Papers by Haiqi Zhou
Fiction Flows: A Replication and Reinterpretation of Narrative Sequentiality (2026.acl-long)
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| Challenge: | a new study shows that imagined narratives exhibit higher "flow" than recalled narratives, but this advantage is not reducible to standard coherence measures. |
| Approach: | They propose a language-model-based measure of sentence-level predictability to measure narrative flow . they find that imagined stories flow better than recalled ones . |
| Outcome: | The proposed measure of sentence-level predictability is based on language models . it shows that fiction exhibits a robust sequentiality advantage over reality-bound genres . |
Story Morals: Surfacing value-driven narrative schemas using large language models (2024.emnlp-main)
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| Challenge: | Using large language models, we extract and validate story morals across a diverse set of narrative genres. |
| Approach: | They propose a task of narrative schema labelling based on the concept of "story morals" they use large language models to extract and validate story morals across a diverse set of genres . |
| Outcome: | The proposed method extracts and validates story morals across folktales, novels, movies and TV, personal stories from social media and the news using automated metrics and human assessments. |
Exploring and Distilling Multi-Dimensional Clues for Interpretable Social Bot Detection (2026.acl-long)
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| Challenge: | Existing research on social bot detection results directly without corresponding supportive explanations, making it difficult to assess the extent to which such predictions are trustworthy. |
| Approach: | They propose a four-dimensional clue framework that uses outcome-reward reinforcement learning to train inspectors to generate faithful, grounded clues from user information, semantic features, interactive situation, and behavioral pattern. |
| Outcome: | The proposed framework outperforms baselines in detection performance and significantly improves the performance of large language models. |