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Beyond Prompts: A Systematic Study of LLM-Based Machine Translation Evaluators
LLM-based evaluators have rapidly become a standard tool for machine translation evaluation, yet the design choices that shape their behavior remain poorly understood. We present a systematic study of how instruction design, few-shot demonstrations, backbone model choice, and multi-step workflows af
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