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cs.CL2026
Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation
Klaudia-Doris Thellmann, Bernhard Stadler, Michael Färber +1
Machine-translated benchmarks are widely used to assess the multilingual capabilities of large language models (LLMs), yet translation errors in these benchmarks remain underexplor…
cs.CL2026
Diagnosing Translated Benchmarks: An Automated Quality Assurance Study of the EU20 Benchmark Suite
Klaudia Thellmann, Bernhard Stadler, Michael Färber
Machine-translated benchmark datasets reduce costs and offer scale, but noise, loss of structure, and uneven quality weaken confidence. What matters is not merely whether we can tr…