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_bibliography/papers.bib

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@article{ukraine_edu25,
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title = {Estimating the impact of the {Russian} invasion on the displacement of graduating high school students in {Ukraine}},
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author = {Tetiana Zakharchenko and Andrew Bell and Nazarii Drushchak and Oleksandra Konopatska and Falaah Arif Khan and Julia Stoyanovich},
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year = {2025},
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journal = {Nature Communications},
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pdf = {https://www.nature.com/articles/s41599-025-04675-5.epdf},
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keywords = {journal,education,policy,RAIforUkraine},
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preview = {map.png},
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code = {https://github.com/DataResponsibly/ZNO-Dataset},
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bibtex_show={true},
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selected = {true}
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}
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@article{hwang2026explanationmultiplicity,
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title={Explanation Multiplicity in {SHAP}: Characterization and Assessment},
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author={Hyunseung Hwang and Seungeun Lee and Lucas Rosenblatt and Steven Euijong Whang and Julia Stoyanovich},
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year={2026},
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eprint={2601.12654},
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pdf = {https://www.arxiv.org/abs/2601.12654},
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archivePrefix={arXiv},
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journal = {CoRR},
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primaryClass={cs.LG},
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selected = {true},
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keywords = {data,explainability,transparency},
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preview = {transparency.png},
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bibtex_show={true}
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}
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@inproceedings{turbal2025ellice,
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title={Elli{CE}: Efficient and Provably Robust Algorithmic Recourse via the Rashomon Sets},
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author={Bohdan Turbal and Iryna Voitsitska and Lesia Semenova},
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booktitle={Proceedings of NeurIPS},
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year={2025},
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keywords = {RAIforUkraine},
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bibtex_show={true},
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pdf = {https://openreview.net/pdf/f59d93d5b3a7a15be7221bf90c47d410aabedea6.pdf},
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preview = {lightbulb.png},
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code = {https://github.com/BogdanTurbal/ellice}
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}
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@inproceedings{restQ,
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author={Kilbasovych, Ostap and Djeffal, Belkis and Bourhis, Pierre and Rouvoy, Romain},
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booktitle={In Proceddings of the IEEE International Conference on Cloud Engineering (IC2E)},
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title={{REST-Q – A Framework to Assess Energy Consumption in Web Applications}},
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year={2025},
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pages={77-78},
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doi={10.1109/IC2E65552.2025.00020},
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pdf = {https://ieeexplore.ieee.org/document/11196504},
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preview = {lightbulb.png},
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bibtex_show={true},
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keywords = {RAIforUkraine},
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note = {demonstration}
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}
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@inproceedings{BuleshnyiPZB,
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title = {Constraint-aware Learning of Probabilistic Sequential Models for Multi-Label Classification},
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author = {Mykhailo Buleshnyi and Anna Polova and Zsolt Zombori and Michael Benedikt},
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booktitle = {In Proceedings of the Workshop on New Ideas for Large-Scale Neurosymbolic Learning Systems (LS-NSL) at VLDB},
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bibtex_show={true},
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year = {2025},
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preview = {lightbulb.png},
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keywords = {RAIforUkraine},
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pdf = {https://www.vldb.org/2025/Workshops/VLDB-Workshops-2025/LS-NSL/LS-NSL25_2.pdf}
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}
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@article{herasymuk2025virnyflow,
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title={{VirnyFlow}: A Design Space for Responsible Model Development},
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author={Denys Herasymuk and Nazar Protsiv and Julia Stoyanovich},
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year={2025},
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eprint={2506.01584},
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pdf = {https://arxiv.org/abs/2506.01584/},
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archivePrefix={arXiv},
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journal = {CoRR},
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primaryClass={cs.LG},
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code = {https://github.com/denysgerasymuk799/virny-flow},
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bibtex_show={true},
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selected = {true},
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preview = {virny.png},
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keywords = {working,RAIforUkraine,data}
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}
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@inproceedings{ecai25,
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title = {From Benchmarking to Understanding {FairML}},
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author = {Mykola Pechenizkiy and Hilde Weerts and Cassio de Campos and Yuya Sasaki and Julia Stoyanovich},
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year = {2025},
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booktitle = {Proceedings of ECAI},
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keywords = {fairness},
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doi = {10.3233/FAIA250783},
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pdf = {https://ebooks.iospress.nl/doi/10.3233/FAIA250783},
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preview = {fairness_tree.png},
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bibtex_show={true}
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}
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@article{natmed_25,
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author = {Tina Hernandez-Boussard
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and Aaron Y. Lee
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bibtex_show={true}
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}
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@article{ukraine_edu25,
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title = {Estimating the impact of the {Russian} invasion on the displacement of graduating high school students in {Ukraine}},
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author = {Tetiana Zakharchenko and Andrew Bell and Nazarii Drushchak and Oleksandra Konopatska and Falaah Arif Khan and Julia Stoyanovich},
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year = {2025},
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journal = {Nature Communications},
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pdf = {https://www.nature.com/articles/s41599-025-04675-5.epdf},
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keywords = {journal,education,policy,RAIforUkraine},
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preview = {map.png},
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code = {https://github.com/DataResponsibly/ZNO-Dataset},
