Understanding Translationese Effects in Multilingual Machine Translation
Authors: Xinchen Yang, Marine Carpuat


Reviewer paper summaries: Overall interesting paper confirming prior hypotheses towards translationese impacting the translation quality in multilingual MT systems, and especially also translation direction. These hypotheses still seemingly can be confirmed with larger LLM-based translation systems.
Summary of strengths: * includes a good number (5) of languages, among which also ones with non-latin scripts (Arabic and Bengali)
* thorough experimentation, incl. significance tests
* will make the sentence-aligned and source and target language annotation corpora and testbed available, open-source
Summary of weaknesses: * the authors mention themselves in the limitation section that a translation direction not involving English would have been interesting to see as well
* the paper overall seems to lack novelty -- both in the approach taken, as well as in the hypotheses, which already could be confirmed by previous authors and research -- LLMs (expectedly?) don't change in behavior here, and maybe the authors should highlight more /why/ this is the case -- maybe if the training data as such, already inherently contains the translationese effects, the sheer size of data, based on which the LLMs are trained, doesn't actually make a difference because the LLMs just "inherit" what's been present in the data anyway?
Comments, suggestions and typos: * I've put most of my questions / considerations in the Summary of Weaknesses section above
Overall assessment scores: 2.5