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cs.CL2026
Can We Triage LLM Translation Errors in Classical Texts Without Human References? Source Novelty, GEMBA Scoring, and Budgeted Review through Pali-to-English Translation
Máté Metzger
As large language models become capable translators of classical texts, a key challenge is deciding which outputs need expert review when no human reference exists. This study test…
cs.CL2026
From Outliers to Errors: Auditing Pali-to-English LLM Translations with Multi-Reference Adjudication
Máté Metzger, Nadnapang Phophichit, Hansa Dhammahaso
Single-score translation metrics can conflate legitimate variation with error, a problem especially acute for classical languages where multiple defensible English renderings of th…
cs.CL2026
PaliBench: A Multi-Reference Blueprint for Classical Language Translation Benchmarks
Máté Metzger, Nadnapang Phophichit
Digital humanities projects increasingly rely on machine translation and large language models to widen access to classical, religious, and otherwise under-translated textual tradi…