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bibtex_show={true},
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selected = {true}
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}
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@article{shades,
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title={Still More Shades of {Null}: An Evaluation Suite for Responsible Missing Value Imputation},
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author={Falaah {Arif Khan} and Denys Herasymuk and Nazar Protsiv and Julia Stoyanovich},
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year={2025},
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journal = {Proc. {VLDB} Endow.},
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volume = {18},
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number = {9},
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doi = {14778/3746405.3746416},
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url={https://www.vldb.org/pvldb/vol18/p2899-stoyanovich.pdf},
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pdf={https://www.vldb.org/pvldb/vol18/p2899-stoyanovich.pdf},
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code = {https://github.com/FalaahArifKhan/data-cleaning-stability},
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preview = {shades.png},
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bibtex_show={true},
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selected = {true},
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keywords = {journal,RAIforUkraine,data}
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}
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@article{sharp,
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author = {Venetia Pliatsika and
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keywords = {journal,data,ranking,explainability,transparency,RAIforUkraine}
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}
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@article{shades,
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title={Still More Shades of {Null}: An Evaluation Suite for Responsible Missing Value Imputation},
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author={Falaah {Arif Khan} and Denys Herasymuk and Nazar Protsiv and Julia Stoyanovich},
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year={2025},
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journal = {Proc. {VLDB} Endow.},
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volume = {18},
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number = {9},
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doi = {14778/3746405.3746416},
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url={https://www.vldb.org/pvldb/vol18/p2899-stoyanovich.pdf},
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pdf={https://www.vldb.org/pvldb/vol18/p2899-stoyanovich.pdf},
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code = {https://github.com/FalaahArifKhan/data-cleaning-stability},
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preview = {shades.png},
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bibtex_show={true},
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selected = {true},
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keywords = {journal,RAIforUkraine,data}
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}
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@inproceedings{sharp_attack,
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title = {{SHAP}-based Explanations are Sensitive to Feature Representation},
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author = {Hyunseung Hwang and Andrew Bell and Joao Fonseca and Venetia Pliatsika and Julia Stoyanovich and Steven Euijong Whang},
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keywords={conference,data,explainability,transparency}
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}
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@inproceedings{fonseca-etal-2025-safenudge,
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title = "{SafeNudge}: Safeguarding Large Language Models in Real-time with Tunable Safety-Performance Trade-offs",
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author = "Fonseca, Joao and
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Bell, Andrew and
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Stoyanovich, Julia",
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booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
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month = nov,
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year = "2025",
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publisher = "ACM",
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doi = "10.18653/v1/2025.emnlp-main.1010",
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pages = "19955--19969",
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ISBN = "979-8-89176-332-6",
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bibtex_show={true},
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selected = {true},
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keywords={conference,privacy,safety}
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}
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@article{Edelson_Kovba_Yershova_Botelho_McCoy_Lauinger_2025,
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title={Measurement and Metrics for Content Moderation: The Multi-Dimensional Dynamics of Engagement and Content Removal on Facebook},
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volume={2},
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title={Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data},
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author={Shlomi Hod and Lucas Rosenblatt and Julia Stoyanovich},
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year={2025},
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journal = {arXiv},
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eprint={2504.14368},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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journal = {The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), Datasets \& Benchmarks Track},
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url={https://arxiv.org/abs/2504.14368},
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pdf={https://arxiv.org/abs/2504.14368},
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preview={epistemic_parity.png},
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pdf = {https://www.vldb.org/pvldb/vol17/p4341-campbell.pdf},
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bibtex_show={true},
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preview = {erica.png},
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keywords={conference,fairness,data,demo}
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keywords={conference,fairness,data,demo,ranking}
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}
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@inproceedings{DBLP:conf/ijcai/BynumLS24,
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keywords = {conference, fairness}
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}
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@inproceedings{fairrecourse,
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title={How Much Effort Is Enough? Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity},
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author={Andrew Bell and Joao Fonseca and Carlo Abrate and Francesco Bonchi and Julia Stoyanovich},
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year={2025},
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booktitle = {Equity and Access in Algorithms, Mechanisms, and Optimization, {EAAMO}},
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publisher = {{ACM}},
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doi = {10.1145/3757887.3763014},
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pdf = {https://dl.acm.org/doi/pdf/10.1145/3757887.3763014},
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preview={recourse.png},
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bibtex_show={true},
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keywords = {conference,fairness}
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}
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@article{DBLP:journals/pvldb/LiMSJ23,
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author = {Jinyang Li and
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Yuval Moskovitch and
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timestamp = {Mon, 27 Nov 2023 13:13:34 +0100},
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biburl = {https://dblp.org/rec/journals/pvldb/LiMSJ23.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org},
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keywords = {journal,fairness,data},
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keywords = {journal,fairness,data,ranking},
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preview = {erica.png},
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bibtex_show = {true}
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}

