SOURCE-LINKED INTELLIGENCE

BabelArena: A Large-Scale Multilingual Benchmark for LLM Agents

arXiv · AI, language, vision and robotics · article · Sep 20, 2026 · UTC

Large language model (LLM) agents increasingly execute multi-step workflows through tool use and interaction with users and environments. However, current agent evaluations are largely English-centric, limiting our understanding of agent capabilities in multilingual settings. We introduce BabelFlow, a benchmark-general agentic workflow that adapts existing agent benchmarks to new languages by analyzing runtime dependencies, coordinating structure-preserving translation, and combining multi-layer verification with human review to preserve task and evaluation semantics. Using BabelFlow, we const

Read original source ↗ Open in workspace

recordType

paper

region

Global