GenNI: Human-AI Collaboration for Data-Backed Text Generation
- URL: http://arxiv.org/abs/2110.10185v1
- Date: Tue, 19 Oct 2021 18:07:07 GMT
- Title: GenNI: Human-AI Collaboration for Data-Backed Text Generation
- Authors: Hendrik Strobelt, Jambay Kinley, Robert Krueger, Johanna Beyer,
Hanspeter Pfister, Alexander M. Rush
- Abstract summary: Table2Text systems generate textual output based on structured data utilizing machine learning.
GenNI (Generation Negotiation Interface) is an interactive visual system for high-level human-AI collaboration in producing descriptive text.
- Score: 102.08127062293111
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: Table2Text systems generate textual output based on structured data utilizing
machine learning. These systems are essential for fluent natural language
interfaces in tools such as virtual assistants; however, left to generate
freely these ML systems often produce misleading or unexpected outputs. GenNI
(Generation Negotiation Interface) is an interactive visual system for
high-level human-AI collaboration in producing descriptive text. The tool
utilizes a deep learning model designed with explicit control states. These
controls allow users to globally constrain model generations, without
sacrificing the representation power of the deep learning models. The visual
interface makes it possible for users to interact with AI systems following a
Refine-Forecast paradigm to ensure that the generation system acts in a manner
human users find suitable. We report multiple use cases on two experiments that
improve over uncontrolled generation approaches, while at the same time
providing fine-grained control. A demo and source code are available at
https://genni.vizhub.ai .
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