Parker Seegmiller

According to our database, Parker Seegmiller authored at least 16 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Medical Triage as Pairwise Ranking: A Benchmark for Urgency in Patient Portal Messages.

Joseph Gatto, Parker Seegmiller, Timothy E. Burdick, Philip Resnik, Roshnik Rahat, Sarah DeLozier, Sarah M. Preum

CoRR, January, 2026

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance.

Parker Seegmiller, Sarah Masud Preum

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

How Much Would a Clinician Edit This Draft? Evaluating LLM Alignment for Patient Message Response Drafting.

Parker Seegmiller, Joseph Gatto, Sarah E. Greer, Ganza Belise Isingizwe, Rohan Ray, Timothy E. Burdick, Sarah Masud Preum

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

FLAMES: Improving LLM Math Reasoning via a Fine-Grained Analysis of the Data Synthesis Pipeline.

Parker Seegmiller, Kartik Mehta, Soumya Saha, Chenyang Tao, Shereen Oraby, Arpit Gupta, Tagyoung Chung, Mohit Bansal, Nanyun Peng

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Document-Level Event-Argument Data Augmentation for Challenging Role Types.

Joseph Gatto, Omar Sharif, Parker Seegmiller, Sarah Masud Preum

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Follow-up Question Generation For Enhanced Patient-Provider Conversations.

Joseph Gatto, Parker Seegmiller, Timothy E. Burdick, Inas S. Khayal, Sarah DeLozier, Sarah Masud Preum

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

In-Context Learning for Preserving Patient Privacy: A Framework for Synthesizing Realistic Patient Portal Messages.

Joseph Gatto, Parker Seegmiller, Timothy E. Burdick, Sarah Masud Preum

CoRR, 2024

Depth F₁: Improving Evaluation of Cross-Domain Text Classification by Measuring Semantic Generalizability.

Parker Seegmiller, Joseph Gatto, Sarah Masud Preum

CoRR, 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

CoRR, 2024

Mad Libs Are All You Need: Augmenting Cross-Domain Document-Level Event Argument Data.

Joseph Gatto, Parker Seegmiller, Omar Sharif, Sarah Masud Preum

CoRR, 2024

2023

Text Encoders Lack Knowledge: Leveraging Generative LLMs for Domain-Specific Semantic Textual Similarity.

Joseph Gatto, Omar Sharif, Parker Seegmiller, Philip Bohlman, Sarah Masud Preum

CoRR, 2023

ActSafe: Predicting Violations of Medical Temporal Constraints for Medication Adherence.

Parker Seegmiller, Joseph Gatto, Abdullah Mamun, Hassan Ghasemzadeh, Diane J. Cook, John A. Stankovic, Sarah Masud Preum

CoRR, 2023

HealthE: Recognizing Health Advice & Entities in Online Health Communities.

Joseph Gatto, Parker Seegmiller, Garrett M. Johnston, Madhusudan Basak, Sarah Masud Preum

Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

The Scope of In-Context Learning for the Extraction of Medical Temporal Constraints.

Parker Seegmiller, Joseph Gatto, Madhusudan Basak, Diane J. Cook, Hassan Ghasemzadeh, John A. Stankovic, Sarah Preum

Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings.

Parker Seegmiller, Sarah Preum

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

HealthE: Classifying Entities in Online Textual Health Advice.

Joseph Gatto, Parker Seegmiller, Garrett Johnston, Sarah Masud Preum

CoRR, 2022