Joyce Chai

Also published as: Joyce Yue Chai, Joyce Y. Chai


2020

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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Dan Jurafsky | Joyce Chai | Natalie Schluter | Joel Tetreault
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

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Experience Grounds Language
Yonatan Bisk | Ari Holtzman | Jesse Thomason | Jacob Andreas | Yoshua Bengio | Joyce Chai | Mirella Lapata | Angeliki Lazaridou | Jonathan May | Aleksandr Nisnevich | Nicolas Pinto | Joseph Turian
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Language understanding research is held back by a failure to relate language to the physical world it describes and to the social interactions it facilitates. Despite the incredible effectiveness of language processing models to tackle tasks after being trained on text alone, successful linguistic communication relies on a shared experience of the world. It is this shared experience that makes utterances meaningful. Natural language processing is a diverse field, and progress throughout its development has come from new representational theories, modeling techniques, data collection paradigms, and tasks. We posit that the present success of representation learning approaches trained on large, text-only corpora requires the parallel tradition of research on the broader physical and social context of language to address the deeper questions of communication.

2018

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Commonsense Justification for Action Explanation
Shaohua Yang | Qiaozi Gao | Sari Sadiya | Joyce Chai
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

To enable collaboration and communication between humans and agents, this paper investigates learning to acquire commonsense evidence for action justification. In particular, we have developed an approach based on the generative Conditional Variational Autoencoder(CVAE) that models object relations/attributes of the world as latent variables and jointly learns a performer that predicts actions and an explainer that gathers commonsense evidence to justify the action. Our empirical results have shown that, compared to a typical attention-based model, CVAE achieves significantly higher performance in both action prediction and justification. A human subject study further shows that the commonsense evidence gathered by CVAE can be communicated to humans to achieve a significantly higher common ground between humans and agents.

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What Action Causes This? Towards Naive Physical Action-Effect Prediction
Qiaozi Gao | Shaohua Yang | Joyce Chai | Lucy Vanderwende
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Despite recent advances in knowledge representation, automated reasoning, and machine learning, artificial agents still lack the ability to understand basic action-effect relations regarding the physical world, for example, the action of cutting a cucumber most likely leads to the state where the cucumber is broken apart into smaller pieces. If artificial agents (e.g., robots) ever become our partners in joint tasks, it is critical to empower them with such action-effect understanding so that they can reason about the state of the world and plan for actions. Towards this goal, this paper introduces a new task on naive physical action-effect prediction, which addresses the relations between concrete actions (expressed in the form of verb-noun pairs) and their effects on the state of the physical world as depicted by images. We collected a dataset for this task and developed an approach that harnesses web image data through distant supervision to facilitate learning for action-effect prediction. Our empirical results have shown that web data can be used to complement a small number of seed examples (e.g., three examples for each action) for model learning. This opens up possibilities for agents to learn physical action-effect relations for tasks at hand through communication with humans with a few examples.

2017

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Interactive Learning of Grounded Verb Semantics towards Human-Robot Communication
Lanbo She | Joyce Chai
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

To enable human-robot communication and collaboration, previous works represent grounded verb semantics as the potential change of state to the physical world caused by these verbs. Grounded verb semantics are acquired mainly based on the parallel data of the use of a verb phrase and its corresponding sequences of primitive actions demonstrated by humans. The rich interaction between teachers and students that is considered important in learning new skills has not yet been explored. To address this limitation, this paper presents a new interactive learning approach that allows robots to proactively engage in interaction with human partners by asking good questions to learn models for grounded verb semantics. The proposed approach uses reinforcement learning to allow the robot to acquire an optimal policy for its question-asking behaviors by maximizing the long-term reward. Our empirical results have shown that the interactive learning approach leads to more reliable models for grounded verb semantics, especially in the noisy environment which is full of uncertainties. Compared to previous work, the models acquired from interactive learning result in a 48% to 145% performance gain when applied in new situations.

2016

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Jointly Learning Grounded Task Structures from Language Instruction and Visual Demonstration
Changsong Liu | Shaohua Yang | Sari Saba-Sadiya | Nishant Shukla | Yunzhong He | Song-Chun Zhu | Joyce Chai
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

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Grounded Semantic Role Labeling
Shaohua Yang | Qiaozi Gao | Changsong Liu | Caiming Xiong | Song-Chun Zhu | Joyce Y. Chai
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Incremental Acquisition of Verb Hypothesis Space towards Physical World Interaction
Lanbo She | Joyce Chai
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Physical Causality of Action Verbs in Grounded Language Understanding
Qiaozi Gao | Malcolm Doering | Shaohua Yang | Joyce Chai
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

2015

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Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Rada Mihalcea | Joyce Chai | Anoop Sarkar
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2014

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Probabilistic Labeling for Efficient Referential Grounding based on Collaborative Discourse
Changsong Liu | Lanbo She | Rui Fang | Joyce Y. Chai
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Back to the Blocks World: Learning New Actions through Situated Human-Robot Dialogue
Lanbo She | Shaohua Yang | Yu Cheng | Yunyi Jia | Joyce Chai | Ning Xi
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

2013

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Towards Situated Dialogue: Revisiting Referring Expression Generation
Rui Fang | Changsong Liu | Lanbo She | Joyce Y. Chai
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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Modeling Collaborative Referring for Situated Referential Grounding
Changsong Liu | Rui Fang | Lanbo She | Joyce Chai
Proceedings of the SIGDIAL 2013 Conference

