Knowledge Reasoning

Knowledge reasoning focuses on enabling artificial intelligence systems to derive new knowledge from existing information, mirroring human cognitive abilities. Current research emphasizes integrating diverse knowledge sources, such as knowledge graphs and unstructured text, into large language models (LLMs) and other architectures, often employing techniques like chain-of-thought prompting, multi-agent collaboration, and knowledge graph embedding methods to improve reasoning accuracy and explainability. This field is crucial for advancing AI capabilities in various applications, including question answering, medical diagnosis, and decision support systems, by enhancing the reliability and trustworthiness of AI-driven inferences.