Activation steering on early layers improves diversity of synthetic data for low-resource languages and often boosts downstream classifier performance compared to non-steered prompting.
Better as Generators Than Classifiers: Leveraging LLM s and Synthetic Data for Low-Resource Multilingual Classification
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
Per-language architecture selection among generalists, specialists, and ensembles achieves 0.796 macro F1 across 22 languages in SemEval-2026 Task 9.
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Want Better Synthetic Data? Steer It: Activation Steering for Low-Resource Language Generation
Activation steering on early layers improves diversity of synthetic data for low-resource languages and often boosts downstream classifier performance compared to non-steered prompting.
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MKJ at SemEval-2026 Task 9: A Comparative Study of Generalist, Specialist, and Ensemble Strategies for Multilingual Polarization
Per-language architecture selection among generalists, specialists, and ensembles achieves 0.796 macro F1 across 22 languages in SemEval-2026 Task 9.