Agentic GraphRAG constructs a Neo4j graph via deterministic structured ingestion plus LLM extraction from notices, then deploys modular agents with tool access and reflection to outperform vector-RAG baselines on Swiss commercial gazette data across entity resolution, answer quality, and multi-turn
Necessary but Not Perfect: Changes in AI Perception at a Large University
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A pilot mixed-methods study at one university uses surveys and pre/post-LLM grade data to document patterns in faculty course design and student learning outcomes after generative AI release.
citing papers explorer
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Agentic GraphRAG: Navigating Unstructured Financial Data with Collaborative AI
Agentic GraphRAG constructs a Neo4j graph via deterministic structured ingestion plus LLM extraction from notices, then deploys modular agents with tool access and reflection to outperform vector-RAG baselines on Swiss commercial gazette data across entity resolution, answer quality, and multi-turn
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Measuring Changes in Instructor Class Design and Student Learning After the Release of Large Language Models (LLMs)
A pilot mixed-methods study at one university uses surveys and pre/post-LLM grade data to document patterns in faculty course design and student learning outcomes after generative AI release.