{"id":1115469,"date":"2025-01-02T10:42:24","date_gmt":"2025-01-02T18:42:24","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-video&p=1115469"},"modified":"2025-01-06T10:32:18","modified_gmt":"2025-01-06T18:32:18","slug":"accelerating-multilingual-rag-systems","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/accelerating-multilingual-rag-systems\/","title":{"rendered":"Accelerating Multilingual RAG Systems"},"content":{"rendered":"
As Retrieval-Augmented Generation (RAG) systems gain prominence for grounding large language models (LLMs) in external knowledge, constructing evaluation frameworks is critical in accelerating developments across multiple diverse languages. This talk introduces a comprehensive multilingual RAG evaluation pipeline comprising three key components: retrieval, relevance assessment, and generation. MIRACL, a multilingual retrieval dataset with high-quality relevance judgments annotated by native speakers; NoMIRACL, a benchmark for assessing relevance in multilingual RAG, designed to measure LLM robustness against retrieval errors; and MIRAGE-Bench, an arena-based multilingual RAG evaluation framework integrating both heuristic metrics and surrogate judge models for multilingual generation evaluation. Together, these resources provide a foundation for advancing multilingual information access and enhancing the robustness of RAG systems. This talk highlights key findings from each section, challenges, and future work for multilingual RAG research.<\/p>\n","protected":false},"excerpt":{"rendered":"
As Retrieval-Augmented Generation (RAG) systems gain prominence for grounding large language models (LLMs) in external knowledge, constructing evaluation frameworks is critical in accelerating developments across multiple diverse languages. This talk introduces a comprehensive multilingual RAG evaluation pipeline comprising three key components: retrieval, relevance assessment, and generation. MIRACL, a multilingual retrieval dataset with high-quality relevance judgments […]<\/p>\n","protected":false},"featured_media":1115472,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556,13563,13545,13554,13560,13555],"msr-video-type":[],"msr-locale":[268875],"msr-post-option":[269148,269142],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-1115469","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-research-area-data-platform-analytics","msr-research-area-human-language-technologies","msr-research-area-human-computer-interaction","msr-research-area-programming-languages-software-engineering","msr-research-area-search-information-retrieval","msr-locale-en_us","msr-post-option-approved-for-river","msr-post-option-include-in-river"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/usvu6Sk1ynk","msr_secondary_video_url":"","msr_video_file":"http:\/\/0","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/1115469","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/1115469\/revisions"}],"predecessor-version":[{"id":1115475,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/1115469\/revisions\/1115475"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/1115472"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1115469"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1115469"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=1115469"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1115469"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=1115469"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1115469"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=1115469"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}