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Supplementary Materials: EmbeddingGemma Vs XLM-R for English-Indonesian Toxic Text Classification

Research datakeyboard_double_arrow_right Dataset Under curation English Publisher:Zenodo
Authors: Santoso, Daniel Christopher; Prabowo, Aryo Bintang; Chowanda, Andry;

doi: 10.5281/zenodo.19858644

Supplementary Materials: EmbeddingGemma Vs XLM-R for English-Indonesian Toxic Text Classification

Abstract

This repository contains the extended experimental environment specifications and latency evaluation results across multiple batch sizes for the paper titled EmbeddingGemma Vs XLM-R for English-Indonesian Toxic Text Classification, submitted to ICADEIS 2026.

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