2012

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Semantic Role Labeling of Implicit Arguments for Nominal Predicates
Matthew Gerber | Joyce Y. Chai
Computational Linguistics, Volume 38, Issue 4 - December 2012

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Autonomous Self-Assessment of Autocorrections: Exploring Text Message Dialogues
Tyler Baldwin | Joyce Chai
Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Towards Mediating Shared Perceptual Basis in Situated Dialogue
Changsong Liu | Rui Fang | Joyce Chai
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2011

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A Joint Model of Implicit Arguments for Nominal Predicates
Matthew Gerber | Joyce Chai | Robert Bart
Proceedings of the ACL 2011 Workshop on Relational Models of Semantics

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Proceedings of the SIGDIAL 2011 Conference
Joyce Y. Chai | Johanna D. Moore | Rebecca J. Passonneau | David R. Traum
Proceedings of the SIGDIAL 2011 Conference

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Beyond Normalization: Pragmatics of Word Form in Text Messages
Tyler Baldwin | Joyce Chai
Proceedings of 5th International Joint Conference on Natural Language Processing

2010

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Hand Gestures in Disambiguating Types of You Expressions in Multiparty Meetings
Tyler Baldwin | Joyce Chai | Katrin Kirchhoff
Proceedings of the SIGDIAL 2010 Conference

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Beyond NomBank: A Study of Implicit Arguments for Nominal Predicates
Matthew Gerber | Joyce Chai
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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Fusing Eye Gaze with Speech Recognition Hypotheses to Resolve Exophoric References in Situated Dialogue
Zahar Prasov | Joyce Y. Chai
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

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Towards Conversation Entailment: An Empirical Investigation
Chen Zhang | Joyce Chai
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

2009

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The Role of Interactivity in Human-Machine Conversation for Automatic Word Acquisition
Shaolin Qu | Joyce Chai
Proceedings of the SIGDIAL 2009 Conference

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What do We Know about Conversation Participants: Experiments on Conversation Entailment
Chen Zhang | Joyce Chai
Proceedings of the SIGDIAL 2009 Conference

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The Role of Implicit Argumentation in Nominal SRL
Matthew Gerber | Joyce Chai | Adam Meyers
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics

2008

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Incorporating Temporal and Semantic Information with Eye Gaze for Automatic Word Acquisition in Multimodal Conversational Systems
Shaolin Qu | Joyce Chai
Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing

2007

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An Exploration of Eye Gaze in Spoken Language Processing for Multimodal Conversational Interfaces
Shaolin Qu | Joyce Chai
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference

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Automated Vocabulary Acquisition and Interpretation in Multimodal Conversational Systems
Yi Liu | Joyce Chai | Rong Jin
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics

2006

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Towards Conversational QA: Automatic Identification of Problematic Situations and User Intent
Joyce Y. Chai | Chen Zhang | Tyler Baldwin
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

2005

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A Salience Driven Approach to Robust Input Interpretation in Multimodal Conversational Systems
Joyce Y. Chai | Shaolin Qu
Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing

2004

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Optimization in Multimodal Interpretation
Joyce Y. Chai | Pengyu Hong | Michelle X. Zhou | Zahar Prasov
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

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Performance Evaluation and Error Analysis for Multimodal Reference Resolution in a Conversation System
Joyce Y. Chai | Zahar Prasov | Pengyu Hong
Proceedings of HLT-NAACL 2004: Short Papers

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Discourse Structure for Context Question Answering
Joyce Y. Chai | Rong Jin
Proceedings of the Workshop on Pragmatics of Question Answering at HLT-NAACL 2004

2003

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Combining Semantic and Temporal Constraints for Multimodal Integration in Conversation Systems
Joyce Y. Chai | Pengyu Hong | Michelle X. Zhou
Proceedings of the HLT-NAACL 2003 Workshop on Research Directions in Dialogue Processing

2002

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Semantics-based Representation for Multimodal Interpretation in Conversational Systems
Joyce Chai
COLING 2002: The 19th International Conference on Computational Linguistics

2001

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A Conversational Interface for Online Shopping
Joyce Chai | Veronika Horvath | Nanda Kambhatla | Nicolas Nicolov | Margo Stys-Budzikowska
Proceedings of the First International Conference on Human Language Technology Research

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Conversational Sales Assistant for Online Shopping
Margo Budzikowska | Joyce Chai | Sunil Govindappa | Veronika Horvath | Nanda Kambhatla | Nicolas Nicolov | Wlodek Zadrozny
Proceedings of the First International Conference on Human Language Technology Research

2000

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Evaluation of a Generic Lexical Semantic Resource in Information Extraction
Joyce Yue Chai
Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00)

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Dynamic User Level and Utility Measurement for Adaptive Dialog in a Help-Desk System
Preetam Maloor | Joyce Chai
1st SIGdial Workshop on Discourse and Dialogue

1997

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Corpus Based Statistical Generalization Tree in Rule Optimization
Joyce Yue Chai | Alan W. Biermann
Fifth Workshop on Very Large Corpora

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The Use of Lexical Semantics in Information Extraction
Joyce Yue Chai | Alan W. Biermann
Automatic Information Extraction and Building of Lexical Semantic Resources for NLP Applications

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A Trainable Message Understanding System
Amit Bagga | Joyce Yue Chai
CoNLL97: Computational Natural Language Learning

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Duke’s Trainable Information and Meaning Extraction System (Duke TIMES)
Amit Bagga | Joyce Yue Chai
Fifth Conference on Applied Natural Language Processing: Descriptions of System Demonstrations and Videos