Mrinmaya Sachan

A metaphor is a figure of speech that refers to one concept in terms of another, as in “He is such a sweet person”. Expand

In recent years, social networking sites have not only enabled people to connect with each other using social links but have also allowed them to share, communicate and interact over diverse geographical regions. Expand

We present a unified max-margin framework that learns to find these hidden structures (given a corpus of question-answer pairs), and uses what it learns to answer machine comprehension questions on novel texts. Expand

We propose a simple modification to existing neural machine translation (NMT) models that enables using a single universal model to translate between multiple languages while allowing for language specific parameterization, and that can also be used for domain adaptation. Expand

We train a bidirectional language model (BiLM) on unlabeled text data to improve the performance of NER models. Expand

We propose an approach using the Abstract Meaning Representation (AMR) formalism for the task of machine comprehension. Expand

In this paper, we address the problem of discovering topically meaningful, yet compact (densely connected) communities in a social network. Expand

We propose a self-training method for jointly learning to ask as well as answer questions, leveraging unlabeled text along with labeled question answer pairs for learning. Expand

We study the problem of automatically building hypernym taxonomies from textual and visual data and propose a probabilistic model based on distributed representations of images and words. Expand

We present a novel approach to modelling distributional semantics that represents meaning as distributions over relations in syntactic neighborhoods. Expand