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Marco Tulio Ribeiro
Marco Tulio Ribeiro
Google DeepMind
Verified email at cs.washington.edu - Homepage
Title
Cited by
Cited by
Year
" Why Should I Trust You?": Explaining the Predictions of Any Classifier
MT Ribeiro, S Singh, C Guestrin
Knowledge Discovery and Data Mining (ACM KDD), 2016
163122016
Anchors: High-Precision Model-Agnostic Explanations
MT Ribeiro, S Singh, C Guestrin
AAAI, 2018
20852018
Sparks of artificial general intelligence: Early experiments with gpt-4
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
arXiv preprint arXiv:2303.12712, 2023
14742023
Model-agnostic interpretability of machine learning
MT Ribeiro, S Singh, C Guestrin
arXiv preprint arXiv:1606.05386, 2016
10672016
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList
MT Ribeiro, T Wu, C Guestrin, S Singh
Association for Computational Linguistics (ACL), 2020
8942020
Semantically Equivalent Adversarial Rules for Debugging NLP Models
MT Ribeiro, S Singh, C Guestrin
Association for Computational Linguistics (ACL), 2018
4862018
Does the whole exceed its parts? the effect of ai explanations on complementary team performance
G Bansal, T Wu, J Zhou, R Fok, B Nushi, E Kamar, MT Ribeiro, D Weld
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021
3992021
Polyjuice: Generating counterfactuals for explaining, evaluating, and improving models
T Wu, MT Ribeiro, J Heer, DS Weld
arXiv preprint arXiv:2101.00288, 2021
200*2021
Multiobjective pareto-efficient approaches for recommender systems
MT Ribeiro, N Ziviani, ESD Moura, I Hata, A Lacerda, A Veloso
ACM Transactions on Intelligent Systems and Technology (TIST) 5 (4), 1-20, 2014
1552014
Pareto-efficient hybridization for multi-objective recommender systems
MT Ribeiro, A Lacerda, A Veloso, N Ziviani
Proceedings of the sixth ACM conference on Recommender systems, 19-26, 2012
1552012
Errudite: Scalable, reproducible, and testable error analysis
T Wu, MT Ribeiro, J Heer, DS Weld
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
1362019
Sparks of artificial general intelligence: early experiments with GPT-4. arXiv
S Bubeck, V Chandrasekaran, R Eldan, J Gehrke, E Horvitz, E Kamar, ...
1182023
Do feature attribution methods correctly attribute features?
Y Zhou, S Booth, MT Ribeiro, J Shah
Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9623-9633, 2022
1062022
Are red roses red? evaluating consistency of question-answering models
MT Ribeiro, C Guestrin, S Singh
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
982019
Editing models with task arithmetic
G Ilharco, MT Ribeiro, M Wortsman, S Gururangan, L Schmidt, ...
arXiv preprint arXiv:2212.04089, 2022
862022
Nothing else matters: Model-agnostic explanations by identifying prediction invariance
MT Ribeiro, S Singh, C Guestrin
arXiv preprint arXiv:1611.05817, 2016
842016
ART: Automatic multi-step reasoning and tool-use for large language models
B Paranjape, S Lundberg, S Singh, H Hajishirzi, L Zettlemoyer, ...
arXiv preprint arXiv:2303.09014, 2023
722023
Programs as black-box explanations
S Singh, MT Ribeiro, C Guestrin
arXiv preprint arXiv:1611.07579, 2016
682016
Why Should I Trust You?": Explaining the Predictions of Any Classifier. CoRR abs/1602.04938 (2016)
MT Ribeiro, S Singh, C Guestrin
arXiv preprint arXiv:1602.04938, 2016
672016
Squinting at vqa models: Introspecting vqa models with sub-questions
RR Selvaraju, P Tendulkar, D Parikh, E Horvitz, MT Ribeiro, B Nushi, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
622020
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