John Lalor

According to our database, John Lalor authored at least 34 papers between 2015 and 2025.

Collaborative distances:

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

2025

Hierarchical Deep Document Model.

Yi Yang, John P. Lalor, Ahmed Abbasi, Daniel Dajun Zeng

IEEE Trans. Knowl. Data Eng., January, 2025

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, Nicole Forsgren

ACM Trans. Inf. Syst., July, 2024

Large Language Model-based Role-Playing for Personalized Medical Jargon Extraction.

Jung Hoon Lim, Sunjae Kwon, Zonghai Yao, John P. Lalor, Hong Yu

CoRR, 2024

A Psychology-based Unified Dynamic Framework for Curriculum Learning.

Guangyu Meng, Qingkai Zeng, John P. Lalor, Hong Yu

CoRR, 2024

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., May, 2023

Evaluating the efficacy of NoteAid on EHR note comprehension among US Veterans through Amazon Mechanical Turk.

John P. Lalor, Hao Wu, Kathleen M. Mazor, Hong Yu

Int. J. Medical Informatics, April, 2023

<tt>py-irt</tt>: A Scalable Item Response Theory Library for Python.

John Patrick Lalor, Pedro Rodríguez

INFORMS J. Comput., 2023

H-COAL: Human Correction of AI-Generated Labels for Biomedical Named Entity Recognition.

Xiaojing Duan, John P. Lalor

CoRR, 2023

Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads.

Yi Yang, Hanyu Duan, Ahmed Abbasi, John P. Lalor, Kar Yan Tam

CoRR, 2023

Stars Are All You Need: A Distantly Supervised Pyramid Network for Document-Level End-to-End Sentiment Analysis.

Wenchang Li, Yixing Chen, John P. Lalor

CoRR, 2023

2022

Measuring algorithmic interpretability: A human-learning-based framework and the corresponding cognitive complexity score.

John P. Lalor, Hong Guo

CoRR, 2022

py-irt: A Scalable Item Response Theory Library for Python.

John P. Lalor, Pedro Rodríguez

CoRR, 2022

Benchmarking Intersectional Biases in NLP.

John Lalor, Yi Yang, Kendall Smith, Nicole Forsgren, Ahmed Abbasi

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Clustering Examples in Multi-Dataset Benchmarks with Item Response Theory.

Pedro Rodríguez, Phu Mon Htut, John Lalor, João Sedoc

Proceedings of the Third Workshop on Insights from Negative Results in NLP, 2022

2021

The Effect of Bots on Human Interaction in Online Communities.

Hani Safadi, John P. Lalor, Nicholas Berente

Proceedings of the 42nd International Conference on Information Systems, 2021

The Illusion of Certainty and Data-Driven Decision Making in Emergent Situations.

Nicholas Berente, John P. Lalor, Sriram Somanchi, Ahmed Abbasi

Proceedings of the 42nd International Conference on Information Systems, 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

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards?

Pedro Rodriguez, Joe Barrow, Alexander Miserlis Hoyle, John P. Lalor, Robin Jia, Jordan L. Boyd-Graber

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Dynamic Data Selection for Curriculum Learning via Ability Estimation.

John P. Lalor, Hong Yu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

An Empirical Analysis of Human-Bot Interaction on Reddit.

Ming-Cheng Ma, John P. Lalor

Proceedings of the Sixth Workshop on Noisy User-generated Text, 2020

2019

Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds.

John P. Lalor, Hao Wu, Hong Yu

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity.

Eunah Cho, He Xie, John P. Lalor, Varun Kumar, William M. Campbell

Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2019

2018

Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study.

John Lalor, Hao Wu, Tsendsuren Munkhdalai, Hong Yu

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Detecting Hypoglycemia Incidents from Patients' Secure Messages.

Jinying Chen, John P. Lalor, Hong Yu

Proceedings of the AMIA 2018, 2018

2017

Improving Machine Learning Ability with Fine-Tuning.

John P. Lalor, Hao Wu, Hong Yu

CoRR, 2017

An Analysis of Machine Learning Intelligence.

John P. Lalor, Hao Wu, Tsendsuren Munkhdalai, Hong Yu

CoRR, 2017

Generating a Test of Electronic Health Record Narrative Comprehension with Item Response Theory.

John P. Lalor, Hao Wu, Li Chen, Kathleen M. Mazor, Hong Yu

Proceedings of the AMIA 2017, 2017

2016

Beyond Majority Voting: Generating Evaluation Scales using Item Response Theory.

John P. Lalor, Hao Wu, Hong Yu

CoRR, 2016

Building an Evaluation Scale using Item Response Theory.

John P. Lalor, Hao Wu, Hong Yu

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

Citation Analysis with Neural Attention Models.

Tsendsuren Munkhdalai, John Lalor, Hong Yu

Proceedings of the Seventh International Workshop on Health Text Mining and Information Analysis, 2016

2015

Evaluating a Linked-courses Learning Community for Development Majors.

Amber Settle, John Lalor, Theresa A. Steinbach

Proceedings of the 16th Annual Conference on Information Technology Education, 2015

Learning Object-Oriented Programming in Python: Towards an Inventory of Difficulties and Testing Pitfalls.

Craig S. Miller, Amber Settle, John Lalor

Proceedings of the 16th Annual Conference on Information Technology Education, 2015

Reconsidering the Impact of CS1 on Novice Attitudes.

Amber Settle, John Lalor, Theresa A. Steinbach

Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 2015

A Computer Science Linked-courses Learning Community.

Amber Settle, John Lalor, Theresa A. Steinbach

Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education, 2015