构建卢森堡语文档跨语言图文检索基准，验证图像检索优于文本检索。
LëtzCross: A Cross-Lingual Page-Level Benchmark for Multimodal Retrieval over Luxembourgish Documents
- 以卢森堡语文档图像为索引，支持多语言查询的跨语言检索评测
- 图像检索模型在所有语言上表现均优于传统文本检索方法
- 多语言微调中加入卢森堡语显著提升本地查询效果，适合小语种研究者
近年来，如ColPali等页面图像检索器在视觉丰富的文档检索中取得进展，但在跨语言、低资源场景下的表现仍不明确。本文提出LëtzCross，一个面向卢森堡语PDF文档的跨语言页面级检索基准，将文档页面作为图像索引，查询语言包括英语、法语、德语和卢森堡语。该基准融合文本导向与视觉对齐的问答对，覆盖基于PDF的RAG中的文本与视觉检索需求。通过LëtzCross对比基于OCR的文本检索器与ColPali风格的页面图像检索器，发现后者在所有查询语言下表现更优。此外，评估了单语言与多语言微调策略：单语言微调中，法语设置在卢森堡语查询上达到最高平均性能；多语言微调中，包含卢森堡语时结果最佳，显著提升卢森堡语查询的检索效果。
原文摘要 · Abstract (English)
Recent page-image retrievers such as ColPali have improved retrieval over visually rich documents, yet little is known about how they behave in cross-lingual, low-resource settings. We introduce LëtzCross, a benchmark for cross-lingual page-level retrieval over Luxembourgish PDF documents, with document pages indexed as images and queries provided in English, French, German, and Luxembourgish. The benchmark combines text-focused QA pairs with visually grounded QA pairs, covering both textual and visual retrieval needs in PDF-based RAG. We use LëtzCross to compare OCR-based text-only retrievers with ColPali-style page-image retrievers and find that the latter perform better across query languages in this system-level comparison. We also examine single-language and multilingual fine-tuning. Fine-tuning transfers across query languages, with French yielding the highest mean performance on Luxembourgish queries among the single-language settings. In the multilingual setting, including Luxembourgish gives the strongest results and substantially improves retrieval for Luxembourgish queries.
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