Francis Ferraro
Francis Ferraro

Assistant Professor

Faculty, Principal Faculty

University of Maryland, Baltimore County
Computer Science and Electrical Engineering, ITE 358, 1000 Hilltop CIrcle, Baltimore, MD 21250, United States

Frank Ferraro is an assistant professor in the Computer Science and Electrical Engineering department at the University of Maryland, Baltimore County. His research focuses on computational event semantics, and unlabeled, structured probabilistic modeling over very large corpora. He has published on a number of cross-disciplinary basic and applied projects, and has papers in areas such as multimodal processing and information extraction, latent-variable syntactic methods and applications, and the induction and evaluation of frames and scripts. He holds a Ph.D. in Computer Science from Johns Hopkins University and Bachelors in Computer Science and Mathematics, from the University of Rochester.

Francis Ferraro

Publications

2024

  1. A. Padia, F. Ferraro, and T. Finin, "Enhancing Knowledge Graph Consistency through Open Large Language Models: A Case Study", InProceedings, Proceedings of AAAI-MAKE: Empowering Machine Learning and Large Language Models with Domain and Commonsense Knowledge, March 2024, 138 downloads.

2023

  1. S. Devare, M. Koupaee, G. Gunapati, S. Ghosh, S. Vallurupalli, Y. K. Lal, F. Ferraro, N. Chambers, G. Durrett, R. Mooney, K. Erk, and N. Balasubramanian, "SAGEViz: SchemA GEneration and Visualization", InProceedings, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, December 2023, 41 downloads.
  2. S. Ghosh, M. Koupaee, I. Chen, F. Ferraro, N. Chambers, and N. Balasubramanian, "PASTA: A Dataset for Modeling PArticipant STAtes in Narratives", Article, Transactions of the Association for Computational Linguistics, November 2023, 66 downloads.
  3. K. Darvish, E. Raff, F. Ferraro, and C. Matuszek, "Multimodal Language Learning for Object Retrieval in Low Data Regimes in the Face of Missing Modalities", Article, Transactions on Machine Learning Research, October 2023, 70 downloads.
  4. S. R. Dipta, M. Rezaee, and F. Ferraro, "Semantically-informed Hierarchical Event Modeling", InProceedings, Proceedings of the 12th Joint Conference on Lexical and Computational Semantics, July 2023, 77 downloads.
  5. M. Rezaee and F. Ferraro, "RevUp: Revise and Update Information Bottleneck for Event Representation", InProceedings, Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, May 2023, 107 downloads.
  6. F. Lu, E. Raff, and F. Ferraro, "Neural Bregman Divergences for Distance Learning", InProceedings, 11th International Conference on Learning Representations, May 2023, 74 downloads.

2022

  1. S. Vallurupalli, S. Ghosh, K. Erk, N. Balasubramanian, and F. Ferraro, "POQue: Asking Participant-specific Outcome Questions for a Deeper Understanding of Complex Events", Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, December 2022, 142 downloads.
  2. F. Lu, J. Munoz, M. Fuchs, T. LeBlond, E. Zaresky-Williams, E. Raff, F. Ferraro, and B. Testa, "A General Framework for Auditing Differentially Private Machine Learning", InProceedings, Advances in Neural Information Processing Systems, November 2022, 134 downloads.
  3. G. Y. Kebe, L. E. Richards, E. Raff, F. Ferraro, and C. Matuszek, "Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech", InProceedings, Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), June 2022, 84 downloads.
  4. A. Padia, F. Ferraro, and T. Finin, "Jointly Identifying and Fixing Inconsistent Readings from Information Extraction Systems", InProceedings, Proceedings of the Third Deep Learning Inside Out (DeeLIO):Workshop: Knowledge Extraction and Integration for Deep Learning Architecture, May 2022, 266 downloads.
  5. F. Lu, F. Ferraro, and E. Raff, "Continuously Generalized Ordinal Regression for Linear and Deep Models", InProceedings, SIAM International Conference on Data Mining, April 2022, 181 downloads.

