Publications
- Evaluating Representativeness in PDF Malware Datasets: A Comparative Study and a New Dataset.
In the IEEE International Conference on Big Data (BigData), December 2023. Ran Liu, Robert Joyce, Cynthia Matuszek, Charles Nicholas. - A Collaborative Building Task in VR vs. Reality.5,7
In the 18th International Symposium on Experimental Robotics (ISER 2023), November 2023. Padraig Higgins, Ryan Barron, Stephanie Lukin, Don Engel, and Cynthia Matuszek. - Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition.5,7
In the 16th ACM Workshop on Artificial Intelligence and Security (AISec), November 2023. Luke E. Richards, Edward Raff, Cynthia Matuszek. - Voice in the Machine: Ethical Considerations for Language-Capable Robots.5,7
In Communications of the ACM (CACM) 66, 8 (August 2023), 20–23, August 2023. Tom Williams, Cynthia Matuszek, Kristiina Jokinen, Raj Korpan, James Pustejovsky, Brian Scassellati. - Machine Learning Security as a Source of Unfairness in Human-Robot Interaction.5,7
In Proceedings of the ACM/IEEE Human-Robot Interaction Conference (HRI): Workshop on Inclusive HRI II: Equity and Diversity in Design, Application, Methods, and Community (DEI HRI), Stockholm, Sweden, March 2023. Luke E. Richards and Cynthia Matuszek. - Lessons From A Small-Scale Robot Joining Experiment in VR.5
In Proceedings of the ACM/IEEE Human-Robot Interaction Conference (HRI): 6th Int'l Workshop on Virtual, Augmented, and Mixed-Reality for Human-Robot Interactions (VAM-HRI), Stockholm, Sweden, March 2023. Padraig Higgins, Ryan Barron, and Cynthia Matuszek. - Augmenting Simulation Data with Sensor Effects for Improved Domain Transfer.3-6
In the 10th International Workshop on Assistive Computer Vision and Robotic at ECCV (ACVR@ECCV), virtual, October 2022. Adam J. Berlier, Anjali Bhatt, and Cynthia Matuszek. - Head Pose for Object Deixis in VR-Based Human-Robot Interaction.4-5
In 31st IEEE International Conference on Robot & Human Interactive Communication (Ro-Man), Naples, Italy, August 2022. Padraig Higgins, Ryan Barron, and Cynthia Matuszek. - Head Pose as a Proxy for Gaze in Virtual Reality.4-5
In Proceedings of the ACM/IEEE Human-Robot Interaction Conference (HRI): 5th Int'l Workshop on Virtual, Augmented, and Mixed-Reality for Human-Robot Interactions (VAM-HRI), virtual, March 2022. Padraig Higgins, Ryan Barron, and Cynthia Matuszek. - Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech.3-6
In Conference on the Advancement of Artificial Intelligence (AAAI), Vancouver, February 2022.
Gaoussou Youssouf Kebe, Luke E. Richards, Edward Raff, Francis Ferraro, Cynthia Matuszek. - A Spoken Language Dataset of Descriptions for Speech-Based Grounded Language Learning.3-6
In Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, virtual, December 2021.
Gaoussou Youssouf Kébé, Padraig Higgins, Patrick Jenkins, Kasra Darvish, Rishabh Sachdeva, Ryan Barron, John Winder, Don Engel, Edward Raff, Francis Ferraro, Cynthia Matuszek. - Adversarial Transfer Attacks with Unknown Data and Class Overlap.
In the 14th ACM Workshop on Artificial Intelligence and Security (AISec), virtual, November 2021.
Luke E. Richards, André Nguyen, Ryan Capps, Steven Forsythe, Cynthia Matuszek, Edward Raff. - Neural Variational Learning for Grounded Language Acquisition.1,3,4,5
In IEEE International Conference on Robot & Human Interactive Communication (Ro-Man), virtual, August 2021.
Nisha Pillai, Cynthia Matuszek, Francis Ferraro. - Towards Making Virtual Human-Robot Interaction a Reality.4,5
In Proceedings of the ACM/IEEE Human-Robot Interaction Conference (HRI): 4th Int'l Workshop on Virtual, Augmented, and Mixed-Reality for Human-Robot Interactions (VAM-HRI), virtual, March 2021. Padraig Higgins, Gaoussou Youssouf Kebe, Kasra Darvish, Don Engel, Francis Ferraro, and Cynthia Matuszek. - Practical Cross-Modal Manifold Alignment for Robotic Grounded Language Learning.3,4,5
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, (pp. 1613-1622), virtual, June 2021. Andre T. Nguyen, Luke E. Richards, Gaoussou Youssouf Kebe, Edward Raff, Kasra Darvish, Francis Ferraro, and Cynthia Matuszek. - Measuring Perceptual and Linguistic Complexity in Multilingual Grounded Language Data.1,4,5
In 34th Conference of the Florida Artificial Intelligence Research Society (FLAIRS), virtual, May 2021. Nisha Pillai, Francis Ferraro, and Cynthia Matuszek. - Sampling Approach Matters: Active Learning for Robotic Language Acquisition.1,3,4,5
In Proceedings of the IEEE International Conference on BigData (IEEE BigData), special session on machine learning in big data, virtual, December 2020.
Nisha Pillai, Edward Raff, Francis Ferraro, Cynthia Matuszek. - Learning Object Attributes with Category-Free Grounded Language from Deep Featurization.1,2
In Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 8400-8407, virtual, October 2020. Luke E. Richards, Kasra Darvish, Cynthia Matuszek. - Planning with Abstract Learned Models While Learning Transferable Subtasks.2,3
In the 34th Conference on Artificial Intelligence (AAAI), February 2020.
John Winder, Stephanie Milani, Matthew Landen, Erebus Oh, Shane Parr, Shawn Squire, Marie desJardins, and Cynthia Matuszek. - A Manifold Alignment Approach to Grounded Language Learning.1,2 [poster]
In the 8th Northeast Robotics Colloquium, Philadelphia, October 2019.
Luke E. Richards, André T. Nguyen, Kasra Darvish, Edward Raff, Cynthia Matuszek. - Building Language-Agnostic Grounded Language Learning Systems.1
In 28th IEEE International Conference on Robot & Human Interactive Communication (Ro-Man), New Delhi, India, October 2019.
Caroline Kery, Nisha Pillai, Cynthia Matuszek, Francis Ferraro. - Learning from Human-Robot Interactions in Modeled Scenes. [short paper]
In ACM SIGGraph 2019, Los Angeles, California, July 2019.
Mark Murnane, Max Breitmeyer, Francis Ferraro, Cynthia Matuszek, Don Engel. - Learning to Understand Non-Categorical Physical Language for Human Robot Interactions.1
In Robotics: Science and Systems (R:SS) Workshop on AI and Its Alternatives in Assistive and Collaboration (RSS:AI+ACR), 2019.
Luke E. Richards and Cynthia Matuszek. - Deep Learning for Category-Free Grounded Language Acquisition.1
In NAACL Workshop on Spatial Language Understanding & Grounded Communication for Robotics (NAACL-SpLU-RoboNLP), Minneapolis, Minnesota, June 2019. Nisha Pillai, Cynthia Matuszek, Francis Ferraro. - ¿Es un plátano? Exploring the Application of a Physically Grounded Language Acquisition System to Spanish.1
In NAACL Workshop on Spatial Language Understanding & Grounded Communication for Robotics (NAACL-SpLU-RoboNLP), Minneapolis, Minnesota, June 2019.
Caroline Kery, Francis Ferraro, Cynthia Matuszek. - Inferring Robot Morphology from Observation of Unscripted Movement.
In the 2019 IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.
Neil R. Bell, Brian Seipp, J. Tim Oates, Cynthia Matuszek. - Virtual Reality and Photogrammetry for Improved Reproducibility of Human-Robot Interaction Studies. [poster]
In the IEEE Conference on Virtual Reality (VR), Osaka, Japan, March 2019.
Mark Murnane, Max Breitmeyer, Cynthia Matuszek, Don Engel. - Grounded Language Learning: Where Robotics and NLP Meet.1 [early career spotlight]
In the 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, 2018.
Cynthia Matuszek. - Optimal Semantic Distance for Negative Example Selection in Grounded Language Acquisition.1 [short paper]
In Robotics: Science and Systems (R:SS) Workshop on Models and Representations for Natural Human-Robot Communication, 2018.
Nisha Pillai, Francis Ferraro, and Cynthia Matuszek. - Unsupervised Selection of Negative Examples for Grounded Language Learning.1
In the 32nd Conference on Artificial Intelligence (AAAI), February 2018.
Nisha Pillai and Cynthia Matuszek. - Identifying Negative Exemplars in Grounded Language Data Sets.
In Robotics: Science and Systems (R:SS) Workshop on Spatial-Semantic Representations in Robotics, 2017.
Nisha Pillai and Cynthia Matuszek. - Discovering Morphology from Action. [short paper]
In Robotics: Science and Systems (R:SS) Workshop on Heterogeneity and Diversity for Resilience in Multi-Robot Systems, 2017.
Neil R. Bell, J. Tim Oates, Cynthia Matuszek. - Using Language Groundings for Context-Sensitive Text Prediction. [poster]
In EMNLP Workshop on Uphill Battles in Language Processing: Scaling Early Achievements to Robust Methods, 2016.
