2024
EMNLP
EMNLP 2024
MSLC24 Submissions to the General Machine Translation Task
Abstract
AbstractThe MSLC (Metric Score Landscape Challenge) submissions for English-German, English-Spanish, and Japanese-Chinese are constrained systems built using Transformer models for the purpose of better evaluating metric performance in the WMT24 Metrics Task. They are intended to be representative of the performance of systems that can be built relatively simply using constrained data and with minimal modifications to the translation training pipeline.
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— wmt24 metrics task
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio