| A Practical guide on Explainable AI Techniques applied on Biomedical use case applications | Nov 13, 2021 | BIG-bench Machine LearningExplainable artificial intelligence | —Unverified | 0 | 0 |
| A Fair Federated Learning Framework With Reinforcement Learning | May 26, 2022 | FairnessFederated Learning | —Unverified | 0 | 0 |
| Can We Trust Machine Learning? The Reliability of Features from Open-Source Speech Analysis Tools for Speech Modeling | Jun 2, 2025 | Fairness | —Unverified | 0 | 0 |
| Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI | Oct 25, 2024 | Bias DetectionEthics | —Unverified | 0 | 0 |
| Approximating Fair k-Min-Sum-Radii in Euclidean Space | Sep 2, 2023 | AttributeFairness | —Unverified | 0 | 0 |
| A Comprehensive Study on Dataset Distillation: Performance, Privacy, Robustness and Fairness | May 5, 2023 | BenchmarkingDataset Distillation | —Unverified | 0 | 0 |
| Can We Improve Model Robustness through Secondary Attribute Counterfactuals? | Nov 1, 2021 | Attributecoreference-resolution | —Unverified | 0 | 0 |
| Approximate Heavily-Constrained Learning with Lagrange Multiplier Models | Dec 1, 2020 | Fairness | —Unverified | 0 | 0 |
| Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms | Jan 3, 2025 | FairnessSynthetic Data Generation | —Unverified | 0 | 0 |
| Approximate Birkhoff-von-Neumann decomposition: a differentiable approach | Jan 1, 2021 | FairnessRiemannian optimization | —Unverified | 0 | 0 |
