Budget-Xfer: Budget-Constrained Source Language Selection for Cross-Lingual Transfer to African Languages
Cross-lingual transfer learning enables NLP for low-resource languages by leveraging labeled data from higher-resource sources, yet existing comparisons of source language selection strategies do not control for total training data, confounding language selection effects with data quantity effects. We introduce Budget-Xfer, a framework that formulates multi-source cross-lingual transfer as a budget-constrained resource allocation problem. Given a fixed annotation budget B, our framework jointly optimizes which source languages to include and how much data to allocate from each. We evaluate four allocation strategies across named entity recognition and sentiment analysis for three African ...
| Authors | Tewodros Kederalah Idris, Roald Eiselen, Prasenjit Mitra |
|---|---|
| Primary category | cs.CL |
| Published | 29 March 2026 |
| Last updated at source | 29 March 2026 |
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