ALLMTS Raw LLM - 566 - Ad Hoc Urgency Accuracy: leaderboard
ALLMTS paper v1 raw-LLM standalone baseline only, Azure Responses GPT-5.2 low effort. No guideline retrieval/execution, web search or ALLMTS system scores attributed to the model. 50curated or566full synthetic expert-validated scenarios are distinct cohorts. Ad-hoc views prompt direct labels; post-hoc views map predicted disposition labels. Nativefraction accuracy/support-weightedF1 higherisbetter; under/over-triagefractions lowerisbetter. Different labeltaxonomies remain separate. 566scenarios; Ad Hoc Urgency; Accuracy. Metric: Accuracy (0-1).
Metric: Accuracy (0-1). Source: arxiv.org. 1 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.2 (low) | 0.56 | #115 (GPT-5.2) |
Interactive version: theaggregate.ai/benchmark?slug=allmts-raw-llm-566-ad-hoc-urgency-accuracy · How It Works · Data refreshed daily, snapshot 2026-10-27.