Amr Sharaf
Cited by
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How good are gpt models at machine translation? a comprehensive evaluation
A Hendy, M Abdelrehim, A Sharaf, V Raunak, M Gabr, H Matsushita, ...
arXiv preprint arXiv:2302.09210, 2023
Real-time multi-scale action detection from 3d skeleton data
A Sharaf, M Torki, ME Hussein, M El-Saban
2015 IEEE Winter Conference on Applications of Computer Vision, 998-1005, 2015
Data augmentation for meta-learning
R Ni, M Goldblum, A Sharaf, K Kong, T Goldstein
International Conference on Machine Learning, 8152-8161, 2021
Meta-learning for few-shot NMT adaptation
A Sharaf, H Hassan, H Daumé III
arXiv preprint arXiv:2004.02745, 2020
Promoting fairness in learned models by learning to active learn under parity constraints
A Sharaf, H Daume III, R Ni
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
Meta-learning for contextual bandit exploration
A Sharaf, H Daumé III
arXiv preprint arXiv:1901.08159, 2019
Active imitation learning with noisy guidance
K Brantley, A Sharaf, H Daumé III
arXiv preprint arXiv:2005.12801, 2020
Structured prediction via learning to search under bandit feedback
A Sharaf, H Daumé III
Proceedings of the 2nd Workshop on Structured Prediction for Natural …, 2017
Leveraging GPT-4 for Automatic Translation Post-Editing
V Raunak, A Sharaf, HH Awadallah, A Menezes
arXiv preprint arXiv:2305.14878, 2023
Kezhi Kong, and Tom Goldstein
R Ni, M Goldblum, A Sharaf
Data augmentation for meta-learning. ICML, 2021
Residual loss prediction: Reinforcement learning with no incremental feedback
H Daumé III, J Langford, A Sharaf
International Conference on Learning Representations, 2018
Meta-learning effective exploration strategies for contextual bandits
A Sharaf, H Daumé III
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9541-9548, 2021
The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task
A Sharaf, S Feng, K Nguyen, K Brantley, H Daumé III
arXiv preprint arXiv:1708.01318, 2017
A paradigm shift in machine translation: Boosting translation performance of large language models
H Xu, YJ Kim, A Sharaf, HH Awadalla
arXiv preprint arXiv:2309.11674, 2023
Strategies to improve few-shot learning for intent classification and slot-filling
S Basu, A Sharaf, KIK Chong, A Fischer, V Rohra, M Amoake, ...
Proceedings of the Workshop on Structured and Unstructured Knowledge …, 2022
Semi-Supervised Few-Shot Intent Classification and Slot Filling
S Basu, A Sharaf, A Fischer, V Rohra, M Amoake, H El-Hammamy, ...
arXiv preprint arXiv:2109.08754, 2021
Random network distillation as a diversity metric for both image and text generation
L Fowl, M Goldblum, A Gupta, A Sharaf, T Goldstein
arXiv preprint arXiv:2010.06715, 2020
Visual Comparison of Images Using Multiple Kernel Learning for Ranking.
A Sharaf, ME Hussein, MA Ismail
BMVC, 95.1-95.13, 2015
On Hard Episodes in Meta-Learning
S Basu, A Sharaf, N Fusi, S Feizi
arXiv preprint arXiv:2110.11190, 2021
A Flexible Measurement of Diversity in Datasets with Random Network Distillation
LH Fowl, M Goldblum, A Gupta, A Sharaf, T Goldstein
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