2021

  1. N. Pillai, C. Matuszek, and F. Ferraro, "Neural Variational Learning for Grounded Language Acquisition", InProceedings, IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), August 2021, 185 downloads.
  2. A. Ganesan, F. Ferraro, and T. Oates, "Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment", InProceedings, Findings of the Association for Computational Linguistics, August 2021, 311 downloads.
  3. M. Rezaee and F. Ferraro, "Event Representation with Sequential, Semi-Supervised Discrete Variables", InProceedings, Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), June 2021, 701 downloads.
  4. N. Pillai, C. Matuszek, and F. Ferraro, "Measuring Perceptual and Linguistic Complexity in Multilingual Grounded Language Data", InProceedings, 34th International FLAIRS Conference (FLAIRS-34), May 2021, 364 downloads.
  5. A. Ganesan, F. Ferraro, and T. Oates, "Locality Preserving Loss: Neighbors that Live together, Align together", InProceedings, AdaptNPT: The Second Workshop on Domain Adaptation for NLP at EACL, April 2021, 264 downloads.
  6. M. Murnane, P. Higgins, M. Saraf, F. Ferraro, C. Matuszek, and D. Engel, "A Simulator for Human-Robot Interaction in Virtual Reality", InProceedings, Conference on Virtual Reality and 3D User Interfaces, Abstracts and Workshops (VRW), March 2021, 488 downloads.
  7. P. Higgins, G. Y. Kebe, K. Darvish, D. Engel, F. Ferraro, and C. Matuszek, "Towards Making Virtual Human-Robot Interaction a Reality", InProceedings, 3rd International Workshop on Virtual, Augmented, and Mixed-Reality for Human-Robot Interactions (VAM-HRI), March 2021, 560 downloads.

2020

  1. N. Pillai, E. Raff, F. Ferraro, and C. Matuszek, "Sampling Approach Matters: Active Learning for Robotic Language Acquisition", InProceedings, IEEE BigData BDML, December 2020, 653 downloads.
  2. M. Rezaee and F. Ferraro, "A Discrete Variational Recurrent Topic Model without the Reparametrization Trick", InProceedings, NeurIPS, December 2020, 343 downloads.
  3. R. Patel and F. Ferraro, "On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling", InProceedings, EMNLP Workshop on Deep Learning Inside Out, November 2020, 305 downloads.
  4. A. Padia, K. Kalpakis, F. Ferraro, and T. Finin, "Knowledge Graph Inference using Tensor Embedding", InProceedings, 17th International Conference on Principles of Knowledge Representation and Reasoning, September 2020, 429 downloads.
  5. A. T. Nguyen, L. E. Richards, G. Y. Kebe, E. Raff, K. Darvish, F. Ferraro, and C. Matuszek, "Practical Cross-modal Manifold Alignment for Grounded Language", Article, arXiv:2009.05147 [cs.CV], September 2020, 271 downloads.
  6. P. Jenkins, R. Sachdeva, G. Y. Kebe, P. Higgins, K. Darvish, E. Raff, D. Engel, J. Winder, F. Ferraro, and C. Matuszek, "Presentation and Analysis of a Multimodal Dataset for Grounded Language Learning", Article, arXiv:2007.14987 [cs.RO], July 2020, 274 downloads.
  7. A. Ganesan, F. Ferraro, and T. Oates, "Locality Preserving Loss to Align Vector Spaces", Article, arXiv:2004.03734 [cs.LG], April 2020, 308 downloads.
  8. T. W. Satyapanich, F. Ferraro, and T. Finin, "CASIE: Extracting Cybersecurity Event Information from Text", InProceedings, Proceeding of the 34th AAAI Conference on Artificial Intelligence, February 2020, 1736 downloads.

