arXiv (All)
open access
VERA: Verdict-Conditioned Reliability for Adaptive LLM Judges
Accurately estimating judgment reliability is a central challenge in adapting LLM judges to newly verified feedback while preserving previously learned behavior. However, existing approaches often rely on output-level confidence, which can be overconfident and poorly aligned with judgment correctnes
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
- CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation#986205
- From IR to RecSys: Evaluating LLM-based Judges in Cranfield-style Recommendation Collections#617902
- From IR to RecSys: Evaluating LLM-based Judges in Cranfield-style Recommendation Collections#617402
- Knowing When to Critique: Task-Adaptive Metacognitive Regulation for Reliable LLM Reasoning#1118403
- The Lifecycle of LLM-as-a-Judge for Large-Scale Recommendation Explanations#819452
Record · ID 1201465
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