AffectWorld: Benchmarking Emotion-Driven Future World Prediction
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.
ProofPaper ↗
Key points
- The world encompasses both physical environments and human actors.
- Predicting its evolution requires understanding both physical laws and how emotions shape human actions.
- 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.
- AffectWorld provides a testbed for advancing world models that capture how emotions shape future physical and social states.
Sources (1)
- [1]AffectWorld: Benchmarking Emotion-Driven Future World PredictionarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 13, 12:50 PM
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.
The world encompasses both physical environments and human actors.
Extractive summary: sentences quoted from the sources.
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