Tim Lewis, Amy Hurst, Matthew E. Taylor, Cynthia Matuszek. - Semantic Knowledge and Privacy in the Physical Web.
In Workshop on Society, Privacy and the Semantic Web - Policy and Technology, co-located with 15th International Semantic Web Conference CEUR Workshop Proceedings, vol. 1750, 2016.
Prajit Das, Abhay Kashyap, Gurpreet Singh, Cynthia Matuszek, Tim Finin, Anupam Joshi. - Improving Grounded Language Acquisition Efficiency Using Interactive Labeling.
In Robotics: Science and Systems (R:SS) Workshop on Model Learning for Human-Robot Communication, 2016.
Nisha Pillai and Cynthia Matuszek. - On the Ability to Provide Demonstrations on a UAS: Observing 90 Untrained Participants Abusing a Flying Robot.
In the AAAI Fall Symposium on Artificial Intelligence and Human-Robot Interaction AI-HRI, 2015.
Scott, M., Peng, B., Chili, M., Nigam, T., Pascual, F., Matuszek, C., and Taylor, M.E. - Unequal Representation and Gender Stereotypes in Image Search Results for Occupations. [best paper]
In the ACM CHI Conference on Human Factors in Computing Systems, Seoul, Korea, April 2015.
Matthew Kay, Cynthia Matuszek, Sean Munson. - Learning from Unscripted Deictic Gesture and Language for Human-Robot Interactions.
In 28th Conference on Artificial Intelligence (AAAI), Québec City, Canada, July 2014.
Cynthia Matuszek, Liefeng Bo, Luke Zettlemoyer, Dieter Fox. - Combining World and Interaction Models for Human-Robot Collaborations.
In AAAI 2013 Workshop on Intelligent Robotic Systems, Bellevue, WA, July 2013.
Cynthia Matuszek*, Andrzej Pronobis*, Luke Zettlemoyer, Dieter Fox. (* equal contributions) - A Joint Model of Language and Perception for Grounded Attribute Learning.
In 2012 International Conference on Machine Learning (ICML), Edinburgh, Scotland, June 2012.
Cynthia Matuszek*, Nicholas FitzGerald*, Liefeng Bo, Luke Zettlemoyer, Dieter Fox. (* equal contributions)
- Learning to Parse Natural Language Commands to a Robot Control System.
In 2012 International Symposium on Experimental Robotics (ISER), Québec City, Canada, June 2012.
Cynthia Matuszek, Evan Herbst, Luke Zettlemoyer, Dieter Fox.
- Interactive Learning and its Role in Pervasive Robotics.
In ICRA Workshop on The Future of HRI, St. Paul, MN, May 2012.
Cynthia Matuszek, Nicholas FitzGerald, Evan Herbst, Dieter Fox, Luke Zettlemoyer. - Gambit: A Robust Chess-Playing Robotic System.
In the 2011 IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, May 2011.
Cynthia Matuszek, Brian Mayton, Roberto Aimi, Marc Peter Deisenroth, Liefeng Bo, Robert Chu, Mike Kung, Louis LeGrand, Joshua R. Smith, Dieter Fox.
- Following Directions Using Statistical Machine Translation.
In 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Osaka, Japan, March 2010.
Cynthia Matuszek, Dieter Fox, Karl Koscher.
(A supplemental discussion of the of the search metric proposed in this paper.) - A Spotlight on Security and Privacy Risks with Future Household Robots: Attacks and Lessons.
In 11th International Conference on Ubiquitous Computing (UbiComp), Orlando, FL, October 2009.
Tamara Denning, Cynthia Matuszek, Karl Koscher, Joshua R. Smith, Tadayoshi Kohno. - Autonomous Classification of Knowledge into an Ontology.
In 20th International FLAIRS Conference, Key West, FL, May 2007.
Matthew E. Taylor, Cynthia Matuszek, Bryan Klimt, Michael Witbrock. - Guiding Inference with Policy Search Reinforcement Learning.
In 20th International FLAIRS Conference, Key West, FL, May 2007.
Matthew E. Taylor, Cynthia Matuszek, P. Reagan Smith, Michael Witbrock. - Automated Population of Cyc: Extracting Information about Named-entities from the Web.
In 19th International FLAIRS Conference, pp. 153-158, Melbourne Beach, FL, May 2006.
Purvesh Shah, David Schneider, Cynthia Matuszek, Robert C. Kahlert, Bjørn Aldag, David Baxter, John Cabral, Michael Witbrock, Jon Curtis. - An Introduction to the Syntax and Content of Cyc. In
In 2006 AAAI Spring Symposium on Formalizing and Compiling Background Knowledge and Its Applications to Knowledge Representation and Question Answering, Stanford, CA, March 2006.
