Papers with story quality
Plan, Write, and Revise: an Interactive System for Open-Domain Story Generation (N19-4)
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| Challenge: | a neural narrative generation system interacts with humans to generate stories . a recent resurgence of interest in collaborative storytelling has led to new approaches . |
| Approach: | They propose a neural narrative generation system that interacts with humans to generate stories. |
| Outcome: | The proposed system improves story quality and user engagement under time constraints. |
Stretch-VST: Getting Flexible With Visual Stories (2021.acl-demo)
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| Challenge: | Existing visual storytelling models produce stories with fixed lengths of five sentences and the fix-length stories carry limited details and provide ambiguous textual information to the readers. |
| Approach: | They propose to “stretch” visual storytelling frameworks by adding appropriate knowledge to the model to generate long stories. |
| Outcome: | The proposed framework provides better focus and detail when long stories are generated without deteriorating the quality. |
No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling (P18-1)
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| Challenge: | Visual captioning is aimed at depicting the concrete content of images, but its capability of performing human-like understanding is still restrictive. |
| Approach: | They propose an Adversarial REward Learning framework to learn an implicit reward function from human demonstrations and optimize policy search with the learned reward function. |
| Outcome: | The proposed framework improves performance over state-of-the-art (SOTA) methods in cloning expert behaviors, but human evaluation shows that it achieves significant improvement in generating more human-like stories than SOTA systems. |
Modeling Protagonist Emotions for Emotion-Aware Storytelling (2020.emnlp-main)
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| Challenge: | Cognitive scientists have pinpointed the central role of emotions in storytelling. |
| Approach: | They propose to use Emotion Supervision and two Emotion-Reinforced models to generate stories that follow the desired emotion arcs for the protagonist. |
| Outcome: | The proposed models generate stories that follow the desired emotion arcs without sacrificing story quality. |
Not (yet) the whole story: Evaluating Visual Storytelling Requires More than Measuring Coherence, Grounding, and Repetition (2024.findings-emnlp)
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| Challenge: | Visual storytelling is a task of generating a story for a sequence of several temporally-ordered images or video frames. |
| Approach: | They propose a method that measures story quality in terms of human likeness regarding three key aspects highlighted in previous work: visual grounding, coherence, and repetitiveness. |
| Outcome: | The proposed method improves on the foundation model LLaVA but only slightly compared to TAPM, a 50-times smaller visual storytelling model. |