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Topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. Meanwhile, massive collections of… (More)
- John Lee, Jason Naradowsky, David A. Smith
- ACL
- 2011
Most previous studies of morphological disambiguation and dependency parsing have been pursued independently. Morphological taggers operate on n-grams and do not take into account syntactic… (More)
- Jason Naradowsky, Kristina Toutanova
- ACL
- 2011
This paper describes an unsupervised dynamic graphical model for morphological segmentation and bilingual morpheme alignment for statistical machine translation. The model extends Hidden Semi-Markov… (More)
- James Goodman, Andreas Vlachos, Jason Naradowsky
- ACL 2016
- 2016
Semantic parsers map natural language statements into meaning representations, and must abstract over syntactic phenomena, resolve anaphora, and identify word senses to eliminate ambiguous… (More)
- Adam Poliak, Jason Naradowsky, Aparajita Haldar, Rachel Rudinger, Benjamin Van Durme
- *SEM@NAACL-HLT
- 2018
We propose a hypothesis only baseline for diagnosing Natural Language Inference (NLI). Especially when an NLI dataset assumes inference is occurring based purely on the relationship between a context… (More)
- Jason Naradowsky, Sebastian Riedel, David A. Smith
- EMNLP-CoNLL
- 2012
Many NLP tasks make predictions that are inherently coupled to syntactic relations, but for many languages the resources required to provide such syntactic annotations are unavailable. For others it… (More)
- Rachel Rudinger, Jason Naradowsky, Brian Leonard, Benjamin Van Durme
- NAACL-HLT
- 2018
We present an empirical study of gender bias in coreference resolution systems. We first introduce a novel, Winograd schema-style set of minimal pair sentences that differ only by pronoun gender.… (More)
- James Goodman, Andreas Vlachos, Jason Naradowsky
- SemEval@NAACL-HLT
- 2016
We develop a novel transition-based parsing algorithm for the abstract meaning representation parsing task using exact imitation learning, in which the parser learns a statistical model by imitating… (More)
- Daniela Gerz, Ivan Vulic, Edoardo Maria Ponti, Jason Naradowsky, Roi Reichart, Anna Korhonen
- Transactions of the Association of Computational…
- 2018
Neural architectures are prominent in the construction of language models (LMs). However, word-level prediction is typically agnostic of subword-level information (characters and character sequences)… (More)
Tensor and matrix factorization methods have attracted a lot of attention recently thanks to their successful applications to information extraction, knowledge base population, lexical semantics and… (More)