| 2026 | SIGMOD | ExDis: Causal Explanations for Disparate Trends. | Tal Blau, Brit Youngmann, Anna Fariha, Yuval Moskovitch |
| 2025 | SIGMOD | Locator: Local Stability for Rankings. | Felix S. Campbell, Yuval Moskovitch |
| 2025 | SIGMOD | OmniTune: A Universal Framework for Query Refinement via LLMs. | Eldar Hacohen, Yuval Moskovitch, Amit Somech |
| 2023 | ICDE | Detection of Groups with Biased Representation in Ranking. | Jinyang Li, Yuval Moskovitch, H. V. Jagadish |
| 2023 | ICDE | On Explaining Confounding Bias. | Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi |
| 2023 | SIGMOD | Dexer: Detecting and Explaining Biased Representation in Ranking. | Yuval Moskovitch, Jinyang Li, H. V. Jagadish |
| 2023 | SIGMOD | NEXUS: On Explaining Confounding Bias. | Brit Youngmann, Michael J. Cafarella, Yuval Moskovitch, Babak Salimi |
| 2021 | ICDE | PITA: Privacy Through Provenance Abstraction. | Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch |
| 2021 | ICDE | Patterns Count-Based Labels for Datasets. | Yuval Moskovitch, H. V. Jagadish |
| 2021 | SIGMOD | On Optimizing the Trade-off between Privacy and Utility in Data Provenance. | Daniel Deutch, Ariel Frankenthal, Amir Gilad, Yuval Moskovitch |
| 2020 | CIKM | Towards Inferring Queries from Simple and Partial Provenance Examples. | Amir Gilad, Yuval Moskovitch |
| 2020 | ICDE | Contribution Maximization in Probabilistic Datalog. | Tova Milo, Yuval Moskovitch, Brit Youngmann |
| 2020 | SIGMOD | Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries. | Pierre Bourhis, Daniel Deutch, Yuval Moskovitch |
| 2019 | CIKM | PODIUM: Probabilistic Datalog Analysis via Contribution Maximization. | Tova Milo, Yuval Moskovitch, Brit Youngmann |
| 2019 | ICDE | COBRA: Compression Via Abstraction of Provenance for Hypothetical Reasoning. | Daniel Deutch, Yuval Moskovitch, Noam Rinetzky |
| 2019 | SIGMOD | Hypothetical Reasoning via Provenance Abstraction. | Daniel Deutch, Yuval Moskovitch, Noam Rinetzky |
| 2018 | EDBT | Towards Hypothetical Reasoning Using Distributed Provenance. | Daniel Deutch, Yuval Moskovitch, Itay Polak, Noam Rinetzky |
| 2017 | ICDE | POLYTICS: Provenance-Based Analytics of Data-Centric Applications. | Pierre Bourhis, Daniel Deutch, Yuval Moskovitch |
| 2016 | ICDE | Analyzing data-centric applications: Why, what-if, and how-to. | Pierre Bourhis, Daniel Deutch, Yuval Moskovitch |
| 2015 | ICDE | selP: Selective tracking and presentation of data provenance. | Daniel Deutch, Amir Gilad, Yuval Moskovitch |
| 2015 | ICDE | Towards web-scale how-provenance. | Daniel Deutch, Amir Gilad, Yuval Moskovitch |