interpretability ↔ Large Language Models

Relations (1)

related 1.58 — strongly supporting 2 facts

Large Language Models are related to interpretability because research aims to improve their logical consistency and reasoning through integration with Knowledge Graphs [1], and interpretability is a key metric used to evaluate the reliability and truthfulness of these models [2].

Facts (2)

Sources

Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org arXiv 1 fact

claimZhang et al. (2023) identified reliability in LLMs by examining tendencies regarding hallucination, truthfulness, factuality, honesty, calibration, robustness, and interpretability.

LLM-empowered knowledge graph construction: A survey - arXiv arxiv.org arXiv 1 fact

claimFuture research in Large Language Models (LLMs) and Knowledge Graphs (KGs) is expected to focus on integrating structured KGs into LLM reasoning mechanisms to enhance logical consistency, causal inference, and interpretability.