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Exploring Numeracy in Word Embeddings
In this work, we show that existing embedding models are inadequate at constructing representations that capture salient aspects of mathematical meaning for numbers, which is important for language understanding.
An Empirical Study of Self-Disclosure in Spoken Dialogue Systems
Self-disclosure is a key social strategy employed in conversation to build relations and increase conversational depth.
Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology-Based Representations
We investigate the pertinence of methods from algebraic topology for text data analysis.
How Would You Say It? Eliciting Lexically Diverse Dialogue for Supervised Semantic Parsing
Wang et al. (2015) proposed a method to build semantic parsing datasets by generating canonical utterances using a grammar and having crowdworkers paraphrase them into natural wording.
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