Papers › Modeling Naive Psychology of Characters in Simple Commonsense Stories
Modeling Naive Psychology of Characters in Simple Commonsense Stories
Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight, Yejin Choi
Understanding a narrative requires reading between the lines and reasoning about the unspoken but obvious implications about events and people's mental states - a capability that is trivial for humans but remarkably hard for machines. To facilitate research addressing this challenge, we introduce a new annotation framework to explain naive psychology of story characters as fully-specified chains of mental states with respect to motivations and emotional reactions. Our work presents a new large-scale dataset with rich low-level annotations and establishes baseline performance on several new tasks, suggesting avenues for future research.
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Emotion Classification | ROCStories | NPN + Explanation Training | F1 | 30.29 | #2 of 2 | Archive leaderboard | report |
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