On pathological Truths. - Lucas Rosenblatt; Damián Enrique Szmuc (Rev. Symb. Log., 2014)

The Logics of Strict-Tolerant Logic. - Eduardo Alejandro Barrio; Lucas Rosenblatt; Diego Tajer (J. Philos. Log., 2015)

Non-deterministic Conditionals and Transparent Truth. - Federico Matias Pailos; Lucas Rosenblatt (Stud Logica, 2015)

VocalIDE: An IDE for Programming via Speech Recognition. - Lucas Rosenblatt (ASSETS, 2017)

Vocal Programming for People with Upper-Body Motor Impairments. - Lucas Rosenblatt; Patrick Carrington; Kotaro Hara; Jeffrey P. Bigham (W4A, 2018)

Contraction, Infinitary Quantifiers, and Omega Paradoxes. - Bruno Da Ré; Lucas Rosenblatt (J. Philos. Log., 2018)

Noncontractive Classical Logic. - Lucas Rosenblatt (Notre Dame J. Formal Log., 2019)

Differentially Private Synthetic Data: Applied Evaluations and Enhancements. - Lucas Rosenblatt; Xiaoyan Liu; Samira Pouyanfar; Eduardo de Leon; Anuj Desai; Joshua Allen (CoRR, 2020)

Towards a Non-classical Meta-theory for Substructural Approaches to Paradox. - Lucas Rosenblatt (J. Philos. Log., 2021)

PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! - H. M. Sajjad Hossain; Marc T. Friedman; Hiren Patel; Shi Qiao 001; Soundar Srinivasan; Markus Weimer; Remmelt Ammerlaan; Lucas Rosenblatt; Gilbert Antonius; Peter Orenberg; Vijay Ramani; Abhishek Roy 008; et al. (Proc. VLDB Endow., 2021)

Spending Privacy Budget Fairly and Wisely. - Lucas Rosenblatt; Joshua Allen; Julia Stoyanovich (CoRR, 2022)

Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. - Lucas Rosenblatt; Anastasia Holovenko; Taras Rumezhak; Andrii Stadnik; Bernease Herman; Julia Stoyanovich; Bill Howe (CoRR, 2022)

Counterfactual Fairness Is Basically Demographic Parity. - Lucas Rosenblatt; R. Teal Witter (AAAI, 2023)

The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. - Andrew Bell; Lucius Bynum; Nazarii Drushchak; Tetiana Zakharchenko; Lucas Rosenblatt; Julia Stoyanovich (FAccT, 2023)

Critical Perspectives: A Benchmark Revealing Pitfalls in PerspectiveAPI. - Lorena Piedras; Lucas Rosenblatt; Julia Wilkins (CoRR, 2023)

The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. - Andrew Bell; Lucius Bynum; Nazarii Drushchak; Tetiana Herasymova; Lucas Rosenblatt; Julia Stoyanovich (CoRR, 2023)

Top-down Green-ups: Satellite Sensing and Deep Models to Predict Buffelgrass Phenology. - Lucas Rosenblatt; Bin Han 011; Erin Posthumus; Theresa Crimmins; Bill Howe (CoRR, 2023)

A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. - Lucas Rosenblatt; Julia Stoyanovich; Christopher Musco (AAAI, 2024)

I Open at the Close: A Deep Reinforcement Learning Evaluation of Open Streets Initiatives. - R. Teal Witter; Lucas Rosenblatt (AAAI, 2024)

Laboratory-Scale AI: Open-Weight Models are Competitive with ChatGPT Even in Low-Resource Settings. - Robert Wolfe; Isaac Slaughter; Bin Han 011; Bingbing Wen; Yiwei Yang 009; Lucas Rosenblatt; Bernease Herman; Eva Maxfield Brown; Zening Qu; Nic Weber; Bill Howe (FAccT, 2024)

Sharper Bounds for Chebyshev Moment Matching with Applications to Differential Privacy and Beyond. - Cameron Musco; Christopher Musco; Lucas Rosenblatt; Apoorv Vikram Singh (CoRR, 2024)

FairlyUncertain: A Comprehensive Benchmark of Uncertainty in Algorithmic Fairness. - Lucas Rosenblatt; R. Teal Witter (CoRR, 2024)

Differential Privacy Under Class Imbalance: Methods and Empirical Insights. - Lucas Rosenblatt; Yuliia Lut; Eitan Turok; Marco Avella-Medina; Rachel Cummings (CoRR, 2024)

Are Data Experts Buying into Differentially Private Synthetic Data? Gathering Community Perspectives. - Lucas Rosenblatt; Bill Howe; Julia Stoyanovich (CoRR, 2024)

Epistemic Parity: Reproducibility as an Evaluation Metric for Differential Privacy. - Lucas Rosenblatt; Bernease Herman; Anastasia Holovenko; Wonkwon Lee; Joshua R. Loftus; Elizabeth McKinnie; Taras Rumezhak; Andrii Stadnik; Bill Howe; Julia Stoyanovich (SIGMOD Rec., 2024)

We Are AI: Taking Control of Technology. - Julia Stoyanovich; Armanda Lewis; Eric Corbett; Lucius E. J. Bynum; Lucas Rosenblatt; Falaah Arif Khan (AAAI, 2025)

Sharper Bounds for Chebyshev Moment Matching, with Applications. - Cameron Musco; Christopher Musco; Lucas Rosenblatt; Apoorv Vikram Singh (COLT, 2025)

Do You Really Need Public Data? Surrogate Public Data for Differential Privacy on Tabular Data. - Shlomi Hod; Lucas Rosenblatt; Julia Stoyanovich (CoRR, 2025)

Fragments to Facts: Partial-Information Fragment Inference from LLMs. - Lucas Rosenblatt; Bin Han 011; Robert Wolfe; Bill Howe (CoRR, 2025)