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Found 7 papers, 1 papers with code
The OSU/Facebook Realizer for SRST 2019: Seq2Seq Inflection and Serialized Tree2Tree Linearization
We describe our exploratory system for the shallow surface realization task, which combines morphological inflection using character sequence-to-sequence models with a baseline linearizer that implements a tree-to-tree model using sequence-to-sequence models on serialized trees.
The OSU Realizer for SRST `18: Neural Sequence-to-Sequence Inflection and Incremental Locality-Based Linearization
Surface realization is a nontrivial task as it involves taking structured data and producing grammatically and semantically correct utterances.
Using Paraphrasing and Memory-Augmented Models to Combat Data Sparsity in Question Interpretation with a Virtual Patient Dialogue System
When interpreting questions in a virtual patient dialogue system one must inevitably tackle the challenge of a long tail of relatively infrequently asked questions.
Breaking NLP: Using Morphosyntax, Semantics, Pragmatics and World Knowledge to Fool Sentiment Analysis Systems
This paper describes our {``}breaker{''} submission to the 2017 EMNLP {``}Build It Break It{''} shared task on sentiment analysis.
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