| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 1175 | 2022 |
| Large image datasets: A pyrrhic win for computer vision? A Birhane, VU Prabhu 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), 1536-1546, 2021 | 448 | 2021 |
| Multimodal datasets: misogyny, pornography, and malignant stereotypes A Birhane, VU Prabhu, E Kahembwe arXiv preprint arXiv:2110.01963, 2021 | 371 | 2021 |
| Cross‐Layer Resource Allocation and Scheduling I Harjula, M Hiivala, VU Prabhu, D Toumpakaris, H Zhu Next Generation Wireless Communications Using Radio over Fiber, 191-210, 2012 | 163* | 2012 |
| On Wireless Channels With -Antenna Eavesdroppers: Characterization of the Outage Probability and -Outage Secrecy Capacity VU Prabhu, MRD Rodrigues IEEE Transactions on Information Forensics and Security 6 (3), 853-860, 2011 | 107 | 2011 |
| Kannada-MNIST: A new handwritten digits dataset for the Kannada language VU Prabhu arXiv preprint arXiv:1908.01242, 2019 | 81 | 2019 |
| Nl-augmenter: A framework for task-sensitive natural language augmentation KD Dhole, V Gangal, S Gehrmann, A Gupta, Z Li, S Mahamood, ... arXiv preprint arXiv:2112.02721, 2021 | 74 | 2021 |
| Into the laion’s den: Investigating hate in multimodal datasets A Birhane, S Han, V Boddeti, S Luccioni Advances in Neural Information Processing Systems 36, 2024 | 51 | 2024 |
| Do deep neural networks learn shallow learnable examples first? K Mangalam, VU Prabhu ICML 2019 Workshop on Identifying and Understanding Deep Learning Phenomena, 2019 | 43 | 2019 |
| An improved ESPRIT based time-of-arrival estimation algorithm for vehicular OFDM systems VU Prabhu, D Jalihal VTC Spring 2009-IEEE 69th Vehicular Technology Conference, 1-4, 2009 | 33 | 2009 |
| On hate scaling laws for data-swamps A Birhane, V Prabhu, S Han, VN Boddeti arXiv preprint arXiv:2306.13141, 2023 | 29 | 2023 |
| Auditing saliency cropping algorithms A Birhane, VU Prabhu, J Whaley Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 20 | 2022 |
| Understanding adversarial robustness through loss landscape geometries VU Prabhu, DA Yap, J Xu, J Whaley arXiv preprint arXiv:1907.09061, 2019 | 18* | 2019 |
| Model weight theft with just noise inputs: The curious case of the petulant attacker N Roberts, VU Prabhu, M McAteer arXiv preprint arXiv:1912.08987, 2019 | 17 | 2019 |
| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models SU Toshniwal, S Debnath, S Shakeri, S Thormeyer, S Melzi, S Reddy, ... ArXiv, abs/2206.04615, 2022 | 13 | 2022 |
| Fonts-2-handwriting: A seed-augment-train framework for universal digit classification VU Prabhu, S Han, DA Yap, M Douhaniaris, P Seshadri, J Whaley arXiv preprint arXiv:1905.08633, 2019 | 11 | 2019 |
| Vulnerability of deep learning-based gait biometric recognition to adversarial perturbations VU Prabhu, J Whaley CVPR Workshop on The Bright and Dark Sides of Computer Vision: Challenges …, 2017 | 11 | 2017 |
| Acctionnet: A dataset of human activity recognition using on-phone motion sensors J Bartlett, V Prabhu, J Whaley Proceedings of the 34th international conference on machine learning (Sydney …, 2017 | 9 | 2017 |
| Deep connectomics networks: Neural network architectures inspired by neuronal networks N Roberts, DA Yap, VU Prabhu arXiv preprint arXiv:1912.08986, 2019 | 8 | 2019 |
| Covering up bias in CelebA-like datasets with Markov blankets: A post-hoc cure for attribute prior avoidance VU Prabhu, DA Yap, A Wang, J Whaley arXiv preprint arXiv:1907.12917, 2019 | 7 | 2019 |
Dian Ang YapStanford UniversityVerified email at stanford.edu
