ACL-OCL / Base_JSON /prefixN /json /naacl /2021.naacl-industry.0.json
Benjamin Aw
Add updated pkl file v3
6fa4bc9
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"title": "Young-bum Kim, Amazon, Inc",
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"year": "",
"venue": null,
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"abstract": "We thank our reviewers, without whom the Industry Track would not be possible. This list also includes reviewers for the secondary ethics review.",
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"abstract": [
{
"text": "We thank our reviewers, without whom the Industry Track would not be possible. This list also includes reviewers for the secondary ethics review.",
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"section": "Abstract",
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{
"text": "Language technologies and their applications are an integral and critical part of our daily lives. The development of many of these technologies trace their roots to academic and industrial research laboratories where researchers invented a plethora of algorithms, benchmarked them against shared datasets and perfected the performance of these algorithms to provide plausible solutions to realworld applications. While a controlled laboratory setting is vital for a deeper scientific understanding of the language problem and the impact of algorithmic design choices on the performance of a technology, transitioning the technology to real-world industrial strength applications raises a different, yet challenging, set of technical issues.",
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"section": "Message from the Industry Track Chairs",
"sec_num": null
},
{
"text": "The Industry Track at NAACL HLT 2021 represents innovations and implementations in speech and natural language processing technologies and systems that are relevant to industrial applications. The primary focus of this track is on papers that advance the understanding of, and demonstrate the effective handling of, practical issues related to the deployment of language processing technologies in non-trivial real-world systems. By \"non-trivial real-world system\" we mean an application that is deployed for real-world use, i.e. outside controlled environments such as a laboratories, classrooms or experimental crowd-sourced setups, and that uses natural language processing (including speech technology), even if not state of the art in terms of research. There is no requirement that the system be made by a for-profit company, but the users of the system must be outside of the NLP research community.",
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"section": "Message from the Industry Track Chairs",
"sec_num": null
},
{
"text": "We received 132 papers, and accepted 39, or 29.5%. This year, nearly half the papers in the Industry Track are about dialog processing, reflecting the importance of interactive systems in industrial applications today. Additional topics include semantics, machine translation, information retrieval, and sentiment analysis.",
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"section": "Message from the Industry Track Chairs",
"sec_num": null
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{
"text": "We hope that these papers will provide an interesting complement to the Main Track papers.",
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"section": "Message from the Industry Track Chairs",
"sec_num": null
},
{
"text": "Young-bum Kim, Yunyao Li, Owen Rambow iii ",
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"section": "Message from the Industry Track Chairs",
"sec_num": null
}
],
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