Latent-space method improves factual consistency across languages without reported accuracy loss
A paper accepted at EMNLP 2026 reports that inference-time latent-space interventions made large language models give more consistent answers across languages, including gains in English-Arabic and English-Russian factual question answering, without degrading factual accuracy in the tested settings.