Story Generation
42 papers with code • 4 benchmarks • 3 datasets
Story generation is the task of automatically generating a coherent narrative, often from a set of premises or a brief summary.
Most implemented papers
Hierarchical Neural Story Generation
We explore story generation: creative systems that can build coherent and fluent passages of text about a topic.
GLAC Net: GLocal Attention Cascading Networks for Multi-image Cued Story Generation
The task of multi-image cued story generation, such as visual storytelling dataset (VIST) challenge, is to compose multiple coherent sentences from a given sequence of images.
Plan-And-Write: Towards Better Automatic Storytelling
Automatic storytelling is challenging since it requires generating long, coherent natural language to describes a sensible sequence of events.
PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
We propose the task of outline-conditioned story generation: given an outline as a set of phrases that describe key characters and events to appear in a story, the task is to generate a coherent narrative that is consistent with the provided outline.
On Faithfulness and Factuality in Abstractive Summarization
It is well known that the standard likelihood training and approximate decoding objectives in neural text generation models lead to less human-like responses for open-ended tasks such as language modeling and story generation.
Language Models Can See: Plugging Visual Controls in Text Generation
MAGIC is a flexible framework and is theoretically compatible with any text generation tasks that incorporate image grounding.
Event Representations for Automated Story Generation with Deep Neural Nets
We then present a technique for automated story generation whereby we decompose the problem into the generation of successive events (event2event) and the generation of natural language sentences from events (event2sentence).
A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generation
Compared to the state-of-the-art models, our skeleton-based model can generate significantly more coherent text according to human evaluation and automatic evaluation.
Plan, Write, and Revise: an Interactive System for Open-Domain Story Generation
We compare different varieties of interaction in story-writing, story-planning, and diversity controls under time constraints, and show that increased types of human collaboration at both planning and writing stages results in a 10-50% improvement in story quality as compared to less interactive baselines.
Informative Visual Storytelling with Cross-modal Rules
To solve this problem, we propose a method to mine the cross-modal rules to help the model infer these informative concepts given certain visual input.