Scaling WebFAQ 2.0 Dataset Size and Its Impact on MTEB Retrievers for Low-Resource Languages

We present WebFAQ, a large-scale collection of open-domain question answering datasets derived from FAQ-style schema.org annotations. In total, the data collection consists of 96 million natural question-answer (QA) pairs across 75 languages, including 47 million (49\%) non-English samples. WebFAQ further serves as the foundation for 20 monolingual retrieval benchmarks with a total size of 11.2 million QA pairs (5.9 million non-English). These datasets are carefully curated through refined filtering and near-duplicate detection, yielding high-quality resources for training and evaluating multil Research goal: How does the scaling of WebFAQ 2.0's dataset size (198M vs. smaller subsets) influence the trade-off between MTEB retrieval scores and inference efficiency of dense retrievers in low-resource languages? Autonomous synthesis report generated by SOVEREIGN Research Kernel. Tribunal consensus score: 7.7/10. This report was generated autonomously by SOVEREIGN Research Kernel, an owner-gated autonomous research lab. The content synthesizes findings from peer-reviewed papers. Tribunal score: 7.7/10.