Stress and burnout in open source: Toward finding, understanding, and mitigating unhealthy interactions N Raman, M Cao, Y Tsvetkov, C Kästner, B Vasilescu Proceedings of the ACM/IEEE 42nd International Conference on Software …, 2020 | 64 | 2020 |
Data-driven methods for balancing fairness and efficiency in ride-pooling N Raman, S Shah, J Dickerson arXiv preprint arXiv:2110.03524, 2021 | 17 | 2021 |
Human uncertainty in concept-based ai systems KM Collins, M Barker, M Espinosa Zarlenga, N Raman, U Bhatt, M Jamnik, ... Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 869-889, 2023 | 16 | 2023 |
Improving learning-to-defer algorithms through fine-tuning N Raman, M Yee arXiv preprint arXiv:2112.10768, 2021 | 5 | 2021 |
Eliciting bias in question answering models through ambiguity A Mao, N Raman, M Shu, E Li, F Yang, J Boyd-Graber Proceedings of the 3rd Workshop on Machine Reading for Question Answering, 92-99, 2021 | 4 | 2021 |
A muffin-theorem generator G Cui, J Dickerson, N Durvasula, W Gasarch, E Metz, J Prinz, N Raman, ... 9th International Conference on Fun with Algorithms (FUN 2018), 2018 | 2 | 2018 |
Do Concept Bottleneck Models Obey Locality? N Raman, ME Zarlenga, J Heo, M Jamnik arXiv preprint arXiv:2401.01259, 2024 | 1 | 2024 |
What more can Entity Linking do for Question Answering? N Raman, P Rodriguez, J Boyd-Graber | | |