Dataset Groups Activity Stream RoBLEURT Submission for the WMT2021 Metrics Task RoBLEURT is a robustly optimizing the training of BLEURT, a trainable metric model for evaluating the semantic consistency between machine translation candidates and golden references. BibTex: @dataset{Yu_Wan_and_Dayiheng_Liu_and_Baosong_Yang_and_Tianchi_Bi_and_Haibo_Zhang_and_Boxing_Chen_and_Weihua_Luo_and_Derek_F_Wong_and_Lidia_S_Chao_2024, abstract = {RoBLEURT is a robustly optimizing the training of BLEURT, a trainable metric model for evaluating the semantic consistency between machine translation candidates and golden references.}, author = {Yu Wan and Dayiheng Liu and Baosong Yang and Tianchi Bi and Haibo Zhang and Boxing Chen and Weihua Luo and Derek F. Wong and Lidia S. Chao}, doi = {10.57702/72be3v9x}, institution = {No Organization}, keyword = {'BLEURT', 'Machine Translation', 'Metric Learning', 'RoBLEURT', 'Semantic Consistency'}, month = {dec}, publisher = {TIB}, title = {RoBLEURT Submission for the WMT2021 Metrics Task}, url = {https://service.tib.eu/ldmservice/dataset/robleurt-submission-for-the-wmt2021-metrics-task}, year = {2024} }
