most citedTraining and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2025

WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects

Daniel Deutsch, Eleftheria Briakou, Isaac Caswell +14

As large language models (LLM) become more and more capable in languages other than English, it is important to collect benchmark datasets in order to evaluate their multilingual p…

cs.CL2023

There's no Data Like Better Data: Using QE Metrics for MT Data Filtering

Jan-Thorsten Peter, David Vilar, Daniel Deutsch +3

Quality Estimation (QE), the evaluation of machine translation output without the need of explicit references, has seen big improvements in the last years with the use of neural me…

cs.CL20231 cited

Training and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level

Daniel Deutsch, Juraj Juraska, Mara Finkelstein +1

As research on machine translation moves to translating text beyond the sentence level, it remains unclear how effective automatic evaluation metrics are at scoring longer translat…

cs.CL20231 cited

Athena 2.0: Discourse and User Modeling in Open Domain Dialogue

Omkar Patil, Lena Reed, Kevin K. Bowden +12

Conversational agents are consistently growing in popularity and many people interact with them every day. While many conversational agents act as personal assistants, they can hav…

cs.CL2023

Controllable Generation of Dialogue Acts for Dialogue Systems via Few-Shot Response Generation and Ranking

Angela Ramirez, Karik Agarwal, Juraj Juraska +2

Dialogue systems need to produce responses that realize multiple types of dialogue acts (DAs) with high semantic fidelity. In the past, natural language generators (NLGs) for dialo…