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2020 – today
- 2024
[c15]Gal Yona, Roee Aharoni, Mor Geva:
Narrowing the Knowledge Evaluation Gap: Open-Domain Question Answering with Multi-Granularity Answers. ACL (1) 2024: 6737-6751- [c14]Gal Yona, Roee Aharoni, Mor Geva:
Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words? EMNLP 2024: 7752-7764 - [c13]Zorik Gekhman, Gal Yona, Roee Aharoni, Matan Eyal, Amir Feder, Roi Reichart, Jonathan Herzig:
Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations? EMNLP 2024: 7765-7784 - [i17]Gal Yona, Roee Aharoni, Mor Geva
:
Narrowing the Knowledge Evaluation Gap: Open-Domain Question Answering with Multi-Granularity Answers. CoRR abs/2401.04695 (2024) - [i16]Zorik Gekhman, Gal Yona, Roee Aharoni, Matan Eyal, Amir Feder, Roi Reichart, Jonathan Herzig:
Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations? CoRR abs/2405.05904 (2024) - [i15]Gal Yona, Roee Aharoni, Mor Geva:
Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words? CoRR abs/2405.16908 (2024) - 2023
- [c12]Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon:
Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds. ICLR 2023 - [c11]Guy N. Rothblum, Gal Yona:
Decision-Making Under Miscalibration. ITCS 2023: 92:1-92:20 - [i14]Gal Yona, Or Honovich, Itay Laish, Roee Aharoni:
Surfacing Biases in Large Language Models using Contrastive Input Decoding. CoRR abs/2305.07378 (2023) - 2022
- [c10]Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona:
Beyond Bernoulli: Generating Random Outcomes that cannot be Distinguished from Nature. ALT 2022: 342-380 - [c9]Gili Karni, Guy N. Rothblum, Gal Yona:
On Fairness and Stability in Two-Sided Matchings. ITCS 2022: 92:1-92:17 - [c8]Gal Yona, Shay Moran, Gal Elidan, Amir Globerson:
Active learning with label comparisons. UAI 2022: 2289-2298 - [i13]Guy N. Rothblum, Gal Yona:
Decision-Making under Miscalibration. CoRR abs/2203.09852 (2022) - [i12]Gal Yona, Shay Moran, Gal Elidan, Amir Globerson:
Active Learning with Label Comparisons. CoRR abs/2204.04670 (2022) - [i11]Gal Yona, Amir Feder, Itay Laish:
Useful Confidence Measures: Beyond the Max Score. CoRR abs/2210.14070 (2022) - [i10]Yoav Wald, Gal Yona, Uri Shalit, Yair Carmon:
Malign Overfitting: Interpolation Can Provably Preclude Invariance. CoRR abs/2211.15724 (2022) - 2021
- [j1]Noam Barda, Gal Yona, Guy N. Rothblum, Philip Greenland, Morton Leibowitz, Ran D. Balicer, Eitan Bachmat, Noa Dagan:
Addressing bias in prediction models by improving subpopulation calibration. J. Am. Medical Informatics Assoc. 28(3): 549-558 (2021) - [c7]Gal Yona, Amirata Ghorbani, James Zou:
Who's Responsible? Jointly Quantifying the Contribution of the Learning Algorithm and Data. AIES 2021: 1034-1041 - [c6]Guy N. Rothblum, Gal Yona:
Multi-group Agnostic PAC Learnability. ICML 2021: 9107-9115 - [c5]Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona:
Outcome indistinguishability. STOC 2021: 1095-1108 - [i9]Guy N. Rothblum, Gal Yona:
Multi-group Agnostic PAC Learnability. CoRR abs/2105.09989 (2021) - [i8]Guy N. Rothblum, Gal Yona:
Consider the Alternatives: Navigating Fairness-Accuracy Tradeoffs via Disqualification. CoRR abs/2110.00813 (2021) - [i7]Gal Yona, Daniel Greenfeld:
Revisiting Sanity Checks for Saliency Maps. CoRR abs/2110.14297 (2021) - [i6]Gili Karni, Guy N. Rothblum, Gal Yona:
On Fairness and Stability in Two-Sided Matchings. CoRR abs/2111.10885 (2021) - 2020
- [c4]Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum, Gal Yona:
Preference-informed fairness. FAT* 2020: 546 - [c3]Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum, Gal Yona:
Preference-Informed Fairness. ITCS 2020: 16:1-16:23 - [i5]Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona:
Outcome Indistinguishability. CoRR abs/2011.13426 (2020) - [i4]Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona:
Outcome Indistinguishability. Electron. Colloquium Comput. Complex. TR20 (2020)
2010 – 2019
- 2019
- [c2]Cynthia Dwork, Michael P. Kim, Omer Reingold, Guy N. Rothblum, Gal Yona:
Learning from Outcomes: Evidence-Based Rankings. FOCS 2019: 106-125 - [i3]Michael P. Kim, Aleksandra Korolova, Guy N. Rothblum, Gal Yona:
Preference-Informed Fairness. CoRR abs/1904.01793 (2019) - [i2]Gal Yona, Amirata Ghorbani, James Y. Zou:
Who's responsible? Jointly quantifying the contribution of the learning algorithm and training data. CoRR abs/1910.04214 (2019) - 2018
- [c1]Gal Yona, Guy N. Rothblum:
Probably Approximately Metric-Fair Learning. ICML 2018: 5666-5674 - [i1]Guy N. Rothblum, Gal Yona:
Probably Approximately Metric-Fair Learning. CoRR abs/1803.03242 (2018)
Coauthor Index
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