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John Lalor
John Lalor
Assistant Professor, University of Notre Dame
Adresse e-mail validée de nd.edu - Page d'accueil
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Building an evaluation scale using item response theory
JP Lalor, H Wu, H Yu
Proceedings of the Conference on Empirical Methods in Natural Language …, 2016
832016
Evaluation examples are not equally informative: How should that change NLP leaderboards?
P Rodriguez, J Barrow, AM Hoyle, JP Lalor, R Jia, J Boyd-Graber
Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021
592021
Benchmarking intersectional biases in NLP
JP Lalor, Y Yang, K Smith, N Forsgren, A Abbasi
Proceedings of the 2022 conference of the North American chapter of the …, 2022
562022
Understanding deep learning performance through an examination of test set difficulty: A psychometric case study
JP Lalor, H Wu, T Munkhdalai, H Yu
Proceedings of the Conference on Empirical Methods in Natural Language …, 2018
45*2018
Learning latent parameters without human response patterns: Item response theory with artificial crowds
JP Lalor, H Wu, H Yu
Proceedings of the Conference on Empirical Methods in Natural Language …, 2019
432019
Detecting hypoglycemia incidents reported in patients’ secure messages: using cost-sensitive learning and oversampling to reduce data imbalance
J Chen, J Lalor, W Liu, E Druhl, E Granillo, VG Vimalananda, H Yu
Journal of medical Internet research 21 (3), e11990, 2019
332019
Citation analysis with neural attention models
T Munkhdalai, JP Lalor, H Yu
Proceedings of the Seventh International Workshop on Health Text Mining and …, 2016
292016
Improving electronic health record note comprehension with NoteAid: randomized trial of electronic health record note comprehension interventions with crowdsourced workers
JP Lalor, B Woolf, H Yu
Journal of medical Internet research 21 (1), e10793, 2019
242019
ComprehENotes, an instrument to assess patient reading comprehension of electronic health record notes: development and validation
JP Lalor, H Wu, L Chen, KM Mazor, H Yu
Journal of medical Internet research 20 (4), e139, 2018
232018
Dynamic data selection for curriculum learning via ability estimation
JP Lalor, H Yu
Proceedings of the Conference on Empirical Methods in Natural Language …, 2020
212020
CIFT: Crowd-informed fine-tuning to improve machine learning ability
JP Lalor, H Wu, H Yu
arXiv preprint arXiv:1702.08563, 2017
20*2017
Reconsidering the impact of CS1 on novice attitudes
A Settle, J Lalor, T Steinbach
Proceedings of the 46th ACM Technical Symposium on Computer Science …, 2015
202015
Efficient semi-supervised learning for natural language understanding by optimizing diversity
E Cho, H Xie, JP Lalor, V Kumar, WM Campbell
2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2019
192019
Learning Object-Oriented Programming in Python: Towards an Inventory of Difficulties and Testing Pitfalls
C Miller, A Settle, J Lalor
172015
Constructing a psychometric testbed for fair natural language processing
A Abbasi, D Dobolyi, JP Lalor, RG Netemeyer, K Smith, Y Yang
Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021
142021
A computer science linked-courses learning community
A Settle, J Lalor, T Steinbach
Proceedings of the 2015 ACM Conference on Innovation and Technology in …, 2015
132015
py-irt: A Scalable Item Response Theory Library for Python
JP Lalor, P Rodriguez
INFORMS Journal on Computing 35 (1), 5-13, 2023
92023
An empirical analysis of human-bot interaction on reddit
MC Ma, JP Lalor
Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020 …, 2020
92020
Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines
JP Lalor, A Abbasi, K Oketch, Y Yang, N Forsgren
ACM Transactions on Information Systems, 2024
62024
Clustering Examples in Multi-Dataset Benchmarks with Item Response Theory
P Rodriguez, PM Htut, JP Lalor, J Sedoc
Proceedings of the Third Workshop on Insights from Negative Results in NLP …, 2022
62022
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