Results 31 to 40 of about 7,092,434 (358)
Knowledge graph-enhanced molecular contrastive learning with functional prompt
Nature Machine Intelligence, 2023 Deep learning models can accurately predict molecular properties and help making the search for potential drug candidates faster and more efficient.
Yin Fang +7 more
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LLM-assisted Knowledge Graph Engineering: Experiments with ChatGPT [PDF]
AI Tomorrow, 2023 Knowledge Graphs (KG) provide us with a structured, flexible, transparent, cross-system, and collaborative way of organizing our knowledge and data across various domains in society and industrial as well as scientific disciplines.
Lars-Peter Meyer +8 more
semanticscholar +1 more source
A type-augmented knowledge graph embedding framework for knowledge graph completion
Scientific Reports, 2023 Knowledge graphs (KGs) are of great importance to many artificial intelligence applications, but they usually suffer from the incomplete problem.
Peng He +4 more
doaj +1 more source
Frontiers in Big Data, 2023 The knowledge graph is one of the essential infrastructures of artificial intelligence. It is a challenge for knowledge engineering to construct a high-quality domain knowledge graph for multi-source heterogeneous data.
Chenwei Yan +6 more
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MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models [PDF]
Annual Meeting of the Association for Computational Linguistics, 2023 Large language models (LLMs) have achieved remarkable performance in natural language understanding and generation tasks. However, they often suffer from limitations such as difficulty in incorporating new knowledge, generating hallucinations, and ...
Yilin Wen, Zifeng Wang, Jimeng Sun
semanticscholar +1 more source
ChatGPT versus Traditional Question Answering for Knowledge Graphs: Current Status and Future Directions Towards Knowledge Graph Chatbots [PDF]
arXiv.org, 2023 Conversational AI and Question-Answering systems (QASs) for knowledge graphs (KGs) are both emerging research areas: they empower users with natural language interfaces for extracting information easily and effectively.
Reham Omar +3 more
semanticscholar +1 more source
IEEE Access, 2022 In recent years, although the application of knowledge graph in natural language processing has made some progress, there are still some key problems to be solved, especially the matching query problem in natural language knowledge graph. Since the basic
Qifeng Zou, Chaoze Lu
doaj +1 more source
Knowledge Graph Quality Management: A Comprehensive Survey
IEEE Transactions on Knowledge and Data Engineering, 2023 As a powerful expression of human knowledge in a structural form, knowledge graph (KG) has drawn great attention from both the academia and the industry and a large number of construction and application technologies have been proposed.
Bingcong Xue, Lei Zou
semanticscholar +1 more source
Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation [PDF]
arXiv.org, 2023 Language models have achieved impressive performances on dialogue generation tasks. However, when generating responses for a conversation that requires factual knowledge, they are far from perfect, due to an absence of mechanisms to retrieve, encode, and
Minki Kang +3 more
semanticscholar +1 more source
Towards Foundation Models for Knowledge Graph Reasoning [PDF]
International Conference on Learning Representations, 2023 Foundation models in language and vision have the ability to run inference on any textual and visual inputs thanks to the transferable representations such as a vocabulary of tokens in language.
Mikhail Galkin +4 more
semanticscholar +1 more source