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Found 3 papers, 2 papers with code
Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models
To further improve the performance of LLMs on MT quality assessment, we investigate several prompting designs, and propose a new prompting method called \textbf{\texttt{Error Analysis Prompting}} (EAPrompt) by combining Chain-of-Thoughts (Wei et al., 2022) and Error Analysis (Lu et al., 2023).
Original or Translated? On the Use of Parallel Data for Translation Quality Estimation
Machine Translation Quality Estimation (QE) is the task of evaluating translation output in the absence of human-written references.
Vega-MT: The JD Explore Academy Translation System for WMT22
As for model sizes, we scale the Transformer-Big up to the extremely large model that owns nearly 4. 7 Billion parameters, to fully enhance the model capacity for our Vega-MT.
Ranked #1 on
Machine Translation
on WMT 2022 English-Russian
