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"title": "Keynote Talk: Knowledge-infused dialog systems",
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"abstract": "in 2017. Zhou has built various dialog systems that have a real impact, such as a job interview training system, a depression screening system, and a second language learning system. Her research interests include dialog systems, language understanding and generation, vision and language, human-computer interaction, and social robots. Zhou",
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"abstract": [
{
"text": "in 2017. Zhou has built various dialog systems that have a real impact, such as a job interview training system, a depression screening system, and a second language learning system. Her research interests include dialog systems, language understanding and generation, vision and language, human-computer interaction, and social robots. Zhou",
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"section": "Abstract",
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"text": "Welcome to the Second Workshop on Document-grounded Dialogue and Conversational Question Answering (DialDoc) co-located with ACL 2022.",
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"section": "Introduction",
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"text": "Following the exiting outcome for the First DialDoc Workshop co-located at ACL-IJCNLP 2021, we continue the goal and effort to explore document knowledge for information-seeking goal-oriented dialogue systems. There is a vast amount of document content created every day by human writers to communicate with human readers for sharing knowledge, ranging from encyclopedias to customer service FAQs. Making the document content accessible to users via conversational systems and scaling it to various domains could be a meaningful yet challenging task. There are significant individual research threads that show promise in handling heterogeous knowledge embedded in documents for building conversational systems, including (1) unstructured content, such as text passages; (2) semi-structured content, such as tables or lists; (3) multi-modal content, such as images and videos along with text descriptions, and so on. The purpose of the workshop is to invite researchers and practitioners to bring their individual perspectives on the subject of document-grounded dialogue and conversational question answering to advance the field in a community-wise joint effort.",
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"section": "Introduction",
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"text": "Different than the First DialDoc Workshop, we highlight the challenge of the scalability on building information-seeking goal-oriented dialogue systems in this workshop. We also propose a special theme on on scaling up document-grounded dialogue systems especially for low-resource domains, such as minority language support and emerging and unforeseen situations such as COVID-19 pandemic. In addition, for the Shared Task on modeling goal-oriented information-seeking dialogues, one of the tasks is based on the low-resource setting.",
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"section": "Introduction",
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"text": "For the Shared Task competition, it mainly focuses on building open-book goal-oriented informationseeking conversation systems. The task are to generate agent responses based on dialogue history and domain documents, where each dialogue could correspond to multiple grounding documents. It includes two leaderbards based on different settings: the first one (SEEN leaderboard) is that all dialogues in the test data are grounded in the documents from the same domains as the training data; the second one (UNSEEN leaderboard) is that all dialogues in the test data are grounded in the documents from an unseen domain. There are a total of 22 teams that participated in the Dev Phase. For the final Test Phase, 10 teams submitted to the leaderboards. Many submissions outperform baseline significantly. On the SEEN leaderboard, the best-performing system achieved 52.2 F1 comparing to 35.95 by the baseline. On the UNSEEN leaderboard, the best-performing system achieved 34.65 F1 comparing to 19.26 by the baseline.",
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"section": "Introduction",
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"text": "In this workshop, we have the research track and technical system track for Shared Task. There are a total 21 submissions. There are 14 accepted papers in the research track, including 12 long papers and 2 short papers. There are 6 accepted papers in the technical system track. The workshop program features 18 paper presentations either as a poster or oral presentation. We are also fortunate to have invited talks from Jeff Dalton, Michel Galley, Mari Ostendorf, Siva Reddy and Zhou Yu.",
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"section": "Introduction",
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"text": "Finally, we would like thank all people who contributed to this workshop: the authors for their paper submissions, the teams for participating the Shared Task, the program committee members for their fundamental contributions, ACL workshop co-chair for the guidance and the amazing invited speakers. Special thanks to IBM Research for sponsoring the rewards for the Shared Task competition. , and a member of the National Academy of Engineering. For her contributions in spoken language processing, she was awarded the 2018 IEEE James L. Flanagan Speech and Audio Processing Award. In 2017, she served as a faculty advisor for the student team winning the inaugural AlexaPrize competition to build a socialbot, and conversational AI is a focus of her current work. Her research explores dynamic models for understanding and generating speech and text, particularly in multi-party contexts, and it contributes to a variety of applications, including call center analytics, information seeking dialogues, equitable assessments in education, and clinical information extraction.",
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"section": "Introduction",
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"text": "Thursday, May 26, 2022 (continued) xvii",
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"text": "Siva Reddy is an Assistant Professor in the School of Computer Science and Linguistics at McGill University. He is a Facebook CIFAR AI Chair and a core faculty member of Mila Quebec AI Institute. Before McGill, he was a postdoctoral researcher at Stanford University. He received his PhD from the University of Edinburgh in 2017, where he was a Google PhD Fellow. His research focuses on representation learning for language that facilitates systematic generalization, reasoning and conversational modeling. He received the 2020 VentureBeat AI Innovation Award in NLP, and the best paper award at EMNLP 2021. Dr. Jeff Dalton is an Assistant Professor in the School of Computing Science at the University of Glasgow where he leads the Glasgow Representation and Information Learning Lab (GRILL) (https://grilllab.ai). His research focuses on text understanding and conversational information seeking. He completed his Ph.D. at the University of Massachusetts Amherst in the Center for Intelligent Information Retrieval. Later in Google Research, he worked on Information Extraction as part of the Knowledge Discovery Team (Knowledge Vault) and on language understanding in the Assistant Response Ranking team. He is the lead organizer for the TREC Conversational Assistance Track (CAsT) (http://treccast.ai) and previously helped organize the Complex Answer Retrieval track. He is the recipient of a prestigious UKRI Turing AI Acceleration Fellowship on Neural Conversational Assistants and received research awards from Google, Amazon, and Bloomberg. He is the faculty advisor for the 2021/2022 Alexa Prize Taskbot challenge team, GRILLBot. He holds multiple patents in retrieval, information extraction, and question answering. Bio: Mari Ostendorf is an Endowed Professor of System Design Methodologies in the Electrical Computer Engineering Department at the University of Washington and currently serves as UW's Vice Provost for Research. She is a Fellow of the IEEE, ISCA and ACL, a former Australian-American Fulbright Scholar, a member of the Washington State Academy of Sciences, a Corresponding Fellow of the Royal Society of Edinburgh",
"content": "<table><tr><td>Wanjun Zhong, MSRA Xi Chen, Tencent Yifan Gao, The Chinese University of Hong Kong Yekun Chai, Baidu Yinhe Zheng, Alibaba DAMO Academy Yiwei Jiang, Ghent University Yajing Sun, Chinese Academy of Sciences Yunqi Qiu, Chinese Academy of Sciences Keynote Talk: How grounded is document-grounded conversational AI? Siva Reddy McGill University, Facebook CIFAR AI, Mila Quebec AI and Understanding: Current Progress and Future Directions Jeff Dalton University of Glasgow Bio: Keynote Talk: Knowledge-Grounded Conversation Search Bio:</td></tr><tr><td>Yosi Mass, IBM Research</td></tr><tr><td>Yutao Zhu, University of Montreal</td></tr><tr><td>Zheng Zhang, Tsinghua University</td></tr><tr><td>Zhenyu Zhang, Chinese Academy of Sciences</td></tr><tr><td>Zhenzhong Lan, Westlake University</td></tr><tr><td>Zhixing Tian, JD</td></tr><tr><td>Song, Chengguang, Ellen, Hui, Caixia, Svitlana</td></tr></table>",
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