(opens in new tab)<\/span><\/a><\/p>\n\n\n\nIndustry-leading Models<\/h2>\n\n\n\n
The Layout(X)LM series models are leading the way in leveraging large-scale unlabeled data and integrating text and images with multimodal, multi-page, and multilingual content. In particular, the generality and superiority of LayoutLMv3 have made it a benchmark model for Document AI industry research. For example, the Layout(X)LM series models have been adopted by many Document AI products from many leading companies, especially in the Robotic Process Automation (RPA) domain.<\/p>\n\n\n\n
“Microsoft Research Asia has not only achieved significant results in modeling innovation and benchmark datasets but it has also developed many applications that allow users to perform multiple tasks with just one single model architecture. Many colleagues in academia and industry are using Layout(X)LM to conduct meaningful scientific explorations and advancing Document AI,” Lei Cui said.<\/p>\n\n\n\n
Microsoft is leading the way in the field, with a range of Microsoft Research Asia’s Document AI models now being used in many Microsoft-related products, such as Azure Form Recognizer, AI Builder, and Microsoft Syntex. “We are excited to work with these top researchers at Microsoft Research Asia. The Document Foundation Models have greatly improved our development and application efficiency and have contributed to the popularity of Document AI. We look forward to more exciting advances in this area in the future,” said Cha Zhang, Partner Engineering Manager from Microsoft Azure AI.<\/p>\n\n\n\n
Next Step in Document AI: Developing General-purpose and Unified Frameworks<\/h2>\n\n\n\n
Over the course of time, technological advances in Document AI have led to its application in various industries such as finance, healthcare, energy, government services, and logistics, saving people in these industries a lot of time as they can now avoid manual processing. For example, in the financial industry, Document AI enables financial report analysis, intelligent decision analysis, and automated information extraction for invoices and orders; in the healthcare industry, it facilitates case digitization, analyzes the relevance of medical literature and cases, and suggests potential treatment options.<\/p>\n\n\n\n
However, Microsoft Research Asia will not rest on its laurels, Lei Cui indicated. Its researchers are planning to further advance fundamental research in Document AI in three aspects: increasing the scale of models, scaling up training data, and unifying frameworks. “The GPT-3 in NLP demonstrates that large language models can significantly improve performance. The training data for current Document AI models equates to less than one-tenth of web-scale data, so there is still room for improvement. We will focus on scaling up data and models in future research to achieve unification across Document AI frameworks.”<\/p>\n\n\n\n
The Natural Language Computing Group at Microsoft Research Asia is looking for researchers and interns. We welcome people who are interested in this research area or related fields to join us!<\/em><\/p>\n\n\n\nTo apply for a full-time position, please send your resume to <\/em>fuwei@microsoft.com<\/em><\/a>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"Have you ever been overwhelmed by invoices with different pieces of information like payables, dates, quantity of goods, unit prices and amounts? When dealing with essential business contracts, are you worried about getting a decimal point wrong, causing incalculable financial losses? Have you ever read numerous resumes while looking for top talent? Business people have […]<\/p>\n","protected":false},"author":34512,"featured_media":913578,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"msr-content-parent":199560,"footnotes":""},"research-area":[],"msr-locale":[268875],"class_list":["post-913566","msr-blog-post","type-msr-blog-post","status-publish","has-post-thumbnail","hentry","msr-locale-en_us"],"msr_assoc_parent":{"id":199560,"type":"lab"},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/913566"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-blog-post"}],"author":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/users\/34512"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/913566\/revisions"}],"predecessor-version":[{"id":913572,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-blog-post\/913566\/revisions\/913572"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/913578"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=913566"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=913566"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=913566"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}