SGNMT - A Flexible NMT Decoding Platform for Quick Prototyping of New Models and Search Strategies. - Felix Stahlberg; Eva Hasler; Danielle Saunders; Bill Byrne (EMNLP (System Demonstrations), 2017)

Morph-to-word transduction for accurate and efficient automatic speech recognition and keyword search. - Anton Ragni; Danielle Saunders; P. Zahemszky; J. Vasilakes; Mark J. F. Gales; Kate M. Knill (ICASSP, 2017)

Multi-representation ensembles and delayed SGD updates improve syntax-based NMT. - Danielle Saunders; Felix Stahlberg; Adrià de Gispert; Bill Byrne (ACL (2), 2018)

Why not be Versatile? Applications of the SGNMT Decoder for Machine Translation. - Felix Stahlberg; Danielle Saunders; Gonzalo Iglesias; Bill Byrne (AMTA (1), 2018)

An Operation Sequence Model for Explainable Neural Machine Translation. - Felix Stahlberg; Danielle Saunders; Bill Byrne (BlackboxNLP@EMNLP, 2018)

Domain Adaptive Inference for Neural Machine Translation. - Danielle Saunders; Felix Stahlberg; Adrià de Gispert; Bill Byrne (ACL (1), 2019)

UCAM Biomedical Translation at WMT19: Transfer Learning Multi-domain Ensembles. - Danielle Saunders; Felix Stahlberg; Bill Byrne (WMT (3), 2019)

CUED@WMT19: EWC&LMs. - Felix Stahlberg; Danielle Saunders; Adrià de Gispert; Bill Byrne (WMT (2), 2019)

Reducing Gender Bias in Neural Machine Translation as a Domain Adaptation Problem. - Danielle Saunders; Bill Byrne (ACL, 2020)

Using Context in Neural Machine Translation Training Objectives. - Danielle Saunders; Felix Stahlberg; Bill Byrne (ACL, 2020)

Inference-only sub-character decomposition improves translation of unseen logographic characters. - Danielle Saunders; Weston Feely; Bill Byrne (WAT@AAC/IJCNLPL, 2020)

Addressing Exposure Bias With Document Minimum Risk Training: Cambridge at the WMT20 Biomedical Translation Task. - Danielle Saunders; Bill Byrne (WMT@EMNLP, 2020)

Neural Machine Translation Doesn't Translate Gender Coreference Right Unless You Make It. - Danielle Saunders; Rosie Sallis; Bill Byrne (CoRR, 2020)

The practical ethics of bias reduction in machine translation: why domain adaptation is better than data debiasing. - Marcus Tomalin; Bill Byrne; Shauna Concannon; Danielle Saunders; Stefanie Ullmann (Ethics Inf. Technol., 2021)

First the Worst: Finding Better Gender Translations During Beam Search. - Danielle Saunders; Rosie Sallis; Bill Byrne (ACL (Findings), 2022)

Domain Adaptation for Neural Machine Translation. - Danielle Saunders (EAMT, 2022)

Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Survey. - Danielle Saunders (J. Artif. Intell. Res., 2022)

Gender, names and other mysteries: Towards the ambiguous for gender-inclusive translation. - Danielle Saunders; Katrina Olsen (CoRR, 2023)

Domain adapted machine translation: What does catastrophic forgetting forget and why? - Danielle Saunders; Steve DeNeefe (EMNLP, 2024)