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2020 – today
- 2024
[c9]Christian Tomani, David Vilar, Markus Freitag, Colin Cherry, Subhajit Naskar, Mara Finkelstein, Xavier Garcia, Daniel Cremers:
Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Model. ACL (1) 2024: 15660-15679- [c8]Mara Finkelstein, Markus Freitag:
MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods. ICLR 2024 - [c7]Wenda Xu, Daniel Deutsch, Mara Finkelstein, Juraj Juraska, Biao Zhang, Zhongtao Liu, William Yang Wang, Lei Li, Markus Freitag:
LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback. NAACL-HLT (Findings) 2024: 1429-1445 - [c6]Juraj Juraska, Daniel Deutsch, Mara Finkelstein, Markus Freitag:
MetricX-24: The Google Submission to the WMT 2024 Metrics Shared Task. WMT 2024: 492-504 - [c5]Mara Finkelstein, David Vilar, Markus Freitag:
Introducing the NewsPaLM MBR and QE Dataset: LLM-Generated High-Quality Parallel Data Outperforms Traditional Web-Crawled Data. WMT 2024: 1355-1372 - [i10]Firas Trabelsi, David Vilar, Mara Finkelstein, Markus Freitag:
Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms. CoRR abs/2406.02832 (2024) - [i9]Mara Finkelstein, David Vilar, Markus Freitag:
Introducing the NewsPaLM MBR and QE Dataset: LLM-Generated High-Quality Parallel Data Outperforms Traditional Web-Crawled Data. CoRR abs/2408.06537 (2024) - [i8]Juraj Juraska, Daniel Deutsch, Mara Finkelstein, Markus Freitag:
MetricX-24: The Google Submission to the WMT 2024 Metrics Shared Task. CoRR abs/2410.03983 (2024) - [i7]Lily H. Zhang, Hamid Dadkhahi, Mara Finkelstein, Firas Trabelsi, Jiaming Luo, Markus Freitag:
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations. CoRR abs/2410.16509 (2024) - 2023
- [c4]Jan-Thorsten Peter, David Vilar, Daniel Deutsch, Mara Finkelstein, Juraj Juraska, Markus Freitag:
There's No Data like Better Data: Using QE Metrics for MT Data Filtering. WMT 2023: 561-577 - [c3]Juraj Juraska, Mara Finkelstein, Daniel Deutsch, Aditya Siddhant, Mehdi Mirzazadeh, Markus Freitag:
MetricX-23: The Google Submission to the WMT 2023 Metrics Shared Task. WMT 2023: 756-767 - [c2]Daniel Deutsch, Juraj Juraska, Mara Finkelstein, Markus Freitag:
Training and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level. WMT 2023: 996-1013 - [c1]Patrick Fernandes, Daniel Deutsch, Mara Finkelstein, Parker Riley, André Martins, Graham Neubig, Ankush Garg, Jonathan H. Clark, Markus Freitag, Orhan Firat:
The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation. WMT 2023: 1066-1083 - [i6]Patrick Fernandes, Daniel Deutsch, Mara Finkelstein, Parker Riley, André F. T. Martins, Graham Neubig, Ankush Garg, Jonathan H. Clark, Markus Freitag, Orhan Firat:
The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation. CoRR abs/2308.07286 (2023) - [i5]Daniel Deutsch, Juraj Juraska, Mara Finkelstein, Markus Freitag:
Training and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level. CoRR abs/2308.13506 (2023) - [i4]Mara Finkelstein, Subhajit Naskar, Mehdi Mirzazadeh, Apurva Shah, Markus Freitag:
MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods. CoRR abs/2309.10966 (2023) - [i3]Christian Tomani, David Vilar, Markus Freitag, Colin Cherry, Subhajit Naskar, Mara Finkelstein, Daniel Cremers:
Quality Control at Your Fingertips: Quality-Aware Translation Models. CoRR abs/2310.06707 (2023) - [i2]Jan-Thorsten Peter, David Vilar, Daniel Deutsch, Mara Finkelstein, Juraj Juraska, Markus Freitag:
There's no Data Like Better Data: Using QE Metrics for MT Data Filtering. CoRR abs/2311.05350 (2023) - [i1]Wenda Xu, Daniel Deutsch, Mara Finkelstein, Juraj Juraska, Biao Zhang, Zhongtao Liu, William Yang Wang, Lei Li, Markus Freitag:
Pinpoint, Not Criticize: Refining Large Language Models via Fine-Grained Actionable Feedback. CoRR abs/2311.09336 (2023)
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