Publications
NLP
In-Context Learning for Preserving Patient Privacy: A Framework for Synthesizing Realistic Patient Portal Messages Joseph Gatto, Parker Seegmiller, Timothy Burdick, Sarah M. Preum. Accepted @ Machine Learning for Health (ML4H) Findings.
Explicit, Implicit, and Scattered: Revisiting Event Extraction to Capture Complex Arguments Omar Sharif, Joseph Gatto, Madhusudan Basak, Sarah Masud Preum, Accepted at EMNLP 2024
Large Language Models for Document-Level Event-Argument Data Augmentation for Challenging Role Types Joseph Gatto, Parker Seegmiller, Omar Sharif, Sarah M. Preum, Pre-Print (2024)
Scope of Large Language Models for Mining Emerging Opinions in Online Health Discourse Joseph Gatto, Madhusudan Basak, Yash Srivastava, Philip Bohlman, Sarah M. Preum, Pre-Print (2024)
Depth F1: Improving Evaluation of Cross-Domain Text Classification by Measuring Semantic Generalizability Parker Seegmiller, Joseph Gatto, Sarah M. Preum, Pre-Print (2024)
Theme-driven Keyphrase Extraction to Analyze Social Media Discourse Romano, W., Sharif, O., Basak, M., Gatto, J. and Preum, S., ICWSM (2024)
Do LLMs Find Human Answers To Fact-Driven Questions Perplexing? A Case Study on Reddit Parker Seegmiller, Joseph Gatto, Omar Sharif, Madhusudan Basak, Sarah Masud Preum, REAL-INFO Workshop ICWSM (2024)
Chain-of-Thought Embeddings for Stance Detection on Social Media Gatto et al., EMNLP Findings (2023)
Text Encoders Lack Knowledge: Leveraging Generative LLMs for Domain-Specific Semantic Textual Similarity Joseph Gatto, Omar Sharif, Parker Seegmiller, Phillip Bohlman, and Sarah M. Preum. Accepted at EMNLP Workshop: Generation, Evaluation & Metrics (2023)
Scope of Pre-trained Language Models for Detecting Conflicting Health Information Joseph Gatto, Madhusudan Basak, and Sarah M. Preum. Proceedings of the International AAAI Conference on Web and Social Media , (2023)
HealthE: Recognizing Health Advice & Entities in Online Health Communities Joseph Gatto, Parker Seegmiller, Garrett Johnston, and Sarah M. Preum. Proceedings of the International AAAI Conference on Web and Social Media (2023)
Not Enough Labeled Data? Just Add Semantics: A Data-Efficient Method for Inferring Online Health Texts Joseph Gatto, Sarah M. Preum (2023)
Identifying the Perceived Severity of Patient-Generated Telemedical Queries Regarding COVID: Developing and Evaluating a Transfer Learning–Based Solution Joseph Gatto, Parker Seegmiller, Garrett Johnston, and Sarah M. Preum. Journal of Medical Informatics (2022) -> Data
The Scope of In-Context Learning for the Extraction of Medical Temporal Constraints. Seegmiller P, Gatto J, Basak M, Cook D, Ghasemzadeh H, Stankovic J, Preum SM. The 6th International Workshop on Health Natural Language Processing (HealthNLP 2023) (ICHI 2023 workshop).
ActSafe: Predicting Violations of Medical Temporal Constraints for Medication Adherence Seegmiller, P., Gatto, J., Mamun, A., Ghasemzadeh, H., Cook, D., Stankovic, J. and Preum, S.M., [preprint] (2023)
Robotics
- A Hierarchical Multi-ASV Control System Framework for Adversarial ASV Detainment. Jeong, M., Blanchet, J., Gatto, J., & Li, A. Q. DMMAS Workshop at IROS (2022).
- Virtual IR Sensing for Planetary Rovers: Improved Terrain Classification and Thermal Inertia Estimation) Yumi Iwashita, Kazuto Nakashima, Joseph Gatto, Shoya Higa, Adrian Stoica, Norris Khoo and Ryo Kurazume (2020
Undergrad Thesis
- Single sample feature importance: an interpretable algorithm for low-level feature analysis Gatto, J., Lanka, R., Iwashita, Y. and Stoica, A., 2019