Impact of Scaling Hybrid Batch Training on Zero-Shot Cross-Modal Retrieval Performance in Large Multimodal Models - Assignee Research (Assignee Research, 2026)
Information retrieval across different languages is an increasingly important challenge in natural language processing. Recent approaches based on multilingual pre-trained language models have achieved remarkable success, yet they often optimize for either monolingual, cross-lingual, or multilingual retrieval performance at the expense of others. This paper proposes a novel hybrid batch training strategy to simultaneously improve zero-shot retrieval performance across monolingual, cross-lingual,
Machine-generated literature synthesis.