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DEEP METRIC LEARNING USING TRIPLET NETWORK
The Triplet network model learns useful representations by distance comparisons. -
Representer Theorems for Metric and Preference Learning
The dataset is used to demonstrate the representer theorem for simultaneous metric and preference learning from paired comparisons and metric learning from triplet comparisons. -
Inferring and Learning from Neuronal Correspondences
The dataset is used for inferring and learning from neuronal correspondences in the European medicinal leech. -
COMET: A neural framework for MT evaluation
The COMET dataset contains human-annotated scores for machine translation candidates. -
WMT2020 Metrics Shared Task
The WMT2020 Metrics Shared Task dataset contains human-annotated scores for machine translation candidates. -
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...
