Fetching the paper…
Reading the bibliography…
Recent years have seen important advances in the building of interpretable models, machine learning models that are designed to be easily understood by humans.
Interpretml: A unified framework for machine learning interpretability
Nori, H.; Jenkins, S.; Koch, P.; and Caruana, R. 2019 · 1909
Earlier work this paper cites.
Using the ADAP learning algorithm to forecast the onset of diabetes mellitus
Smith, J. W.; Everhart, J. E.; Dickson, W.; Knowler, W. C.; and Johannes, R. S. 1988 · 1988
Earlier work this paper cites.
Generalized additive models , volume 43
Hastie, T. J.; and Tibshirani, R. J. 1990 · 1990
Earlier work this paper cites.
Sparse spatial autoregressions
Kelley Pace, R.; and Barry, R. 1997 · 1997
Earlier work this paper cites.
OpenML: networked science in machine learning
Vanschoren, J.; Van Rijn, J. N.; Bischl, B.; and Torgo, L. 2014 · 2014
Earlier work this paper cites.
Intelligible models for healthcare: Predicting pneumonia risk and hospital 30-day readmission
Caruana, R.; Lou, Y.; Gehrke, J.; Koch, P.; Sturm, M.; and Elhadad, N. 2015 · 2015
Earlier work this paper cites.
A unified approach to interpreting model predictions
Lundberg, S. M.; and Lee, S.-I. 2017 · 2017
Earlier work this paper cites.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Rudin, C. 2019 · 2019
Earlier work this paper cites.
Generalized and scalable optimal sparse decision trees
Lin, J.; Zhong, C.; Hu, D.; Rudin, C.; and Seltzer, M. 2020 · 2020
Earlier work this paper cites.
Language models are realistic tabular data generators
Borisov, V.; Seßler, K.; Leemann, T.; Pawelczyk, M.; and Kasneci, G. 2022 · 2022
Cited alongside, same era.
Death by Round Numbers: Glass-Box Machine Learning Uncovers Biases in Medical Practice
Lengerich, B. J.; Caruana, R.; Nunnally, M. E.; and Kellis, M. 2022 · 2022
Cited alongside, same era.
Can Foundation Models Wrangle Your Data?
Narayan, A.; Chami, I.; Orr, L.; Arora, S.; and Ré, C. 2022 · 2022
Cited alongside, same era.
Talktomodel: Understanding machine learning models with open ended dialogues
Slack, D.; Krishna, S.; Lakkaraju, H.; and Singh, S. 2022 · 2022
Cited alongside, same era.
Towards Parameter-Efficient Automation of Data Wrangling Tasks with Prefix-Tuning
Vos, D.; Döhmen, T.; and Schelter, S. 2022 · 2022
Faith and Fate: Limits of Transformers on Compositionality
Dziri, N.; Lu, X.; Sclar, M.; Li, X. L.; Jian, L.; Lin, B. Y.; West, P.; Bhagavatula, C.; Bras, R. L.; Hwang, J. D.; et al. 2023 · 2023
Later among the works it cites.
Tabllm: Few-shot classification of tabular data with large language models
Hegselmann, S.; Buendia, A.; Lang, H.; Agrawal, M.; Jiang, X.; and Sontag, D. 2023 · 2023
Later among the works it cites.
Hollmann, N.; Müller, S.; and Hutter, F. 2023 · 2023
Later among the works it cites.
LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs
Lengerich, B. J.; Bordt, S.; Nori, H.; Nunnally, M. E.; Aphinyanaphongs, Y.; Kellis, M.; and Caruana, R. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J.; Wang, X.; Schuurmans, D.; Bosma, M.; Xia, F.; Chi, E.; Le, Q. V.; Zhou, D.; et al. 2022 · 2022
Cited alongside, same era.
Interpretable Medical Diagnostics with Structured Data Extraction by Large Language Models
Bisercic, A.; Nikolic, M.; van der Schaar, M.; Delibasic, B.; Lio, P.; and Petrovic, A. 2023 · 2023
Cited alongside, same era.
Elephants Never Forget: Testing Language Models for Memorization of Tabular Data
Bordt, S.; Nori, H.; and Caruana, R. 2023 · 2023
Cited alongside, same era.
From Shapley values to generalized additive models and back
Bordt, S.; and von Luxburg, U. 2023 · 2023
Cited alongside, same era.
Liu, N. F.; Lin, K.; Hewitt, J.; Paranjape, A.; Bevilacqua, M.; Petroni, F.; and Liang, P. 2023 · 2023
Later among the works it cites.
TabRet: Pre-training Transformer-based Tabular Models for Unseen Columns
Onishi, S.; Oono, K.; and Hayashi, K. 2023 · 2023
Later among the works it cites.
OpenAI. 2023 · 2023
Later among the works it cites.
AnyPredict: Foundation Model for Tabular Prediction
Wang, Z.; Gao, C.; Xiao, C.; and Sun, J. 2023 · 2023
Later among the works it cites.