LKM2024:
1st International OpenKG Workshop on
Large Knowledge-enhanced Models
In conjunction with the IJCAI 2024,
the 33rd International Joint Conference on Artificial Intelligence
Room 2F-Room 202A,
International Convention Center Jeju (ICC Jeju)
Jeju Island, South Korea
, August 3, 2024
(
http://lkm2024.openkg.org/
)
Overview
OpenKG和Data Intelligence期刊在今年的IJCAI (CCF A类会议）上联合组织关于“Large Knowledge-enhanced Models”的专题研讨会，探索大模型知识增强的基本方法、前沿技术与实践应用。本次研讨会总计录用了来自中国、美国、日本、韩国、澳大利亚等多个国家的28篇投稿论文，
并邀请了来自得克萨斯大学奥斯汀分校、同济大学、清华大学、宾夕法尼亚州立大学、Google DeepMind、东南大学、北京邮电大学、新加坡国立大学等学术界和产业界学者的共2个Keynotes和5个Invited Talks，并包含有8个Spotlight Oral论文报告，以及20篇Poster论文展示。欢迎参会共同研讨，期待8月3日相聚韩国济州岛。
本次研讨会同时有在线直播，并提供实时翻译，欢迎预约观看。
Schedule
注意：程序册时间为韩国济州岛当地时间，北京时间对应提前一小时
KeyNote1：LLM and KG: where are the future of KGs in the era of LLM
Ying Ding
University of Texas at Austin
Dr. Ying Ding is Bill & Lewis Suit Professor at School of Information, University of Texas at Austin. She co-chairs AI in Health Lab at School of Information and Dell Medical School at UT Austin. Before that, she was a professor and director of graduate studies for data science program at School of Informatics, Computing, and Engineering at Indiana University. She has led the effort to develop the online data science graduate program for Indiana University. She also worked as a senior researcher at Department of Computer Science, University of Innsburck (Austria) and Free University of Amsterdam (the Netherlands). She has been involved in various NIH, NSF and European-Union funded projects. She has published 240+ papers in journals, conferences, and workshops, and served as the program committee member for 200+ international conferences. She is the co-editor of book series called Semantic Web Synthesis by Morgan & Claypool publisher, the co-editor-in-chief for Data Intelligence published by MIT Press and Chinese Academy of Sciences, and serves as the editorial board member for several top journals in Information Science and Semantic Web. She is the co-founder of Data2Discovery company advancing cutting edge AI technologies in drug discovery and healthcare. Her current research interests include AI in Healthcare, Semantic Web, knowledge Graph, Data Science, and Science of Science.
KeyNote2：Theoretical Innovations And New Research Paradigms Of Knowledge Graphs In The Era Of Large Language Models
Haofen Wang
Tongji University
Dr. Haofen Wang is a Distinguished Researcher and Ph.D. supervisor under the "100 People Plan" at Tongji University. He is one of the initiators of OpenKG, the world's largest alliance for Chinese open knowledge graphs. He has participated in and led several national-level AI-related projects, published over 100 high-level papers in the AI field with more than 3,900 citations and an H-index of 29. He developed the world's first interactive virtual idol—"Amber Xuyan." Additionally, the intelligent customer service robots he built have served over 1 billion users. Currently, he holds several social positions including Vice Chairman of the Terminology Committee of the Chinese Computer Federation (CCF), Secretary-General of the Natural Language Processing Society, Director of the Chinese Information Society of China, Executive Committee member of the Large Model Committee, Deputy Secretary-General of the Language and Knowledge Computing Committee, and Deputy Director of the Natural Language Processing Committee of the Shanghai Computer Society.
Invited Talk1：LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing
Dr. Yin is an Assistant Professor in the Department of Computer Science and Engineering at Penn State University, USA. Prior to joining PSU, he was a Postdoctoral Researcher with the University of Pennsylvania and as a Senior Research Scientist with Salesforce Research. His research interests include natural language processing, multimodality, and human-centered AI.
Invited Talk2：Advancements in Large Language Model Summarization for Decision-Making and Knowledge Updating
Yichao Zhou
Google DeepMind
Dr. Yichao Zhou is a senior researcher at Google DeepMind, specializing in natural language processing and information extraction. He earned his Ph.D. in Computer Science from the University of California, Los Angeles, under the mentorship of Prof. Wei Wang. Dr. Zhou's research spans various areas, including incremental and contrastive summarization, document understanding, and knowledge extraction from web documents. His research is dedicated to pioneering advancements in structured knowledge representation and updating, aiming to enhance the precision and efficiency of retrieval augmented generation in the LLM era.
Invited Talk3：Knowledge-Aware Parsimony Learning: A Perspective from Relational Graphs
Quanming Yao
Tsinghua University
Dr. Quanming Yao currently is a tenure-track assistant professor at Department of Electronic Engineering, Tsinghua University. Before that, he spent three years from a researcher to a senior scientist in 4Paradigm Inc, where he set up and led the company's machine learning research team. He obtained his Ph.D. degree at the Department of Computer Science and Engineering of Hong Kong University of Science and Technology (HKUST). He has published 80+ top conference and journal papers (including Nature Series / JMLR / IEEE TPAMI / ICML / NeurIPS / ICLR), with more than 10000 citations. He regularly serves as area chairs for ICML, NeurIPS and ICLR. He is a receipt of New Faculty Highlights (AAAI), Aharon Katzir Young Investigator Award (INNS), Forbes 30 Under 30 (China), Young Scientist Awards (Hong Kong Institution of Science), and Google Fellowship (in machine learning).
Invited Talk4：Towards Graph Foundation Models
Dr. Cheng Yang is an Associate Professor of Computer Science at Beijing University of Posts and Telecommunications (BUPT). He received his Bachelor and Ph.D. degrees from Tsinghua University in 2014 and 2019, respectively. Cheng's research interests include data mining, natural language processing and social computing. He has published 60+ papers in top journals and conferences, such as IEEE TKDE, ACM TOIS, KDD, WWW, NeurIPS and ACL. His work has got more than 10,000 citations as shown by Google Scholar. Cheng is named by Baidu as one of the Top 100 Chinese Young Scholars in Artificial Intelligence.
Invited Talk5：Label Enhancement Learning for Complex Semantic and Its Applications on Large Language Models
