A Computer Science Linked-courses Learning Community. - Amber Settle; John Lalor; Theresa A. Steinbach (ITiCSE, 2015)

Reconsidering the Impact of CS1 on Novice Attitudes. - Amber Settle; John Lalor; Theresa A. Steinbach (SIGCSE, 2015)

Learning Object-Oriented Programming in Python: Towards an Inventory of Difficulties and Testing Pitfalls. - Craig S. Miller; Amber Settle; John Lalor (SIGITE, 2015)

Evaluating a Linked-courses Learning Community for Development Majors. - Amber Settle; John Lalor; Theresa A. Steinbach (SIGITE, 2015)

Citation Analysis with Neural Attention Models. - Tsendsuren Munkhdalai; John Lalor; Hong Yu 001 (Louhi@EMNLP, 2016)

Building an Evaluation Scale using Item Response Theory. - John P. Lalor; Hao Wu 055; Hong Yu 001 (EMNLP, 2016)

Beyond Majority Voting: Generating Evaluation Scales using Item Response Theory. - John P. Lalor; Hao Wu 055; Hong Yu 001 (CoRR, 2016)

Generating a Test of Electronic Health Record Narrative Comprehension with Item Response Theory. - John P. Lalor; Hao Wu 055; Li Chen; Kathleen M. Mazor; Hong Yu 001 (AMIA, 2017)

An Analysis of Machine Learning Intelligence. - John P. Lalor; Hao Wu 055; Tsendsuren Munkhdalai; Hong Yu 001 (CoRR, 2017)

Improving Machine Learning Ability with Fine-Tuning. - John P. Lalor; Hao Wu 055; Hong Yu 001 (CoRR, 2017)

Detecting Hypoglycemia Incidents from Patients' Secure Messages. - Jinying Chen; John P. Lalor; Hong Yu 001 (AMIA, 2018)

Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study. - John Lalor; Hao Wu 055; Tsendsuren Munkhdalai; Hong Yu 001 (EMNLP, 2018)

Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity. - Eunah Cho; He Xie; John P. Lalor; Varun Kumar; William M. Campbell (ASRU, 2019)

Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds. - John P. Lalor; Hao Wu 055; Hong Yu 001 (EMNLP/IJCNLP (1), 2019)

An Empirical Analysis of Human-Bot Interaction on Reddit. - Ming-Cheng Ma; John P. Lalor (W-NUT@EMNLP, 2020)

Dynamic Data Selection for Curriculum Learning via Ability Estimation. - John P. Lalor; Hong Yu 001 (EMNLP (Findings), 2020)

Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? - Pedro Rodriguez 001; Joe Barrow; Alexander Miserlis Hoyle; John P. Lalor; Robin Jia; Jordan L. Boyd-Graber (ACL/IJCNLP (1), 2021)

Constructing a Psychometric Testbed for Fair Natural Language Processing. - Ahmed Abbasi; David G. Dobolyi; John P. Lalor; Richard G. Netemeyer; Kendall Smith; Yi Yang 042 (EMNLP (1), 2021)

The Illusion of Certainty and Data-Driven Decision Making in Emergent Situations. - Nicholas Berente; John P. Lalor; Sriram Somanchi; Ahmed Abbasi (ICIS, 2021)

The Effect of Bots on Human Interaction in Online Communities. - Hani Safadi; John P. Lalor; Nicholas Berente (ICIS, 2021)

Clustering Examples in Multi-Dataset Benchmarks with Item Response Theory. - Pedro Rodríguez 001; Phu Mon Htut; John Lalor; João Sedoc (Insights@ACL, 2022)

Benchmarking Intersectional Biases in NLP. - John Lalor; Yi Yang 042; Kendall Smith; Nicole Forsgren; Ahmed Abbasi (NAACL-HLT, 2022)

py-irt: A Scalable Item Response Theory Library for Python. - John P. Lalor; Pedro Rodríguez 001 (CoRR, 2022)

Measuring algorithmic interpretability: A human-learning-based framework and the corresponding cognitive complexity score. - John P. Lalor; Hong Guo (CoRR, 2022)

Stars Are All You Need: A Distantly Supervised Pyramid Network for Document-Level End-to-End Sentiment Analysis. - Wenchang Li; Yixing Chen 006; John P. Lalor (CoRR, 2023)

Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads. - Yi Yang 042; Hanyu Duan; Ahmed Abbasi; John P. Lalor; Kar Yan Tam (CoRR, 2023)

H-COAL: Human Correction of AI-Generated Labels for Biomedical Named Entity Recognition. - Xiaojing Duan; John P. Lalor (CoRR, 2023)

py-irt: A Scalable Item Response Theory Library for Python. - John Patrick Lalor; Pedro Rodríguez 001 (INFORMS J. Comput., 2023)

Evaluating the efficacy of NoteAid on EHR note comprehension among US Veterans through Amazon Mechanical Turk. - John P. Lalor; Hao Wu 055; Kathleen M. Mazor; Hong Yu 001 (Int. J. Medical Informatics, 2023)

Business Analytics in Healthcare: Past, Present, and Future Trends. - Kaitlin D. Wowak; John P. Lalor; Sriram Somanchi; Corey M. Angst (Manuf. Serv. Oper. Manag., 2023)

A Psychology-based Unified Dynamic Framework for Curriculum Learning. - Guangyu Meng; Qingkai Zeng; John P. Lalor; Hong Yu 001 (CoRR, 2024)

Large Language Model-based Role-Playing for Personalized Medical Jargon Extraction. - Jung Hoon Lim; Sunjae Kwon; Zonghai Yao; John P. Lalor; Hong Yu 001 (CoRR, 2024)

Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines. - John P. Lalor; Ahmed Abbasi; Kezia Oketch; Yi Yang 042; Nicole Forsgren (ACM Trans. Inf. Syst., 2024)

GALEA - Leveraging Generative Agents in Artifact Evaluation. - Nicolas Prat; John P. Lalor; Ahmed Abbasi (DESRIST (1), 2025)

No Simple Answer to Data Complexity: An Examination of Instance-Level Complexity Metrics for Classification Tasks. - Ryan A. Cook; John P. Lalor; Ahmed Abbasi (NAACL (Long Papers), 2025)

Hierarchical Deep Document Model. - Yi Yang 042; John P. Lalor; Ahmed Abbasi; Daniel Dajun Zeng (IEEE Trans. Knowl. Data Eng., 2025)

Bridging the LLM Accessibility Divide? Performance, Fairness, and Cost of Closed versus Open LLMs for Automated Essay Scoring. - Kezia Oketch; John P. Lalor; Yi Yang 042; Ahmed Abbasi (CoRR, 2025)