DeepSPIN: Deep Structured Prediction for Natural Language Processing

André F. T. Martins; Ben Peters; Chrysoula Zerva; Chunchuan Lyu; Gonçalo Correia; Marcos Treviso; Pedro Martins; Tsvetomila Mihaylova

DeepSPIN: Deep Structured Prediction for Natural Language Processing

André F. T. Martins, Ben Peters, Chrysoula Zerva, Chunchuan Lyu, Gonçalo Correia, Marcos Treviso, Pedro Martins, Tsvetomila Mihaylova

Correct Metadata for

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Abstract

DeepSPIN is a research project funded by the European Research Council (ERC) whose goal is to develop new neural structured prediction methods, models, and algorithms for improving the quality, interpretability, and data-efficiency of natural language processing (NLP) systems, with special emphasis on machine translation and quality estimation. We describe in this paper the latest findings from this project.

Anthology ID:: 2022.eamt-1.53
Volume:: Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
Month:: June
Year:: 2022
Address:: Ghent, Belgium
Editors:: Helena Moniz, Lieve Macken, Andrew Rufener, Loïc Barrault, Marta R. Costa-jussà, Christophe Declercq, Maarit Koponen, Ellie Kemp, Spyridon Pilos, Mikel L. Forcada, Carolina Scarton, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne
Venue:: EAMT
SIG:
Publisher:: European Association for Machine Translation
Note:
Pages:: 327–328
Language:
URL:: https://aclanthology.org/2022.eamt-1.53/
DOI:
Bibkey:
Cite (ACL):: André F. T. Martins, Ben Peters, Chrysoula Zerva, Chunchuan Lyu, Gonçalo Correia, Marcos Treviso, Pedro Martins, and Tsvetomila Mihaylova. 2022. DeepSPIN: Deep Structured Prediction for Natural Language Processing. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 327–328, Ghent, Belgium. European Association for Machine Translation.
Cite (Informal):: DeepSPIN: Deep Structured Prediction for Natural Language Processing (Martins et al., EAMT 2022)
Copy Citation:
PDF:: https://aclanthology.org/2022.eamt-1.53.pdf

