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Generating Coherent Narratives by Learning Dynamic and Discrete Entity States with a Contrastive Framework
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use dynamic discrete entity states learned with a contrastive objective | BART-Base narrative generation · Wikiplots test | B-1: 29.81 -> 31.81 | Helped |
| Use dynamic discrete entity states learned with a contrastive objective | BART-Base narrative generation · Wikiplots test | MAUVE: 80.16 -> 87.88 | Helped |
| Use dynamic discrete entity states learned with a contrastive objective | BART-Base narrative generation · CNN News test | B-1: 33.07 -> 33.83 | Helped |
| Use dynamic discrete entity states learned with a contrastive objective | BART-Base narrative generation · CNN News test | MAUVE: 87.25 -> 91.02 | Helped |
| Use dynamic discrete entity states learned with a contrastive objective | BART-Base narrative generation · CNN News test | Rpt-16: 14.37 -> 14.29 | Helped |
| Add entity state attention layer (ablation) | ERIC · Wikiplots test | B-1: 30.12 -> 31.81 | Helped |
| Add entity state attention layer (ablation) | ERIC · Wikiplots test | MAUVE: 83.29 -> 87.88 | Helped |
| Add entity state attention layer (ablation) | ERIC · Wikiplots test | Rpt-16: 16.75 -> 16.22 | Helped |
| Add entity state representations and contrastive learning (ablation) | ERIC · Wikiplots test | B-1: 28.84 -> 31.81 | Helped |
| Add entity state representations and contrastive learning (ablation) | ERIC · Wikiplots test | MAUVE: 83.18 -> 87.88 | Helped |
| Add entity states, contrastive learning, and next-mentioned-entity prediction (ablation) | ERIC · Wikiplots test | B-1: 28.63 -> 31.81 | Helped |
| Add entity states, contrastive learning, and next-mentioned-entity prediction (ablation) | ERIC · Wikiplots test | MAUVE: 73.01 -> 87.88 | Helped |
Closest papers by meaning
- Towards Coherent and Consistent Use of Entities in Narrative Generation (ICML 2022 · similarity 0.89)
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- Parameterized Synthetic Text Generation with SimpleStories (NeurIPS 2025 · similarity 0.84)
- Compressed and Smooth Latent Space for Text Diffusion Modeling (NeurIPS 2025 · similarity 0.84)
- Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models (AAAI 2025 · similarity 0.83)
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