Authors build an ontology and taxonomy for untranslatability in MT, release a paired dataset of untranslatable sentences with strategy-based translations, and report human preference for annotation-style compensation.
Controlling Politeness in Neural Machine Translation via Side Constraints
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CL 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
ComplexityMT benchmark finds higher CEFR levels increase translation difficulty and MT systems often shift target CEFR levels versus source texts in most of six languages tested.
citing papers explorer
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Translating the Untranslatable: An Operationalizable Ontology for Untranslatability
Authors build an ontology and taxonomy for untranslatability in MT, release a paired dataset of untranslatable sentences with strategy-based translations, and report human preference for annotation-style compensation.
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ComplexityMT: Benchmarking the Interaction Between Text Complexity and Machine Translation
ComplexityMT benchmark finds higher CEFR levels increase translation difficulty and MT systems often shift target CEFR levels versus source texts in most of six languages tested.