Returning to the Start: Generating Narratives with Related Endpoints (2024.naacl-short)
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| Challenge: | RENarGen generates closed narratives by ensuring the first and last sentences are related and then infilling the middle sentences. |
| Approach: | They propose a novel novel novel that generates closed narratives by ensuring the first and last sentences are related and then infilling the middle sentences. |
| Outcome: | The proposed paradigm generates closed narratives by ensuring the first and last sentences are related and then infilling the middle sentences. |
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| Challenge: | Existing language models generate word by word, but fail to capture high-level interactions . a novel decomposition approach allows more abstract representations to be generated first . |
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Text-to-Text Automatic Story Generation: A Survey (2026.eacl-srw)
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| Challenge: | Automated story generation aims to produce coherent, engaging, and contextually consistent narratives with minimal or no human involvement . despite advances in large language models, maintaining narrative coherence, character consistency, storyline diversity, and plot controllability in generating stories is still challenging. |
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Go Back in Time: Generating Flashbacks in Stories with Event Temporal Prompts (2022.naacl-main)
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Stylized Story Generation with Style-Guided Planning (2021.findings-acl)
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| Challenge: | Existing tools for text-to-image synthesis can visualize machine imaginations for a given context. |
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