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        <title>Multi-input Recurrent Independent Mechanisms for leveraging knowledge sources: Case studies on sentiment analysis and health text mining</title>
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            <title>Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures</title>
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        <name type="personal">
            <namePart type="given">Eneko</namePart>
            <namePart type="family">Agirre</namePart>
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            <namePart type="given">Marianna</namePart>
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            <namePart type="given">Ivan</namePart>
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    <abstract>This paper presents a way to inject and leverage existing knowledge from external sources in a Deep Learning environment, extending the recently proposed Recurrent Independent Mechnisms (RIMs) architecture, which comprises a set of interacting yet independent modules. We show that this extension of the RIMs architecture is an effective framework with lower parameter implications compared to purely fine-tuned systems.</abstract>
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    <identifier type="doi">10.18653/v1/2021.deelio-1.11</identifier>
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%0 Conference Proceedings
%T Multi-input Recurrent Independent Mechanisms for leveraging knowledge sources: Case studies on sentiment analysis and health text mining
%A Bagherzadeh, Parsa
%A Bergler, Sabine
%Y Agirre, Eneko
%Y Apidianaki, Marianna
%Y Vulić, Ivan
%S Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F bagherzadeh-bergler-2021-multi
%X This paper presents a way to inject and leverage existing knowledge from external sources in a Deep Learning environment, extending the recently proposed Recurrent Independent Mechnisms (RIMs) architecture, which comprises a set of interacting yet independent modules. We show that this extension of the RIMs architecture is an effective framework with lower parameter implications compared to purely fine-tuned systems.
%R 10.18653/v1/2021.deelio-1.11
%U https://aclanthology.org/2021.deelio-1.11
%U https://doi.org/10.18653/v1/2021.deelio-1.11
%P 108-118

Markdown (Informal)

[Multi-input Recurrent Independent Mechanisms for leveraging knowledge sources: Case studies on sentiment analysis and health text mining](https://aclanthology.org/2021.deelio-1.11) (Bagherzadeh & Bergler, DeeLIO 2021)

• Multi-input Recurrent Independent Mechanisms for leveraging knowledge sources: Case studies on sentiment analysis and health text mining (Bagherzadeh & Bergler, DeeLIO 2021)

ACL

• Parsa Bagherzadeh and Sabine Bergler. 2021. Multi-input Recurrent Independent Mechanisms for leveraging knowledge sources: Case studies on sentiment analysis and health text mining. In Proceedings of Deep Learning Inside Out (DeeLIO): The 2nd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, pages 108–118, Online. Association for Computational Linguistics.