DialDefer - Judgment Accuracy (Factual Framing): leaderboard
DialDefer (Rabbani et al., 2026) asks whether a given answer to a question is correct, over 3,244 items: 2,964 from nine benchmarks (among them TruthfulQA, HaluEval, BBQ, SocialIQA, GPQA and HARP) and 280 Reddit r/AmIOverreacting conflicts labelled by community verdict. Under factual framing the answer is shown as a statement to verify; each item is posed once with a correct and once with an incorrect answer. Accuracy in percent, the mean of true- and false-answer accuracy per domain averaged over the ten domains; higher is better.
Metric: Accuracy (%; factual framing, 'Is this statement correct?': judging whether a given answer is correct, mean of true- and false-answer accuracy per domain, averaged over ten domains, 3,244 items). Source: arxiv.org. Saturation forecast: Estimated already saturated. 5 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5 Mini | 75.6 | #349 |
| 2 | GPT-4o (2024-11-20) | 69.6 | #864 |
| 3 | GPT-4o Mini | 63.6 | #1627 |
| 4 | Gemma 3 12B (IT) | 62.4 | #1849 |
| 5 | Qwen 2.5 7B Instruct | 60.4 | #2583 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=dialdefer-judgment-accuracy-factual-framing · How It Works · Data refreshed daily, snapshot 2026-11-12.