Vighnesh Leonardo Shiv
2019
Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling
Vighnesh Leonardo Shiv
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Chris Quirk
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Anshuman Suri
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Xiang Gao
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Khuram Shahid
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Nithya Govindarajan
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Yizhe Zhang
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Jianfeng Gao
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Michel Galley
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Chris Brockett
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Tulasi Menon
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Bill Dolan
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
The Intelligent Conversation Engine: Code and Pre-trained Systems (Microsoft Icecaps) is an upcoming open-source natural language processing repository. Icecaps wraps TensorFlow functionality in a modular component-based architecture, presenting an intuitive and flexible paradigm for constructing sophisticated learning setups. Capabilities include multitask learning between models with shared parameters, upgraded language model decoding features, a range of built-in architectures, and a user-friendly data processing pipeline. The system is targeted toward conversational tasks, exploring diverse response generation, coherence, and knowledge grounding. Icecaps also provides pre-trained conversational models that can be either used directly or loaded for fine-tuning or bootstrapping other models; these models power an online demo of our framework.
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Co-authors
- Chris Quirk 1
- Anshuman Suri 1
- Xiang Gao 1
- Khuram Shahid 1
- Nithya Govindarajan 1
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