of remembering facts seen atExpand
  • 48
  • 2
  • Open Access
LSTMs Exploit Linguistic Attributes of Data
While recurrent neural networks have found success in a variety of natural language processing applications, they are general models of sequential data. We investigate how the properties of naturalExpand
  • 11
  • 2
  • Open Access
Evaluating NLP Models via Contrast Sets
Standard test sets for supervised learning evaluate in-distribution generalization. Unfortunately, when a dataset has systematic gaps (e.g., annotation artifacts), these evaluations are misleading: aExpand
  • 31
  • 1
  • Open Access
Discovering Phonesthemes with Sparse Regularization
We introduce a simple method for extracting non-arbitrary form-meaning representations from a collection of semantic vectors. We treat the problem as one of feature selection for a model trained toExpand
  • 5
  • 1
  • Open Access
Augmenting Statistical Machine Translation with Subword Translation of Out-of-Vocabulary Words
Most statistical machine translation systems cannot translate words that are unseen in the training data. However, humans can translate many classes of out-of-vocabulary (OOV) words (e.g., novelExpand
  • 4
  • 1
  • Open Access