arXiv Computation and Language August 28, 2026 By Anjishnu Mukherjee, Ziwei Zhu, Antonios Anastasopoulos

MAPLE: Metadata Conditioned LLM Pretraining for Locale-Aware Question Answering

Read the original on arXiv Computation and Language →

The paper introduces MAPLE, a family of decoder‑only language models pretrained with document‑level geographic metadata such as source URL, country, and continent. MAPLE is evaluated on a new benchmark, LocalNewsQA, which tests whether models can switch answers when the locale changes. Experiments show that, with inference‑time metadata fixed, MAPLE outperforms metadata‑free controls in both answer switching and accuracy on locale‑dependent questions, and these gains grow with model size.

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