Research map / Label-efficient and robust learning / Semi-supervised learning
Modeling Evolving Relationships Between Characters in Literary Novels
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use second-order instead of first-order Markov segmentation | semi-supervised relationship model · SparkNotes | F1: 73.70 -> 76.76 | Helped |
| use second-order instead of first-order Markov segmentation | semi-supervised relationship model · SparkNotes | edit distance: 0.9 -> 0.66 | Helped |
| use first-order structured model instead of unstructured LR | relationship model · SparkNotes | F1: 72.94 -> 73.70 | No clear effect |
| use second-order structured model instead of LR | relationship model · AMT change prediction | F1: 51.48 -> 60.76 | Helped |
| use first-order instead of unstructured LR | relationship model · AMT change prediction | F1: 51.48 -> 52.52 | No clear effect |
| add 'Are Team' and 'Acts Together' feature families (ablation) | LR relationship classifier · SparkNotes | F1 | Helped |
| add 'Adverbs Together' feature family (ablation) | LR relationship classifier · SparkNotes | F1 | Mixed |
Closest papers by meaning
- Unsupervised Learning of Evolving Relationships Between Literary Characters (AAAI 2017 · similarity 0.94)
- Inferring Interpersonal Relations in Narrative Summaries (AAAI 2016 · similarity 0.87)
- Procedural Text Understanding via Scene-Wise Evolution (AAAI 2022 · similarity 0.85)
- M-sense: Modeling Narrative Structure in Short Personal Narratives Using Protagonist’s Mental Representations (AAAI 2023 · similarity 0.85)
- Agents' Room: Narrative Generation through Multi-step Collaboration (ICLR 2025 · similarity 0.82)
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