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Recent advancements in massively multilingual machine translation systems have significantly enhanced translation accuracy; however, even the best performing systems still generate hallucinations, severely impacting user trust.
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INSTRUCTSCORE: Towards explainable text generation evaluation with automatic feedback
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Enhancing uncertainty-based hallucination detection with stronger focus
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Multilingual machine translation with large language models: Empirical results and analysis
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Cited alongside, same era.
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Looking for a needle in a haystack: A comprehensive study of hallucinations in neural machine translation
Nuno M. Guerreiro, Elena Voita, and André Martins. 2023b
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Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection
Weijia Xu, Sweta Agrawal, Eleftheria Briakou, Marianna J. Martindale, and Marine Carpuat. 2023a
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