arXiv (OAI)
open access
Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models
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
- Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models#177037
- Hierarchical Group-Conditional Conformal Risk Control for Selective Prediction in Language Models#405700
- Do Large Language Models Capture the Diversity in their Training Data?#924174
- Do Large Language Models Capture the Diversity in their Training Data?#919943
- Advantageous Parameter Expansion Training Makes Better Large Language Models#670342
Record · ID 176995
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