mlsanityData to 14 Oct 2026

Fabricator or dynamic translator?

arXiv 2604.15165 ↗First posted 16 Apr 2026cs.CLcited by 0

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Abstract (arXiv)

LLMs are proving to be adept at machine translation although due to their generative nature they may at times overgenerate in various ways. These overgenerations are different from the neurobabble seen in NMT and range from LLM self-explanations, to risky confabulations, to appropriate explanations, where the LLM is able to act as a human translator would, enabling greater comprehension for the target audience. Detecting and determining the exact nature of the overgenerations is a challenging task. We detail different strategies we have explored for our work in a commercial setting, and present our results.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 17 references that are in the map. First posted on arXiv 16 Apr 2026.

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11 of 17 references.

References · 11

  1. 2023How Good Are GPT Models at Machine Translation? A Comprehensive Evaluationcited by 348
  2. 2021Word Alignment by Fine-tuning Embeddings on Parallel Corporacited by 186
  3. 2023Hallucinations in Large Multilingual Translation Modelscited by 129
  4. 2022Measuring the Mixing of Contextual Information in the Transformercited by 65
  5. 2022Towards Opening the Black Box of Neural Machine Translation: Source and Target Interpretations of the Transformercited by 45
  6. 2024Confabulation: The Surprising Value of Large Language Model Hallucinationscited by 43
  7. 2023HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translationcited by 35
  8. 2025SemEval-2025 Task 3: Mu-SHROOM, the Multilingual Shared Task on Hallucinations and Related Observable Overgeneration Mistakescited by 27
  9. 2024SemEval-2024 Shared Task 6: SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakescited by 24
  10. 2022SALTED: A Framework for SAlient Long-Tail Translation Error Detectioncited by 23
  11. 2024Machine Translation Hallucination Detection for Low and High Resource Languages using Large Language Modelscited by 13

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