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ORCIDDanielle Saunders
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2020 – today
- 2024
[c15]Danielle Saunders, Steve DeNeefe:
Domain adapted machine translation: What does catastrophic forgetting forget and why? EMNLP 2024: 12660-12671- 2023
- [i15]Danielle Saunders, Katrina Olsen:
Gender, names and other mysteries: Towards the ambiguous for gender-inclusive translation. CoRR abs/2306.04573 (2023) - 2022
- [j2]Danielle Saunders:
Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey. J. Artif. Intell. Res. 75: 351-424 (2022) - [c14]Danielle Saunders, Rosie Sallis, Bill Byrne
:
First the Worst: Finding Better Gender Translations During Beam Search. ACL (Findings) 2022: 3814-3823 - [c13]Danielle Saunders:
Domain Adaptation for Neural Machine Translation. EAMT 2022: 9-10 - 2021
- [j1]Marcus Tomalin, Bill Byrne, Shauna Concannon, Danielle Saunders, Stefanie Ullmann:
The practical ethics of bias reduction in machine translation: why domain adaptation is better than data debiasing. Ethics Inf. Technol. 23(3): 419-433 (2021) - [i14]Danielle Saunders:
Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey. CoRR abs/2104.06951 (2021) - [i13]Danielle Saunders, Rosie Sallis, Bill Byrne:
First the worst: Finding better gender translations during beam search. CoRR abs/2104.07429 (2021) - 2020
- [c12]Danielle Saunders, Bill Byrne:
Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problem. ACL 2020: 7724-7736 - [c11]Danielle Saunders, Felix Stahlberg, Bill Byrne:
Using Context in Neural Machine Translation Training Objectives. ACL 2020: 7764-7770 - [c10]Danielle Saunders, Weston Feely, Bill Byrne:
Inference-only sub-character decomposition improves translation of unseen logographic characters. WAT@AAC/IJCNLPL 2020: 170-177 - [c9]Danielle Saunders, Bill Byrne:
Addressing Exposure Bias With Document Minimum Risk Training: Cambridge at the WMT20 Biomedical Translation Task. WMT@EMNLP 2020: 862-869 - [i12]Danielle Saunders, Bill Byrne:
Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problem. CoRR abs/2004.04498 (2020) - [i11]Danielle Saunders, Felix Stahlberg, Bill Byrne:
Using Context in Neural Machine Translation Training Objectives. CoRR abs/2005.01483 (2020) - [i10]Danielle Saunders, Rosie Sallis, Bill Byrne:
Neural Machine Translation Doesn't Translate Gender Coreference Right Unless You Make It. CoRR abs/2010.05332 (2020) - [i9]Danielle Saunders, Bill Byrne:
Addressing Exposure Bias With Document Minimum Risk Training: Cambridge at the WMT20 Biomedical Translation Task. CoRR abs/2010.05333 (2020) - [i8]Danielle Saunders, Weston Feely, Bill Byrne:
Inference-only sub-character decomposition improves translation of unseen logographic characters. CoRR abs/2011.06523 (2020)
2010 – 2019
- 2019
- [c8]Danielle Saunders, Felix Stahlberg, Adrià de Gispert, Bill Byrne:
Domain Adaptive Inference for Neural Machine Translation. ACL (1) 2019: 222-228 - [c7]Danielle Saunders, Felix Stahlberg, Bill Byrne:
UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles. WMT (3) 2019: 169-174 - [c6]Felix Stahlberg, Danielle Saunders, Adrià de Gispert, Bill Byrne:
CUED@WMT19: EWC&LMs. WMT (2) 2019: 364-373 - [i7]Danielle Saunders, Felix Stahlberg, Adrià de Gispert, Bill Byrne:
Domain Adaptive Inference for Neural Machine Translation. CoRR abs/1906.00408 (2019) - [i6]Felix Stahlberg, Danielle Saunders, Adrià de Gispert, Bill Byrne:
Cued@wmt19: ewc&lms. CoRR abs/1906.05447 (2019) - [i5]Danielle Saunders, Felix Stahlberg, Bill Byrne:
UCAM Biomedical translation at WMT19: Transfer learning multi-domain ensembles. CoRR abs/1906.05786 (2019) - 2018
- [c5]Danielle Saunders, Felix Stahlberg, Adrià de Gispert, Bill Byrne:
Multi-representation ensembles and delayed SGD updates improve syntax-based NMT. ACL (2) 2018: 319-325 - [c4]Felix Stahlberg, Danielle Saunders, Gonzalo Iglesias, Bill Byrne:
Why not be Versatile? Applications of the SGNMT Decoder for Machine Translation. AMTA (1) 2018: 208-216 - [c3]Felix Stahlberg, Danielle Saunders, Bill Byrne:
An Operation Sequence Model for Explainable Neural Machine Translation. BlackboxNLP@EMNLP 2018: 175-186 - [i4]Felix Stahlberg, Danielle Saunders, Gonzalo Iglesias, Bill Byrne:
Why not be Versatile? Applications of the SGNMT Decoder for Machine Translation. CoRR abs/1803.07204 (2018) - [i3]Danielle Saunders, Felix Stahlberg, Adrià de Gispert, Bill Byrne:
Multi-representation Ensembles and Delayed SGD Updates Improve Syntax-based NMT. CoRR abs/1805.00456 (2018) - [i2]Felix Stahlberg, Danielle Saunders, Bill Byrne:
An Operation Sequence Model for Explainable Neural Machine Translation. CoRR abs/1808.09688 (2018) - 2017
- [c2]Felix Stahlberg, Eva Hasler, Danielle Saunders, Bill Byrne:
SGNMT - A Flexible NMT Decoding Platform for Quick Prototyping of New Models and Search Strategies. EMNLP (System Demonstrations) 2017: 25-30 - [c1]Anton Ragni, Danielle Saunders, P. Zahemszky, J. Vasilakes, Mark J. F. Gales, Kate M. Knill:
Morph-to-word transduction for accurate and efficient automatic speech recognition and keyword search. ICASSP 2017: 5770-5774 - [i1]Felix Stahlberg, Eva Hasler, Danielle Saunders, Bill Byrne:
SGNMT - A Flexible NMT Decoding Platform for Quick Prototyping of New Models and Search Strategies. CoRR abs/1707.06885 (2017)
Coauthor Index
aka: Bill Byrne
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