外观
论文arXiv 2610.1830515 天前
AffectWorld：评测情绪驱动的未来世界预测
原文链接：AffectWorld: Benchmarking Emotion-Driven Future World Prediction（arXiv 2610.18305 · 发布日期：2026-10-13）
AffectWorld: Benchmarking Emotion-Driven Future World Prediction
AffectWorld通过情绪-动作-世界状态三任务，评测日常视频中情绪驱动的未来世界预测。
核心要点
- 现有世界模型基准多关注物理合理性和感知质量，较少测试情绪驱动演化。
- AffectWorld评估Emotion-Action-World State链，包含三项一致性任务。
- 基准含1,498个日常视频样本，并设233个反事实样本测试情绪改变影响。
- 对五个SoTA世界模型的评估显示，其情绪驱动后果生成与适应仍有明显差距。
验证范围与局限：验证范围为日常视频样本、反事实子集和五个SoTA世界模型评测。
英文摘要 (Abstract)
The world encompasses both physical environments and human actors. Predicting its evolution requires understanding both physical laws and how emotions shape human actions. However, existing world model benchmarks primarily assess physical plausibility and perceptual quality, leaving emotion-driven world evolution largely untested.We introduce AffectWorld, a benchmark that evaluates the chain Emotion-Action-World State through three tasks: World-State Consistency, Emotion-Action Consistency, and Causal Consistency. It comprises 1,498 everyday video samples annotated with plausible emotions, action tendencies, and atomic world-state constraints. A counterfactual subset of 233 samples tests whether changing an agent's emotion under fixed scene and event conditions yields corresponding changes in actions and consequences. We define eight metrics across the three tasks and an additional counterfactual metric, combining automatic visual assessment with human-calibrated VLM/LLM judgments. Evaluations of five SoTA world models (e.g., Cosmos3) required world-state change scores of 0.100-0.280 and counterfactual emotion sensitivity scores of 0.027-0.070 on a [0, 1] scale. These results reveal substantial gaps in generating the consequences of emotion-driven actions and adapting future predictions to emotional interventions. AffectWorld provides a testbed for advancing world models that capture how emotions shape future physical and social states.
作者：Changhao Song, Yacong Chen, Hui Gao, Yazhou Zhang, Peng Zhang
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