LLMbench: A Comparative Close Reading Workbench for Large Language Models
2026-04-20T07:23:52Z•32c2cf24d37799949127b2ca6421c0d820f53928622ada810ef573a95d2a5f80
AI ethicsAI governanceLLM evaluationPolymarketUMAaccessibility as defenseanthropomorphic deceptiondark patternsdelayed ground truthdrift detectionhuman-AI interactionlarge language modelslog-probability analysismodel interpretabilityon-chain dispute resolutionprediction marketsprivacy & health AIprobability visualizationproxy monitoring
What happened
This RSS batch (arXiv CS & related fields) collects new 2026 papers on LLM tooling, governance, monitoring, and ethics. Highlights: LLMbench — a browser workbench exposing token-level log-probabilities, diffs, tone, and structure to support close comparative reading of model outputs; a study showing web-enabled LLMs reach 89.58% agreement with UMA on-chain dispute resolutions but cannot reliably predict which markets will be disputed in advance; an evidence-sufficiency model and proxy-monitoring framework for systems operating with delayed ground truth that reliably detects covariate/mixed dr`
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- 32c2cf24d37799949127b2ca6421c0d820f53928622ada810ef573a95d2a5f80
- Enrichment time
- 2026-04-20T07:23:52Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.