2019

  1. T. W. Satyapanich, T. Finin, and F. Ferraro, "Extracting Rich Semantic Information about Cybersecurity Events", InProceedings, Second Workshop on Big Data for CyberSecurity, held in conjunction with the IEEE Int. Conf. on Big Data, December 2019, 902 downloads.
  2. A. Padia, K. Kalpakis, F. Ferraro, and T. Finin, "Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization", Article, Journal of Web Semantics, December 2019, 964 downloads.
  3. A. Padia, K. Kalpakis, F. Ferraro, and T. Finin, "Reflections on: Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization", InProceedings, International Semantic Web Conference (Journal Track), October 2019, 655 downloads.
  4. C. Kery, N. Pillai, C. Matuszek, and F. Ferraro, "Building Language-Agnostic Grounded Language Learning Systems", InProceedings, 28th International Conference on Robot and Human Interactive Communication (Ro-Man), October 2019, 389 downloads.
  5. A. S. White, E. Stengel-Eskin, S. Vashishtha, V. Govindarajan, D. Reisinger, T. Vieira, K. Sakaguchi, S. Zhang, F. Ferraro, R. Rudinger, K. Rawlins, and B. Van Durme, "The Universal Decompositional Semantics Dataset and Decomp Toolkit", Article, arXiv:1909.13851 [cs.CL], September 2019, 323 downloads.
  6. F. Ferraro, T. (. Huang, S. M. Lukin, and M. Mitchell, "Proceedings of the Second Workshop on Storytelling", Proceedings, Association for Computational Linguistics, August 2019, 391 downloads.
  7. M. Murnane, M. Breitmeyer, F. Ferraro, C. Matuszek, and D. Engel, "Learning from Human-Robot Interactions in Modeled Scenes", InProceedings, ACM SIGGRAPH 2019 Posters, July 2019, 279 downloads.
  8. M. Murnane, M. Breitmeyer, F. Ferraro, and C. Matuszek, "Learning from Human-Robot Interactions in Modeled Scenes", InProceedings, ACM SIGGRAPH 2019 Posters, July 2019, 268 downloads.
  9. C. Kery, F. Ferraro, and C. Matuszek, "¿Es un plátano? Exploring the Application of a Physically Grounded Language Acquisition System to Spanish", NAACL Combined Workshop on Spatial Language Understanding and Grounded Communication for Robotics, June 2019, 396 downloads.
  10. N. Pillai, F. Ferraro, and C. Matuszek, "Deep Learning for Category-Free Grounded Language Acquisition", NAACL Workshop on Spatial Language Understanding and Grounded Communication for Robotics, June 2019, 328 downloads.

2018

  1. A. Padia, F. Ferraro, and T. Finin, "SURFACE: Semantically Rich Fact Validation with Explanations", InCollection, arXiv, November 2018, 534 downloads.
  2. A. Padia, F. Ferraro, and T. Finin, "Team UMBC-FEVER: Claim verification using Semantic Lexical Resources", InProceedings, Proceedings of the First Workshop on Fact Extraction and Verification, November 2018, 604 downloads.
  3. A. Padia, F. Ferraro, and T. Finin, "SURFACE: Semantically Rich Fact Validation with Explanations", Article, arXiv preprint arXiv:1810.13223, October 2018, 404 downloads.
  4. A. Padia, F. Ferraro, and T. Finin, "KG Cleaner: Identifying and Correcting Errors Produced by Information Extraction Systems", InCollection, arXiv, August 2018, 600 downloads.
  5. N. Pillai, F. Ferraro, and C. Matuszek, "Optimal Semantic Distance for Negative Example Selection in Grounded Language Acquisition", Workshop on Models and Representations for Natural Human-Robot Communication (Robotics: Science and Systems), June 2018, 394 downloads.
  6. M. Mitchell, F. Ferraro, and I. Misra, "Proceedings of the First Workshop on Storytelling", Proceedings, Association for Computational Linguistics, June 2018, 431 downloads.
  7. A. Padia, A. Roy, T. W. Satyapanich, F. Ferraro, S. Pan, Y. Park, A. Joshi, and T. Finin, "UMBC at SemEval-2018 Task 8: Understanding Text about Malware", InProceedings, Proceedings of International Workshop on Semantic Evaluation (SemEval-2018), June 2018, 995 downloads.

2017

  1. F. Ferraro, A. Poliak, R. Cotterell, and B. Van Durme, "Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles", InProceedings, Proceedings of the Sixth Joint Conference on Lexical and Computational Semantics (*SEM), August 2017, 544 downloads.

2016

  1. F. Ferraro and B. Van Durme, "A Unified Bayesian Model of Scripts, Frames and Language.", InProceedings, Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 2016, 537 downloads.