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Paper · arXiv

BabelJudge: Measuring LLM-as-a-Judge Reliability Across Languages and Agent Trajectories

LLM-as-a-judge has become the dominant approach to scalable evaluation in NLP pipelines, yet judges themselves carry systematic biases that raw accuracy hides: they favor responses placed in slot A (position bias), they prefer longer responses regardless of quality (verbosity bias), and their reliability degrades sharply in lower-resource languages. We introduce BabelJudge, an open-source benchmark and reliability audit framework that measures all four failure modes -- position bias, verbosity bias, order inconsistency, and cross-lingual degradation -- on any judge model, without requiring human preference labels. The key insight is gold-labelling by degradation: starting from a high-qual...

AuthorsShreyas KC
Primary categorycs.CL
Published21 June 2026
Last updated at source21 June 2026
cs.CLcs.AI
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