<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="bjorklund-etal-2021-bridging">
    <titleInfo>
        <title>Bridging Perception, Memory, and Inference through Semantic Relations</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Johanna</namePart>
        <namePart type="family">Björklund</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Adam</namePart>
        <namePart type="family">Dahlgren Lindström</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Frank</namePart>
        <namePart type="family">Drewes</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2021-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Marie-Francine</namePart>
            <namePart type="family">Moens</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Xuanjing</namePart>
            <namePart type="family">Huang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lucia</namePart>
            <namePart type="family">Specia</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Scott</namePart>
            <namePart type="given">Wen-tau</namePart>
            <namePart type="family">Yih</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online and Punta Cana, Dominican Republic</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>There is a growing consensus that surface form alone does not enable models to learn meaning and gain language understanding. This warrants an interest in hybrid systems that combine the strengths of neural and symbolic methods. We favour triadic systems consisting of neural networks, knowledge bases, and inference engines. The network provides perception, that is, the interface between the system and its environment. The knowledge base provides explicit memory and thus immediate access to established facts. Finally, inference capabilities are provided by the inference engine which reflects on the perception, supported by memory, to reason and discover new facts. In this work, we probe six popular language models for semantic relations and outline a future line of research to study how the constituent subsystems can be jointly realised and integrated.</abstract>
    <identifier type="citekey">bjorklund-etal-2021-bridging</identifier>
    <identifier type="doi">10.18653/v1/2021.emnlp-main.719</identifier>
    <location>
        <url>https://aclanthology.org/2021.emnlp-main.719</url>
    </location>
    <part>
        <date>2021-11</date>
        <extent unit="page">
            <start>9136</start>
            <end>9142</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Bridging Perception, Memory, and Inference through Semantic Relations
%A Björklund, Johanna
%A Dahlgren Lindström, Adam
%A Drewes, Frank
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and Punta Cana, Dominican Republic
%F bjorklund-etal-2021-bridging
%X There is a growing consensus that surface form alone does not enable models to learn meaning and gain language understanding. This warrants an interest in hybrid systems that combine the strengths of neural and symbolic methods. We favour triadic systems consisting of neural networks, knowledge bases, and inference engines. The network provides perception, that is, the interface between the system and its environment. The knowledge base provides explicit memory and thus immediate access to established facts. Finally, inference capabilities are provided by the inference engine which reflects on the perception, supported by memory, to reason and discover new facts. In this work, we probe six popular language models for semantic relations and outline a future line of research to study how the constituent subsystems can be jointly realised and integrated.
%R 10.18653/v1/2021.emnlp-main.719
%U https://aclanthology.org/2021.emnlp-main.719
%U https://doi.org/10.18653/v1/2021.emnlp-main.719
%P 9136-9142

Markdown (Informal)

[Bridging Perception, Memory, and Inference through Semantic Relations](https://aclanthology.org/2021.emnlp-main.719) (Björklund et al., EMNLP 2021)

• Bridging Perception, Memory, and Inference through Semantic Relations (Björklund et al., EMNLP 2021)

ACL

• Johanna Björklund, Adam Dahlgren Lindström, and Frank Drewes. 2021. Bridging Perception, Memory, and Inference through Semantic Relations. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 9136–9142, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.