arXiv (All)
open access
From Policy Documents to Structured Survey Responses: Evaluating Large Language Models for Policy Monitoring
Science, technology, and innovation policies are crucial for competitiveness, yet their diversity and scale make them difficult to map and monitor consistently. Existing approaches rely heavily on manual survey efforts, which are costly and challenging to scale across countries. Large language model
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning#328707
- Do large language models scrutinise what they review? A multimodal audit of scoring calibration, error detection, and author-identity effects#792877
- Do large language models scrutinise what they review? A multimodal audit of scoring calibration, error detection, and author-identity effects#788873
- A golden era for open-ended questions? Using LLMs to scale the qualitative coding of open-ended survey responses#1169193
- A golden era for open-ended questions? Using LLMs to scale the qualitative coding of open-ended survey responses#1168989
Record · ID 1077299
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive