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NLP & Language ModelsLLM-assisted generation2607.23058

ADAGE: A Language-Agnostic Pipeline for Analogical Reasoning Evaluation

Ahmed Haj Ahmed, Alvin Grissom

cs.CL cs.AI

Abstract

Multilingual reasoning evaluation overwhelmingly relies on translating English benchmarks, a practice that introduces linguistic artifacts and fails to test culturally-grounded reasoning. We introduce ADAGE (Analogical Difficulty-by-design Assessment for Grounded Evaluation), a language-agnostic pipeline that combines native-speaker curation with LLM-assisted generation to construct challenging, translation-free benchmarks for abstract analogical reasoning. We validate ADAGE by constructing benchmarks for Arabic, Amharic, and Japanese. Evaluating 14 open-weight models, we find a consistent cultural reasoning gap: models that perform well on English proverb reasoning struggle substantially on all three native benchmarks, with accuracy dropping by 12--52 percentage points relative to English. We release the pipeline, all three benchmarks, and the full evaluation suite.

Topics

Classified with taxonomy v2 on Sat, 5 Sept 2026.

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