作者位次 #2/4ACL 2026Poster· Natural Language Processing
Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation
Klaudia Thellmann · Bernhard Stadler · Michael Färber · Jens Lehmann
摘要
Machine-translated benchmarks are widely used to assess the multilingual capabilities of large language models (LLMs), yet translation errors in these benchmarks remain underexplored, raising concerns about the reliability and comparability of multilingual evaluation. We address two practical gap...