AI RESEARCH
GAIA-v2-LILT: Multilingual Adaptation of Agent Benchmark beyond Translation
arXiv CS.CL
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ArXi:2604.24929v1 Announce Type: new Agent benchmarks remain largely English-centric, while their multilingual versions are often built with machine translation (MT) and limited post-editing. We argue that, for agentic tasks, this minimal workflow can easily break benchmark validity through query-answer misalignment or culturally off-target context. We propose a refined workflow for adapting English benchmarks into multiple languages with explicit functional alignment, cultural alignment, and difficulty calibration using both automated checks and human review. Using this workflow, we.