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KGLLM 2024 : Special session on Knowledge Graphs and Large Language Models | |||||||||||
Link: https://www.icnlsp.org/2024welcome/#special_session | |||||||||||
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Call For Papers | |||||||||||
** SUBMISSION DEADLINE EXTENDED : 08 July 2024 **
---------------------------------------------------------------- The Special session on Knowledge Graphs and Large Language Models will be held Within the 7th International Conference on Natural Language and Speech Processing (ICNLSP 2024) on October 19, 2024. ** DESCRIPTION ** “In recent years, the fields of Knowledge Graphs (KGs) and Large Language Models (LLMs) have witnessed remarkable advancements, revolutionizing the landscape of artificial intelligence and natural language processing. KGs, structured representations of knowledge, and LLMs, powerful language models trained on vast amounts of text data, have individually demonstrated their prowess in various applications. However, the integration and synergy between KGs and LLMs have emerged as a new frontier, offering unprecedented opportunities for enhancing knowledge representation, understanding, and generation. This integration not only enriches the semantic understanding of textual data but also empowers AI systems with the ability to reason, infer, and generate contextually relevant responses. ** TOPICS ** This special session aims to delve into the theoretical foundations, historical perspectives, and practical applications of the fusion between Knowledge Graphs and Large Language Models. We invite contributions that explore the following areas: 1- Theoretical Frameworks: Papers elucidating the theoretical underpinnings of integrating KGs and LLMs, including methodologies, algorithms, and models for knowledge-enhanced language understanding and generation. 2- Historical Perspectives: Insights into the evolution of KGs and LLMs, tracing their development trajectories, seminal works, and transformative milestones leading to their integration. 3- Design and Implementation: Research articles focusing on the design principles, architectures, and techniques for effectively combining KGs and LLMs to facilitate tasks such as information retrieval, question answering, knowledge inference, and natural language understanding. 4- Explanatory Capabilities: Explorations into how the fusion of KGs and LLMs enables the development of explainable AI systems, providing transparent and interpretable insights into model decisions and outputs. 5- Human-Centered Intelligent Systems: Studies examining the design and deployment of interactive AI systems that leverage KGs and LLMs to facilitate seamless human- computer interaction, catering not only to experts but also to a broader lay audience. We encourage submissions that contribute to advancing our understanding of the synergistic relationship between Knowledge Graphs and Large Language Models, fostering interdisciplinary collaborations across computer science, artificial intelligence, linguistics, cognitive science, and beyond. By shedding light on this burgeoning area of research, this special session aims to propel the field forward and inspire future innovations in AI-driven knowledge representation and natural language processing.” ** SESSION ORGANIZERS ** Gérard Chollet, CNRS-SAMOVAR Institut Polytechnique de Paris, France. Hugues Sansen, Institut Polytechnique de Paris, France. ** IMPORTANT DEADLINES ** Submission deadline: 30 June 2024 11:59 PM (GMT) Notification of acceptance: 15 September 2024 Camera-ready paper due: 25 September 2024 ** PUBLICATION ** The accepted papers will be included in the Conference proceedings which will be published in ACL anthology. The extended versions will be published in a special issue of the Machine Learning and Knowledge Extraction Journal (MAKE), indexed in Web of Science, Scopus, etc. |
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