Knowledge Tree
Relations (1)
related 2.58 — strongly supporting 5 facts
Large Language Models are directly linked to decision-making as they serve as the backbone for intelligent agents [1], facilitate medical and enterprise QA {fact:2, fact:3}, provide insights for financial risk assessment [2], and are actively evaluated for their reasoning and decision-making capabilities [3].
Facts (5)
Sources
Bridging the Gap Between LLMs and Evolving Medical Knowledge arxiv.org 1 fact
claimThe Medical Knowledge Graph (MKG) is designed to be both human-readable and usable by advanced LLMs, serving as a tool for medical QA and decision-making.
Practices, opportunities and challenges in the fusion of knowledge ... frontiersin.org 1 fact
referenceFinDKG, as described by Li (2023), utilizes Large Language Models to extract information from financial reports, news, and transaction records to provide insights for risk assessment and decision-making.
A Survey of Incorporating Psychological Theories in LLMs - arXiv arxiv.org 1 fact
measurementCognitive development and reasoning capabilities in Large Language Models have been assessed through cognitive maturity (Laverghetta Jr. & Licato, 2022), subjective similarity (Malloy et al., 2024), reasoning strategies (Mondorf & Plank, 2024; Yuan et al., 2023), decision-making (Ying et al., 2024), and Theory of Mind (Jung et al., 2024).
How NebulaGraph Fusion GraphRAG Bridges the Gap Between ... nebula-graph.io 1 fact
claimIntegrating Large Language Models with Knowledge Graphs enables applications to move beyond basic retrieval toward reliable, contextual, and proactive decision-making, addressing the requirements of enterprise AI.
The Integration of Symbolic and Connectionist AI in LLM-Driven ... econpapers.repec.org 1 fact
claimLarge Language Models (LLMs) exhibit traits of both symbolic and connectionist paradigms and can serve as the backbone for integrating these approaches to improve decision-making, natural language understanding, and autonomy in intelligent agents.