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{martins-etal-2022-deepspin,
    title = "{D}eep{SPIN}: Deep Structured Prediction for Natural Language Processing",
    author = "Martins, Andr{\'e} F. T.  and
      Peters, Ben  and
      Zerva, Chrysoula  and
      Lyu, Chunchuan  and
      Correia, Gon{\c{c}}alo  and
      Treviso, Marcos  and
      Martins, Pedro  and
      Mihaylova, Tsvetomila",
    editor = {Moniz, Helena  and
      Macken, Lieve  and
      Rufener, Andrew  and
      Barrault, Lo{\"i}c  and
      Costa-juss{\`a}, Marta R.  and
      Declercq, Christophe  and
      Koponen, Maarit  and
      Kemp, Ellie  and
      Pilos, Spyridon  and
      Forcada, Mikel L.  and
      Scarton, Carolina  and
      Van den Bogaert, Joachim  and
      Daems, Joke  and
      Tezcan, Arda  and
      Vanroy, Bram  and
      Fonteyne, Margot},
    booktitle = "Proceedings of the 23rd Annual Conference of the European Association for Machine Translation",
    month = jun,
    year = "2022",
    address = "Ghent, Belgium",
    publisher = "European Association for Machine Translation",
    url = "https://aclanthology.org/2022.eamt-1.53/",
    pages = "327--328",
    abstract = "DeepSPIN is a research project funded by the European Research Council (ERC) whose goal is to develop new neural structured prediction methods, models, and algorithms for improving the quality, interpretability, and data-efficiency of natural language processing (NLP) systems, with special emphasis on machine translation and quality estimation. We describe in this paper the latest findings from this project."
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="martins-etal-2022-deepspin">
    <titleInfo>
        <title>DeepSPIN: Deep Structured Prediction for Natural Language Processing</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">André</namePart>
        <namePart type="given">F</namePart>
        <namePart type="given">T</namePart>
        <namePart type="family">Martins</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ben</namePart>
        <namePart type="family">Peters</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Chrysoula</namePart>
        <namePart type="family">Zerva</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Chunchuan</namePart>
        <namePart type="family">Lyu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Gonçalo</namePart>
        <namePart type="family">Correia</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Marcos</namePart>
        <namePart type="family">Treviso</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Pedro</namePart>
        <namePart type="family">Martins</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Tsvetomila</namePart>
        <namePart type="family">Mihaylova</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2022-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 23rd Annual Conference of the European Association for Machine Translation</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Helena</namePart>
            <namePart type="family">Moniz</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lieve</namePart>
            <namePart type="family">Macken</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Andrew</namePart>
            <namePart type="family">Rufener</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Loïc</namePart>
            <namePart type="family">Barrault</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Marta</namePart>
            <namePart type="given">R</namePart>
            <namePart type="family">Costa-jussà</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Christophe</namePart>
            <namePart type="family">Declercq</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Maarit</namePart>
            <namePart type="family">Koponen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ellie</namePart>
            <namePart type="family">Kemp</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Spyridon</namePart>
            <namePart type="family">Pilos</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mikel</namePart>
            <namePart type="given">L</namePart>
            <namePart type="family">Forcada</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Carolina</namePart>
            <namePart type="family">Scarton</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Joachim</namePart>
            <namePart type="family">Van den Bogaert</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Joke</namePart>
            <namePart type="family">Daems</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Arda</namePart>
            <namePart type="family">Tezcan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Bram</namePart>
            <namePart type="family">Vanroy</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Margot</namePart>
            <namePart type="family">Fonteyne</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>European Association for Machine Translation</publisher>
            <place>
                <placeTerm type="text">Ghent, Belgium</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>DeepSPIN is a research project funded by the European Research Council (ERC) whose goal is to develop new neural structured prediction methods, models, and algorithms for improving the quality, interpretability, and data-efficiency of natural language processing (NLP) systems, with special emphasis on machine translation and quality estimation. We describe in this paper the latest findings from this project.</abstract>
    <identifier type="citekey">martins-etal-2022-deepspin</identifier>
    <location>
        <url>https://aclanthology.org/2022.eamt-1.53/</url>
    </location>
    <part>
        <date>2022-06</date>
        <extent unit="page">
            <start>327</start>
            <end>328</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T DeepSPIN: Deep Structured Prediction for Natural Language Processing
%A Martins, André F. T.
%A Peters, Ben
%A Zerva, Chrysoula
%A Lyu, Chunchuan
%A Correia, Gonçalo
%A Treviso, Marcos
%A Martins, Pedro
%A Mihaylova, Tsvetomila
%Y Moniz, Helena
%Y Macken, Lieve
%Y Rufener, Andrew
%Y Barrault, Loïc
%Y Costa-jussà, Marta R.
%Y Declercq, Christophe
%Y Koponen, Maarit
%Y Kemp, Ellie
%Y Pilos, Spyridon
%Y Forcada, Mikel L.
%Y Scarton, Carolina
%Y Van den Bogaert, Joachim
%Y Daems, Joke
%Y Tezcan, Arda
%Y Vanroy, Bram
%Y Fonteyne, Margot
%S Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
%D 2022
%8 June
%I European Association for Machine Translation
%C Ghent, Belgium
%F martins-etal-2022-deepspin
%X DeepSPIN is a research project funded by the European Research Council (ERC) whose goal is to develop new neural structured prediction methods, models, and algorithms for improving the quality, interpretability, and data-efficiency of natural language processing (NLP) systems, with special emphasis on machine translation and quality estimation. We describe in this paper the latest findings from this project.
%U https://aclanthology.org/2022.eamt-1.53/
%P 327-328

Download as File

Markdown (Informal)

[DeepSPIN: Deep Structured Prediction for Natural Language Processing](https://aclanthology.org/2022.eamt-1.53/) (Martins et al., EAMT 2022)

DeepSPIN: Deep Structured Prediction for Natural Language Processing (Martins et al., EAMT 2022)

ACL

André F. T. Martins, Ben Peters, Chrysoula Zerva, Chunchuan Lyu, Gonçalo Correia, Marcos Treviso, Pedro Martins, and Tsvetomila Mihaylova. 2022. DeepSPIN: Deep Structured Prediction for Natural Language Processing. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 327–328, Ghent, Belgium. European Association for Machine Translation.