BabelArena: A Large-Scale Multilingual Benchmark for LLM Agents
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 construct BabelArena, a task-aligned benchmark comprising 16,146 instances derived from 702 canonical ...
| Authors | Peng Kuang, Yuchun Fan, Jiangnan Li et al. |
|---|---|
| Primary category | cs.CL |
| Published | 20 September 2026 |
| Last updated at source | 20 September 2026 |
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