Cross-Lingual LLM-Judge Transfer via Evaluation Decomposition

ACL ARR 2026 March Submission1406 Authors

Keywords: Multilingual, LLM-Judge, Evaluation, Transfer Learning

Abstract: As large language models are increasingly deployed across diverse real-world applications, extending automated evaluation beyond English has become a critical challenge. Existing evaluation approaches are predominantly English-focused, and adapting them to other languages is hindered by the scarcity and cost of human-annotated judgments in most languages. We introduce a decomposition-based evaluation framework built around a Universal Criteria Set (UCS). UCS consists of a shared, language-agnostic set of evaluation dimensions, producing an interpretable intermediate representation that supports cross-lingual transfer with minimal supervision. Experiments on multiple faithfulness tasks across languages and model backbones demonstrate consistent improvements over strong baselines without requiring target-language annotations.

Paper Type: Long

Research Area: Multilingualism and Cross-Lingual NLP

Research Area Keywords: Multilingualism and Cross-Lingual NLP

Contribution Types: Model analysis & interpretability

Languages Studied: English, Amharic, Burmese, French, German, Swahili, Thai, Arabic, Hindi, and Spanish

Submission Number: 1406