| Phi-3 technical report: A highly capable language model locally on your phone M Abdin, J Aneja, H Awadalla, A Awadallah, AA Awan, N Bach, A Bahree, ... arXiv preprint arXiv:2404.14219, 2024 | 788 | 2024 |
| Textbooks are all you need S Gunasekar, Y Zhang, J Aneja, CCT Mendes, A Del Giorno, S Gopi, ... arXiv preprint arXiv:2306.11644, 2023 | 593 | 2023 |
| Generalized decoding for pixel, image, and language X Zou, ZY Dou, J Yang, Z Gan, L Li, C Li, X Dai, H Behl, J Wang, L Yuan, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 252 | 2023 |
| Phi-2: The Surprising Power of Small Language Models M Abdin, J Aneja, S Bubeck, CCT Mendes, W Chen, A Del Giorno, ... https://www.microsoft.com/en-us/research/blog/phi-2-the-surprising-power-of …, 2023 | 226* | 2023 |
| Progressive skeletonization: Trimming more fat from a network at initialization P De Jorge, A Sanyal, HS Behl, PHS Torr, G Rogez, PK Dokania NeurIPS, 2020 | 115 | 2020 |
| Steer: Simple temporal regularization for neural ode A Ghosh, H Behl, E Dupont, P Torr, V Namboodiri Advances in Neural Information Processing Systems 33, 14831-14843, 2020 | 96 | 2020 |
| Alpha MAML: Adaptive Model-Agnostic Meta-Learning HS Behl, AG Baydin, PHS Torr ICML, 2019 | 89 | 2019 |
| Scaling the convex barrier with active sets A De Palma, HS Behl, R Bunel, P Torr, MP Kumar Proceedings of the ICLR 2021 Conference, 2021 | 64 | 2021 |
| Autosimulate: Learning synthetic data generation HS Behl, AG Baydin, R Gal, PHS Torr, V Vineet European Conference on Computer Vision, 255-271, 2020 | 39 | 2020 |
| Neural-sim: Learning to generate training data with nerf Y Ge, H Behl, J Xu, S Gunasekar, N Joshi, Y Song, X Wang, L Itti, V Vineet European Conference on Computer Vision, 477-493, 2022 | 32 | 2022 |
| Peekaboo: Interactive video generation via masked-diffusion Y Jain, A Nasery, V Vineet, H Behl Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 28 | 2024 |
| Incremental tube construction for human action detection HS Behl, M Sapienza, G Singh, S Saha, F Cuzzolin, PHS Torr BMVC, 2018 | 24 | 2018 |
| Meta-learning deep visual words for fast video object segmentation HS Behl, M Naja, A Arnab, PHS Torr 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 22 | 2020 |
| Phi-4 technical report M Abdin, J Aneja, H Behl, S Bubeck, R Eldan, S Gunasekar, M Harrison, ... arXiv preprint arXiv:2412.08905, 2024 | 14 | 2024 |
| DAMEX: Dataset-aware Mixture-of-Experts for visual understanding of mixture-of-datasets Y Jain, H Behl, Z Kira, V Vineet Advances in Neural Information Processing Systems 36, 2024 | 10 | 2024 |
| Scaling the convex barrier with sparse dual algorithms A De Palma, HS Behl, R Bunel, PHS Torr, MP Kumar Journal of Machine Learning Research 25 (61), 1-51, 2024 | 9 | 2024 |
| Overcoming the convex barrier for simplex inputs HS Behl, MP Kumar, P Torr, K Dvijotham Advances in Neural Information Processing Systems 34, 4871-4882, 2021 | 6 | 2021 |
| Efficiently robustify pre-trained models N Jain, H Behl, YS Rawat, V Vineet Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 3 | 2023 |
| Unlocking spatial comprehension in text-to-image diffusion models MM Derakhshani, M Xia, H Behl, CGM Snoek, V Rühle arXiv preprint arXiv:2311.17937, 2023 | 1 | 2023 |
| Automated and verified deep learning HS Behl University of Oxford, 2021 | | 2021 |
Philip TorrProfessor, University of OxfordVerified email at eng.ox.ac.uk