{"id":493928,"date":"2018-07-05T22:56:59","date_gmt":"2018-07-06T05:56:59","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=493928"},"modified":"2020-02-04T15:06:39","modified_gmt":"2020-02-04T23:06:39","slug":"neural-approaches-to-conversational-ai","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/neural-approaches-to-conversational-ai\/","title":{"rendered":"Neural Approaches to Conversational AI – Tutorial at ACL\/SIGIR 2018"},"content":{"rendered":"
This tutorial surveys neural approaches to conversational AI that were developed in the last few years. We group conversational systems into three categories: (1) question answering agents, (2) task-oriented dialogue agents, and (3) social bots. For each category, we present a review of state-of-the-art neural approaches, draw the connection between neural approaches and traditional symbolic approaches, and discuss the progress we have made and challenges we are facing, using specific systems and models as case studies.<\/p>\n","protected":false},"excerpt":{"rendered":"
This tutorial surveys neural approaches to conversational AI that were developed in the last few years. We group conversational systems into three categories: (1) question answering agents, (2) task-oriented dialogue agents, and (3) social bots. For each category, we present a review of state-of-the-art neural approaches, draw the connection between neural approaches and traditional symbolic […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-493928","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2018-7-5","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"ACL and SIGIR tutorial","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"https:\/\/1drv.ms\/p\/s!AshEqwB44aR6k8wgo9s-Jk3-A8ZiaQ","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/1drv.ms\/p\/s!AshEqwB44aR6k8wgo9s-Jk3-A8ZiaQ","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":0,"url":"https:\/\/1drv.ms\/p\/s!AshEqwB44aR6k8wgo9s-Jk3-A8ZiaQ"}],"msr-author-ordering":[{"type":"user_nicename","value":"Jianfeng Gao","user_id":32246,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Jianfeng Gao"},{"type":"user_nicename","value":"Michel Galley","user_id":32887,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Michel Galley"},{"type":"text","value":"Lihong Li","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[144736],"msr_project":[171447],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":171447,"post_title":"Data-Driven Conversation","post_name":"data-driven-conversation","post_type":"msr-project","post_date":"2015-03-19 17:13:58","post_modified":"2019-08-19 10:40:23","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/data-driven-conversation\/","post_excerpt":"This project aims to enable people to converse with their devices. We are trying to teach devices to engage with humans using human language in ways that appear seamless and natural to humans. Our research focuses on statistical methods by which devices can learn from human-human conversational interactions and can situate responses in the verbal context and in physical or virtual environments. 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