What strategies help maintain coherence in long-form text generation using GPT

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I am developing a content-generating tool that uses a GPT model to create long-term articles, such as blogs, posts, or essays. During the testing, I have noticed that the overall coherence of generated content sometimes suffers, making it feel disjointed. What should I do to ensure that the generated content flows well and maintains coherence throughout?
Oct 16 in Artificial Intelligence by Ashutosh
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edited Nov 5 by Ashutosh 122 views

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To ensure that your content-generation tool creates coherent long-form pieces, here are five ways you may implement:

Chunking and Overlap: When creating text, divide the content into smaller portions or chunks. This helps to keep context between paragraphs. For example, when creating a new paragraph, add the previous paragraph's last few phrases to provide context for the model.

Consistent Prompts:  Use prompts that help the model stay on subject and maintain the tone or style of the article. Starting each part with a clear direction can be beneficial.

Fine-tuning using Coherent Datasets: Test your model on a dataset of high-quality, coherent long-form texts. This allows the model to learn patterns of coherence and flow in larger texts.

Human-in-the-Loop Review: Create a review process that allows a human editor to provide feedback on the created content. This can assist in identifying fragmented areas early on and direct the model to more coherent outputs.

Post-Generation Editing: After producing the entire text, use a coherence-checking algorithm or a second model to assess the flow of ideas and recommend adjustments. This helps to ensure that the finished product reads properly as a coherent unit.

Following these steps, you can maintain coherence in long text generated using GPT or, in this case, a chatbot based on the GPT model.

answered Nov 5 by josh manila

selected Nov 8 by Ashutosh

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