SPIN Unprocessed October 26, 2026 ai_technology research
Knowledge Graphs Quality Assessment in the Era of LLMs: A Conceptual Framework
View original on arxiv.orgOverview
arXiv:2610.31684v1 Announce Type: new Abstract: Knowledge Graphs (KGs) have been popularized during the last few decades and are increasingly constructed and consumed by Large Language Models (LLMs). Various applications therefore rely on KGs to provide concise, complete, accurate, faithful, fresh, and traceable answers. However, what is the quality of those KGs? In which cases should a KG be used, and can it be trusted to ground an LLM? How might it be evaluated? We reviewed the literature on q
SpinGraph analysis pending — check back after processing.
Ask AI about this story
Opens with the SpinGraph .md URL and structured context — one click, prompt included.
More from arXiv Computation and Language
View all →- Each Insufficient in Its Own Way: Calibrating Language Models Across Varying Evidence States
- Position, Role or Label? A Controlled Study of Instruction Conflicts in LLM Agents
- Parametric Session States Recover Retrieval Intent without Replaying History
- EviGround-CT: Sentence-to-Volume Grounding for Verifying LLM-Generated Chest CT Reports
- A Benchmark for Controllable Speaking-Style Captioning in Audio-Language Models
- Conceptizer: Next-Token Prediction Is Not All You Need
Markdown (.md) · JSON-LD schema (.json) · Machine-readable for AI & GEO