What Do Compressed Multilingual Machine Translation Models Forget?

22 May 2022

Papers citing "What Do Compressed Multilingual Machine Translation Models Forget?"

7 / 7 papers shown

Title
Too Brittle To Touch: Comparing the Stability of Quantization and Distillation Towards Developing Lightweight Low-Resource MT Models Harshita Diddee Sandipan Dandapat Monojit Choudhury T. Ganu Kalika Bali 22 5 0 27 Oct 2022
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation Orevaoghene Ahia Julia Kreutzer Sara Hooker 97 46 0 06 Oct 2021
Larger-Scale Transformers for Multilingual Masked Language Modeling Naman Goyal Jingfei Du Myle Ott Giridhar Anantharaman Alexis Conneau 88 125 0 02 May 2021
Carbon Emissions and Large Neural Network Training David A. Patterson Joseph E. Gonzalez Quoc V. Le Chen Liang Lluís-Miquel Munguía D. Rothchild David R. So Maud Texier J. Dean AI4CE 233 626 0 21 Apr 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey Tailin Liang C. Glossner Lei Wang Shaobo Shi Xiaotong Zhang MQ 121 665 0 24 Jan 2021
I-BERT: Integer-only BERT Quantization Sehoon Kim A. Gholami Z. Yao Michael W. Mahoney Kurt Keutzer MQ 83 332 0 05 Jan 2021
Learning Light-Weight Translation Models from Deep Transformer Bei Li Ziyang Wang Hui Liu Quan Du Tong Xiao Chunliang Zhang Jingbo Zhu VLM 101 36 0 27 Dec 2020