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Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation

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arxiv 2305.00034 v1 pith:ZA6UKQER submitted 2023-04-28 cs.CL

classification cs.CL
keywords generationconditionaltextblueprintcontrolgeneratedorderplan
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While conditional generation models can now generate natural language well enough to create fluent text, it is still difficult to control the generation process, leading to irrelevant, repetitive, and hallucinated content. Recent work shows that planning can be a useful intermediate step to render conditional generation less opaque and more grounded. We present a web browser-based demonstration for query-focused summarization that uses a sequence of question-answer pairs, as a blueprint plan for guiding text generation (i.e., what to say and in what order). We illustrate how users may interact with the generated text and associated plan visualizations, e.g., by editing and modifying the blueprint in order to improve or control the generated output. A short video demonstrating our system is available at https://goo.gle/text-blueprint-demo.

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  1. Why you shouldn't fully trust ChatGPT: A synthesis of this AI tool's error rates across disciplines and the software engineering lifecycle

    cs.SE 2025-04 reject novelty 2.0 of 10

    A multivocal literature review finds ChatGPT's reported error rates range from single digits to over 80 percent depending on domain and task, yet its synthesized ranges are not backed by a released dataset.

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