AI RESEARCH
MIMO: Multilingual Information Retrieval via Monolingual Objectives
arXiv CS.AI
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ArXi:2605.31171v1 Announce Type: cross Multilingual Information Retrieval (MLIR) reflects real-world search environments in which queries and relevant documents may appear in different languages within a mixed-language corpus. However, existing embedding models are primarily optimized for Multi-Monolingual retrieval and their performance often degrades in MLIR settings. Moreover, directly applying conventional contrastive learning to MLIR can exacerbate language clustering and expose a trade-off between cross-lingual alignment and embedding uniformity.