MixingBoard: a Knowledgeable Stylized Integrated Text Generation Platform
Xiang Gao, Michel Galley, Bill Dolan
Abstract
We present MixingBoard, a platform for quickly building demos with a focus on knowledge grounded stylized text generation. We unify existing text generation algorithms in a shared codebase and further adapt earlier algorithms for constrained generation. To borrow advantages from different models, we implement strategies for cross-model integration, from the token probability level to the latent space level. An interface to external knowledge is provided via a module that retrieves, on-the-fly, relevant knowledge from passages on the web or a document collection. A user interface for local development, remote webpage access, and a RESTful API are provided to make it simple for users to build their own demos.- Anthology ID:
- 2020.acl-demos.26
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 224–231
- URL:
- https://www.aclweb.org/anthology/2020.acl-demos.26
- DOI:
- PDF:
- https://www.aclweb.org/anthology/2020.acl-demos.26.pdf
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