_pages/publications.md

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permalink: /research/
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title:
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description:
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#years: [2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015] # replace with your own years
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#years: [i2026, 2025, 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015] # replace with your own years
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years_priv: [2025,2024, 2023, 2022, 2020, 2018, 2017]
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years_rank: [2024, 2023, 2022, 2021, 2019, 2018, 2017, 2016, 2015]
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years_rank: [2025, 2024, 2023, 2022, 2021, 2019, 2018, 2017, 2016, 2015]
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years_edu: [2025, 2024, 2023, 2022, 2021, 2020]
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years_fair: [2024, 2023, 2022, 2021, 2020, 2019, 2017]
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years_expl: [2025, 2024, 2023, 2022, 2020, 2019]
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years_fair: [2025, 2024, 2023, 2022, 2021, 2020, 2019, 2017]
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years_expl: [2026, 2025, 2024, 2023, 2022, 2020, 2019]
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years_pol: [2025, 2024, 2023, 2022, 2019, 2018, 2017]
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nav: false
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nav_order: 2
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{% bibliography -f papers -q @*[year={{y}} && keywords ^= *policy]* %}
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{% endfor %}
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<h2 class="category" id="privacy">Privacy</h2>
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<h2 class="category" id="privacy">Safety and Privacy</h2>
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Our work in privacy includes peer-reviewed papers, as well as tools and benchmarks.
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Take a look at the <a href="https://github.com/DataResponsibly/DataSynthesizer">Data Synthesizer</a> tool
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that we've been using to teach differentially private data synthesis.
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And check out our latest DP synethetic data benchmarking package,
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<a href="https://github.com/DataResponsibly/SynRD">SynRD</a>, posing the question:
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"Can a DP synthesizer produce private (tabular) data that preserves scientific findings?"
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In other words, do DP synthesizers satisfy epistemic parity?
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In other words, do DP synthesizers satisfy epistemic parity?
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We also started working on safety assessment and interventions, take a look at our <a href="https://github.com/joaopfonseca/SafeNudge">SafeNudge</a> project.
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<!-- Add your category specific text here -->
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{% for y in page.years_priv %}
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<h2 class="year">{{y}}</h2>
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{% bibliography -f papers -q @*[year={{y}} && keywords ^= *privacy && keywords ^= *priv] %}
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<h2 class="year">{{ y }}</h2>
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{% bibliography -f papers -q @*[year={{y}} && keywords ~= privacy|safety]* %}
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{% endfor %}
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<h2 class="category" id="ranking">Ranking</h2> One kind of algorithm

_pages/research_dropdown.md

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- title: Fairness
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permalink: /research/#fairness
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- title: divider
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- title: Policy
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- title: Policy and Regulation
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permalink: /research/#policy
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- title: divider
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- title: Privacy
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- title: Privacy and Safety
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permalink: /research/#privacy
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- title: divider
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- title: Ranking
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- title: Ranking and Matching
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permalink: /research/#ranking
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- title: divider
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- title: RAI education

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