@inproceedings{shiv-etal-2019-microsoft,
title = "{M}icrosoft Icecaps: An Open-Source Toolkit for Conversation Modeling",
author = "Shiv, Vighnesh Leonardo and
Quirk, Chris and
Suri, Anshuman and
Gao, Xiang and
Shahid, Khuram and
Govindarajan, Nithya and
Zhang, Yizhe and
Gao, Jianfeng and
Galley, Michel and
Brockett, Chris and
Menon, Tulasi and
Dolan, Bill",
editor = "Costa-juss{\`a}, Marta R. and
Alfonseca, Enrique",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-3021",
doi = "10.18653/v1/P19-3021",
pages = "123--128",
abstract = "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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<abstract>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.</abstract>
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%0 Conference Proceedings
%T Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling
%A Shiv, Vighnesh Leonardo
%A Quirk, Chris
%A Suri, Anshuman
%A Gao, Xiang
%A Shahid, Khuram
%A Govindarajan, Nithya
%A Zhang, Yizhe
%A Gao, Jianfeng
%A Galley, Michel
%A Brockett, Chris
%A Menon, Tulasi
%A Dolan, Bill
%Y Costa-jussà, Marta R.
%Y Alfonseca, Enrique
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F shiv-etal-2019-microsoft
%X 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.
%R 10.18653/v1/P19-3021
%U https://aclanthology.org/P19-3021
%U https://doi.org/10.18653/v1/P19-3021
%P 123-128
Markdown (Informal)
[Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling](https://aclanthology.org/P19-3021) (Shiv et al., ACL 2019)
ACL
- Vighnesh Leonardo Shiv, Chris Quirk, Anshuman Suri, Xiang Gao, Khuram Shahid, Nithya Govindarajan, Yizhe Zhang, Jianfeng Gao, Michel Galley, Chris Brockett, Tulasi Menon, and Bill Dolan. 2019. Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 123–128, Florence, Italy. Association for Computational Linguistics.