| 2025 | EMNLP | Beyond Pointwise Scores: Decomposed Criteria-Based Evaluation of LLM Responses. | Fangyi Yu, Nabeel Seedat, Drahomira Herrmannova, Frank Schilder, Jonathan Richard Schwarz |
| 2025 | ICLR | Going Beyond Static: Understanding Shifts with Time-Series Attribution. | Jiashuo Liu, Nabeel Seedat, Peng Cui, Mihaela van der Schaar |
| 2025 | ICML | Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching. | Nabeel Seedat, Mihaela van der Schaar |
| 2024 | AISTATS | DAGnosis: Localized Identification of Data Inconsistencies using Structures. | Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabb, Zhaozhi Qian, Mihaela van der Schaar |
| 2024 | ICLR | Large Language Models to Enhance Bayesian Optimization. | Tennison Liu, Nicols Astorga, Nabeel Seedat, Mihaela van der Schaar |
| 2024 | ICLR | Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI. | Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar |
| 2024 | ICML | Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise. | Thomas Pouplin, Alan Jeffares, Nabeel Seedat, Mihaela van der Schaar |
| 2024 | ICML | Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes. | Nabeel Seedat, Nicolas Huynh, Boris van Breugel, Mihaela van der Schaar |
| 2023 | AISTATS | Improving Adaptive Conformal Prediction Using Self-Supervised Learning. | Nabeel Seedat, Alan Jeffares, Fergus Imrie, Mihaela van der Schaar |
| 2023 | ICML | Differentiable and Transportable Structure Learning. | Jeroen Berrevoets, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar |
| 2022 | ICML | Data-SUITE: Data-centric identification of in-distribution incongruous examples. | Nabeel Seedat, Jonathan Crabb, Mihaela van der Schaar |
| 2022 | ICML | Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. | Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar |