Cross-Lingual LLM-Judge Transfer via Evaluation Decomposition
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866911529114271744 |
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| author | Sheth, Ivaxi Jonke, Zeno Mantrach, Amin Mansour, Saab |
| author_facet | Sheth, Ivaxi Jonke, Zeno Mantrach, Amin Mansour, Saab |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_18557 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Cross-Lingual LLM-Judge Transfer via Evaluation Decomposition Sheth, Ivaxi Jonke, Zeno Mantrach, Amin Mansour, Saab Computation and Language 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. |
| title | Cross-Lingual LLM-Judge Transfer via Evaluation Decomposition |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2603.18557 |