Sample-Size Scaling
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Sample-Size Scaling of the African Languages NLI Evaluation
arXiv:2606.03219v1 Announce Type: new Abstract: African languages have very little labelled data, and it is unclear if augmenting the quantity of annotation data reliably enhances downstream performance. The study is a systematic sample-size scaling study of natural language inference (NLI) on 16 African languages based on the AfriXNLI benchmark. Under controlled conditions, two multilingual transformer models with roughly 0.6B parameters XLM-R Large fine-tuned on XNLI and AfroXLM-R Large...
Genomic Dimensionality Bounds Mixed-Model Association Power and Fine-Mapping Resolution
Mixed-model genome-wide association studies (GWAS) behave differently in livestock than in humans, yet a unified explanation is lacking. Analyses using the full genomic relationship matrix (full-GRM; from genome-wide SNPs) yield only a few significant peaks even with hundreds of thousands of animals, whereas leave-one-chromosome-out (LOCO), numerator-relationship-matrix, and sparse-GRM approaches report many broad associations over similar data. Here we develop a framework that traces these...