Sudeep Gandhe


2021

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DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections
Yury Zemlyanskiy | Sudeep Gandhe | Ruining He | Bhargav Kanagal | Anirudh Ravula | Juraj Gottweis | Fei Sha | Ilya Eckstein
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume

This paper explores learning rich self-supervised entity representations from large amounts of associated text. Once pre-trained, these models become applicable to multiple entity-centric tasks such as ranked retrieval, knowledge base completion, question answering, and more. Unlike other methods that harvest self-supervision signals based merely on a local context within a sentence, we radically expand the notion of context to include any available text related to an entity. This enables a new class of powerful, high-capacity representations that can ultimately distill much of the useful information about an entity from multiple text sources, without any human supervision. We present several training strategies that, unlike prior approaches, learn to jointly predict words and entities – strategies we compare experimentally on downstream tasks in the TV-Movies domain, such as MovieLens tag prediction from user reviews and natural language movie search. As evidenced by results, our models match or outperform competitive baselines, sometimes with little or no fine-tuning, and are also able to scale to very large corpora. Finally, we make our datasets and pre-trained models publicly available. This includes Reviews2Movielens, mapping the ~1B word corpus of Amazon movie reviews (He and McAuley, 2016) to MovieLens tags (Harper and Konstan, 2016), as well as Reddit Movie Suggestions with natural language queries and corresponding community recommendations.

2014

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SAWDUST: a Semi-Automated Wizard Dialogue Utterance Selection Tool for domain-independent large-domain dialogue
Sudeep Gandhe | David Traum
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

2013

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Surface Text based Dialogue Models for Virtual Humans
Sudeep Gandhe | David Traum
Proceedings of the SIGDIAL 2013 Conference

2011

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Rapid Development of Advanced Question-Answering Characters by Non-experts
Sudeep Gandhe | Alysa Taylor | Jillian Gerten | David Traum
Proceedings of the SIGDIAL 2011 Conference

2010

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I’ve said it before, and I’ll say it again: An empirical investigation of the upper bound of the selection approach to dialogue
Sudeep Gandhe | David Traum
Proceedings of the SIGDIAL 2010 Conference

2008

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Rapidly Deploying Grammar-Based Speech Applications with Active Learning and Back-off Grammars
Tim Paek | Sudeep Gandhe | Max Chickering
Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue

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Evaluation Understudy for Dialogue Coherence Models
Sudeep Gandhe | David Traum
Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue

2007

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Handling Out-of-Grammar Commands in Mobile Speech Interaction Using Backoff Filler Models
Tim Paek | Sudeep Gandhe | Max Chickering | Yun Cheng Ju
Proceedings of the Workshop on Grammar-Based Approaches to Spoken Language Processing

2005

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Dealing with Doctors: A Virtual Human for Non-team Interaction
David Traum | William Swartout | Jonathan Gratch | Stacy Marsella | Patrick Kenny | Eduard Hovy | Shri Narayanan | Ed Fast | Bilyana Martinovski | Rahul Baghat | Susan Robinson | Andrew Marshall | Dagen Wang | Sudeep Gandhe | Anton Leuski
Proceedings of the 6th SIGdial Workshop on Discourse and Dialogue

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Transonics: A Practical Speech-to-Speech Translator for English-Farsi Medical Dialogs
Robert Belvin | Emil Ettelaie | Sudeep Gandhe | Panayiotis Georgiou | Kevin Knight | Daniel Marcu | Scott Millward | Shrikanth Narayanan | Howard Neely | David Traum
Proceedings of the ACL Interactive Poster and Demonstration Sessions