AffToM - Factual Consistency: leaderboard
Video-based recursive affective theory-of-mind questions across individual and multiparty social interactions. GPT-5-mini rubric mean (1–5). AffToM v1 Table2,1822MCQs plus100open-ended questions from258videos; temperature0 and64uniformframes unless source exception. Native base models and separately trained AffToM-R1 remain distinct. MCQ exact accuracy in%; open answers graded by GPT-5-mini on1–5 Emotion Correctness/Factual Consistency rubrics. Human250-question reference retained in source pins but not emitted as a model. Different LLaVA-OneVision1.5 parameter sizes stay distinct.
Metric: GPT-5-mini rubric mean (1–5). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 23 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.5 (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 2.99 | |
| 2 | Qwen 3.5 27B (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 2.23 | |
| 3 | Qwen 3 VL 32B Instruct (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.96 | |
| 4 | Qwen 2.5 VL 72B Instruct (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.95 | |
| 5 | AffToM-R1 (Qwen3.5-4B) (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.89 | |
| 6 | Seed 2.0 Lite (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.88 | |
| 7 | InternVL3.5-38B (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.76 | |
| 8 | Qwen 3 VL 8B Instruct (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.7 | |
| 9 | InternVL3.5-14B (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.62 | |
| 10 | LLaVA-OneVision-1.5 8B (Benchmark Sweep Run: source=AffToM; temperature0; video64uniformframes; native Table2 checkpoint; no subtitle ablation) | 1.61 |
Interactive version: theaggregate.ai/benchmark?slug=afftom-factual-consistency · How It Works · Data refreshed daily, snapshot 2026-11-06.