Cynthia Matuszek, John Cabral, Michael Witbrock, John DeOliveira. - Converting Semantic Meta-Knowledge into Inductive Bias.
In 15th International Conference on Inductive Logic Programming (ILP), Bonn, Germany, August 2005.
John Cabral, Robert C. Kahlert, Cynthia Matuszek, Michael Witbrock, Brett Summers. - Searching for Common Sense: Populating Cyc from the Web.
In 20th National Conference on Artificial Intelligence (AAAI), Pittsburgh, Pennsylvania, July 2005.
Cynthia Matuszek, Michael Witbrock, Robert C. Kahlert, John Cabral, David Schneider, Purvesh Shah, Douglas Lenat.
Note: This paper is occasionally mis-attributed to "Cynthia Matuszek Michael". - A Knowledge-Based Approach to Network Security: Applying Cyc in the Domain of Network Risk Assessment.
In 17th Innovative Applications of Artificial Intelligence Conference (IAAI), Pittsburgh, Pennsylvania, July 2005.
Blake Shepard, Cynthia Matuszek, C. Bruce Fraser, William Wechtenhiser, David Crabbe, Zelal Güngördü, John Jantos, Todd Hughes, Larry Lefkowitz, Michael Witbrock, Douglas Lenat, Eric Larson. -
Knowledge Begets Knowledge: Steps towards Assisted Knowledge Acquisition in Cyc.
In Papers from the 2005 AAAI Spring Symposium on Knowledge Collection from Volunteer Contributors (KCVC), pp. 99-105, Stanford, California, March 2005.
Michael Witbrock, Cynthia Matuszek, Antoine Brusseau, Robert C. Kahlert, C. Bruce Fraser, Douglas Lenat. - Gathering and Managing Facts for Intelligence Analysis.
In 2005 International Conference on Intelligence Analysis, McLean, Virginia, May 2005.
David Schneider, Cynthia Matuszek, Purvesh Shah, Robert C. Kahlert, David Baxter, John Cabral, Michael Witbrock, Douglas Lenat.
Journals
- Scarecrows in Oz: The Use of Large Language Models in HRI.5,7
In ACM Transactions on Human-Robot Interaction, 2024. Tom Williams, Cynthia Matuszek, Ross Mead, Nick DePalma. -
Spoken language interaction with robots: Recommendations for future research.
In Computer Speech & Language, Volume 71. Elsevier, January 2022. Matthew Marge, Carol Espy-Wilson, Nigel G. Ward, Abeer Alwan, Yoav Artzi, Mohit Bansal, Gil Blankenship, Joyce Chai, Hal Daumé, Debadeepta Dey, Mary Harper, Thomas Howard, Casey Kennington, Ivana Kruijff-Korbayová, Dinesh Manocha, Cynthia Matuszek, Ross Mead, Raymond Mooney, Roger K. Moore, Mari Ostendorf, Heather Pon-Barry, Alexander I. Rudnicky, Matthias Scheutz, Robert St. Amant, Tong Sun, Stefanie Tellex, David Traum, Zhou Yu. -
Robots That Use Language.
In Annual Review of Control, Robotics, and Autonomous Systems, Vol. 3:25-55. January 2020. Stefanie Tellex, Nakul Gopalan, Hadas Kress-Gazit, and Cynthia Matuszek. -
Common Sense Reasoning – From Cyc to Intelligent Assistant.
In Yang Cai and Julio Abascal (eds.), Ambient Intelligence in Everyday Life, pp. 1-31, LNAI 3864, Springer, 2006.
Kathy Panton, Cynthia Matuszek, Douglas Lenat, David Schneider, Michael Witbrock, Nick Siegel, Blake Shepard.
2 This material is based in part upon work supported by the National Science Foundation under Grant No. 1637937: NRI: Collaborative Research: A Framework for Hierarchical, Probabilistic Planning and Learning.
3 This material is based in part upon work supported by the National Science Foundation under Grant No. 1813223: RI: Small: Concept Formation in Partially Observable Domains.
4 This material is based in part upon work supported by the National Science Foundation under Grant No. 1940931: EAGER: Learning Language in Simulation for Real Robot Interaction.
5 This material is based in part upon work supported by the National Science Foundation under Grant No. 2024878: NRI: FND: Semi-Supervised Deep Learning for Domain Adaptation in Robotic Language Acquisition.
6 This material is based in part upon work supported by the National Science Foundation under Grant No. 1920079: MRI: Acquisition of a Heterogeneous GPU Cluster to Facilitate Deep Learning Research at UMBC.
7 This material is based in part upon work supported by the National Science Foundation under Grant No. 2145642: CAREER: Robots, Speech, and Learning in Inclusive Human Spaces.