arXiv (All)
open access
On Epistemic Diversity in Large Language Models
Large language models (LLMs) are increasingly used not only to retrieve information, but to answer questions, explain, teach, and support inquiry. In such settings, evaluation cannot be exhausted by accuracy or alignment alone. A system may give a correct answer while still narrowing users' access %
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
- A Zeroth-Order Paradigm for LLM Preference Alignment#1013346
- A Zeroth-Order Paradigm for LLM Preference Alignment#965397
- From Echo Chambers to Epistemic Monoculture: Large Language Models Present Temporally Contingent Partisan Alignments as Knowledge#984636
- Embedding qualitative data in LLM semantic space: A tutorial on conceptualization, measurement, and validation#1054851
- Embedding qualitative data in LLM semantic space: A tutorial on conceptualization, measurement, and validation#1040333
Record · ID 971500
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