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.
Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation
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abstract
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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cs.SE 1years
2025 1verdicts
REJECT 1representative citing papers
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Why you shouldn't fully trust ChatGPT: A synthesis of this AI tool's error rates across disciplines and the software engineering lifecycle
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.