MIMO: Multilingual Information Retrieval via Monolingual Objectives

• URL: http://arxiv.org/abs/2605.31171v1
• Date: Fri, 29 May 2026 11:34:15 GMT
• Title: MIMO: Multilingual Information Retrieval via Monolingual Objectives
• Abstract summary: Existing embedding models are primarily optimized for Multi-Monolingual retrieval.<n>Milo is a two-stage framework that uses a stable English semantic space from a high-performing teacher model as an anchor.<n>Milo consistently outperforms existing cross-lingual training baselines.
• Score: 22.085658351797765
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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. To address these limitations, we propose MIMO: Multilingual Information Retrieval via Monolingual Objectives, a two-stage framework that uses a stable English semantic space from a high-performing teacher model as an anchor. MIMO first initializes the student model's cross-lingual alignment through knowledge distillation, and then jointly optimizes distillation and cross-lingual contrastive learning to improve retrieval discrimination while preserving alignment. Extensive experiments show that MIMO consistently outperforms existing cross-lingual training baselines across various MLIR and Multi-Monolingual benchmarks. MIMO also remains competitive with off-the-shelf models of similar or larger parameter scales. Furthermore, our cross-lingual Alignment-Uniformity analysis clarifies the distinct roles of the two loss components and shows that their combination yields a favorable trade-off between alignment and uniformity.

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