<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="xu-etal-2024-quantum">
    <titleInfo>
        <title>Quantum Recurrent Architectures for Text Classification</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Wenduan</namePart>
        <namePart type="family">Xu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Stephen</namePart>
        <namePart type="family">Clark</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Douglas</namePart>
        <namePart type="family">Brown</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Gabriel</namePart>
        <namePart type="family">Matos</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Konstantinos</namePart>
        <namePart type="family">Meichanetzidis</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Yaser</namePart>
            <namePart type="family">Al-Onaizan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mohit</namePart>
            <namePart type="family">Bansal</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yun-Nung</namePart>
            <namePart type="family">Chen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Miami, Florida, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We develop quantum RNNs with cells based on Parametrised Quantum Circuits (PQCs). PQCs can provide a form of hybrid quantum-classical computation where the input and the output is in the form of classical data. The previous “hidden” state is the quantum state from the previous time-step, and an angle encoding is used to define a (non-linear) mapping from a classical word embedding into the quantum Hilbert space. Measurements of the quantum state provide classical statistics which are used for classification. We report results which are competitive with various RNN baselines on the Rotten Tomatoes dataset, as well as emulator results which demonstrate the feasibility of running such models on quantum hardware.</abstract>
    <identifier type="citekey">xu-etal-2024-quantum</identifier>
    <location>
        <url>https://aclanthology.org/2024.emnlp-main.1000</url>
    </location>
    <part>
        <date>2024-11</date>
        <extent unit="page">
            <start>18020</start>
            <end>18027</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Quantum Recurrent Architectures for Text Classification
%A Xu, Wenduan
%A Clark, Stephen
%A Brown, Douglas
%A Matos, Gabriel
%A Meichanetzidis, Konstantinos
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F xu-etal-2024-quantum
%X We develop quantum RNNs with cells based on Parametrised Quantum Circuits (PQCs). PQCs can provide a form of hybrid quantum-classical computation where the input and the output is in the form of classical data. The previous “hidden” state is the quantum state from the previous time-step, and an angle encoding is used to define a (non-linear) mapping from a classical word embedding into the quantum Hilbert space. Measurements of the quantum state provide classical statistics which are used for classification. We report results which are competitive with various RNN baselines on the Rotten Tomatoes dataset, as well as emulator results which demonstrate the feasibility of running such models on quantum hardware.
%U https://aclanthology.org/2024.emnlp-main.1000
%P 18020-18027

Markdown (Informal)

[Quantum Recurrent Architectures for Text Classification](https://aclanthology.org/2024.emnlp-main.1000) (Xu et al., EMNLP 2024)

• Quantum Recurrent Architectures for Text Classification (Xu et al., EMNLP 2024)

ACL

• Wenduan Xu, Stephen Clark, Douglas Brown, Gabriel Matos, and Konstantinos Meichanetzidis. 2024. Quantum Recurrent Architectures for Text Classification. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pages 18020–18027, Miami, Florida, USA. Association for Computational Linguistics.