Hello,
Could you please distribute the following job offer? Thanks.
Best,
Pascal
-------------------------------------------------------------------------------------
3-year PhD position in Computational Models of Semantic Memory and its Acquisition (Inria and University of Lille, France)
We invite applications for a 3-year PhD position at the University of
Lille in the context of the recently funded research project
"COMANCHE" (Computational Models of Lexical Meaning and Change). The
position is funded by Inria, the French national research institute in
Computer Science and Applied Mathematics.
COMANCHE proposes to transfer and adapt neural word embeddings
algorithms to model the acquisition and evolution of word meaning, by
comparing them with linguistic theories on language acquisition and
language evolution. At the intersection between Natural Language
Processing, psycholinguistics and historical linguistics, this project
intends to validate or revise some of these theories, while also
developing computational models that are less data hungry and
computationally intensive as they exploit new inductive biases
inspired by these disciplines.
The first strand of the project, on which the successful candidate
will work, focuses on the development of computational models of
semantic memory and its acquisition. Two main research directions will
be pursued. On the one hand, we will compare the structural properties
associated to different semantic spaces derived from word embedding
algorithms to those found in human semantic memory as reflected in
behavioral data (such as typicality norms) as well as brain imaging
data. The latter data will then used as additional supervision to
inject more hierarchical structure into the learned semantic
spaces. One the other hand, we intend to experiment with training
regimes for word embedding algorithms that are closer to those of
humans when they acquire language, controlling the quantity as well as
the linguistic complexity of the inputs fed to the learning algorithms
through the use of longitudinal and child directed speech corpora
(e.g., CHILDES, Colaje). In both cases, both English and French data
will be considered.
The successful candidate holds a Master's degree in computational
linguistics or computer science or cognitive science and has prior
experience in word embedding models. Furthermore, the candidate will
provide strong programming skills, expertise in machine learning
approaches and is eager to work across languages.
The position is affiliated with the MAGNET team at Inria, Lille [1] as
well as with the SCALAB group at University of Lille [2] in an effort
to strenghten collaborations between these two groups, and ultimately
foster cross-fertilizations between Natural Language Processing and
Psycholinguistics.
Applications will be considered until the position is filled. However,
you are encouraged to apply early as we shall start processing the
applications as and when they are received. Applications, written in
English or French, should include a brief cover letter with research
interests and vision, a CV (including your contact address, work
experience, publications), and contact information for at least 2
referees. Applications (and questions) should be sent to Angèle
Brunellière (angele.brunelliere(a)univ-lille.fr) and Pascal Denis
(pascal.denis(a)inria.fr).
The starting date of the position is 1 October 2022 or soon
thereafter, for a total of 3 full years.
Best regards,
Angèle Brunellière and Pascal Denis
[1] https://team.inria.fr/magnet/
[2] https://scalab.univ-lille.fr/
--
Pascal
----
Pour une évaluation indépendante, transparente et rigoureuse !
Je soutiens la Commission d'Évaluation de l'Inria.
----
+++++++++++++++++++++++++++++++++++++++++++++++
Pascal Denis
Equipe MAGNET, INRIA Lille Nord Europe
Bâtiment B, Avenue Heloïse
Parc scientifique de la Haute Borne
59650 Villeneuve d'Ascq
Tel: ++33 3 59 35 87 24
Url: http://researchers.lille.inria.fr/~pdenis/
+++++++++++++++++++++++++++++++++++++++++++++++
*Asia Pacific Journal of Corpus Research (APJCR) is now available online:*
http://icr.or.kr/ejournals-apjcr
*The Incredible Shrinking Noun Phrase: Ongoing Change in Japanese Word
Formation*Kevin Heffernan, (Kwansei Gakuin University), JAPAN; Yusuke
Imanishi (Kwansei Gakuin University), JAPAN
DOI: https://doi.org/10.22925/apjcr.2023.4.1.1
________________________________________
*Identifying Key Grammatical Errors of Japanese English as a Foreign
Language Learners in a Learner Corpus: Toward Focused Grammar Instruction
with Data-Driven Learning*
Atsushi Mizumoto (Kansai University), JAPAN; Yoichi Watari (Chukyo
University), JAPAN
DOI: https://doi.org/10.22925/apjcr.2023.4.1.25
________________________________________
*A Comparison of the Constructions Make / Take a Decision in Malaysian
English with the Supervarieties *
Christina Sook Beng Ong (Wawasan Open University), MALAYSIA
DOI: https://doi.org/10.22925/apjcr.2023.4.1.43
________________________________________
*Effects of Corpus Use on Error Identification in L2 Writing *
Yoshiho Satake (Aoyama Gakuin University), JAPAN
DOI: https://doi.org/10.22925/apjcr.2023.4.1.61
---
*CK Jung BEng(Hons) Birmingham MSc Warwick EdD Warwick Cert Oxford*
Associate Professor | Department of English Language and Literature,
Incheon National University, *South Korea*
President | The Korea Association of Secondary English Education, *South
Korea *(http://kasee.org)
Vice President | The Korea Association of Primary English Education), *South
Korea *(http://kapee.or.kr)
Director | Institute for Corpus Research, Incheon National University, *South
Korea* (http://icr.or.kr)
Editor-in-Chief | Asia Pacific Journal of Corpus Research, ICR,
*International* (http://icr.or.kr/apjcr)
Editorial Board | Corpora, Edinburgh University Press, *UK*
Editorial Board | English Today, Cambridge University Press, *UK*
E: ckjung(a)inu.ac.kr / T: +82 (0)32 835 8129
H(EN): http://ckjung.org
== 12th NLP4CALL, Tórshavn, Faroe Islands==
The workshop series on Natural Language Processing (NLP) for Computer-Assisted Language Learning (NLP4CALL) is a meeting place for researchers working on the integration of Natural Language Processing and Speech Technologies in CALL systems and exploring the theoretical and methodological issues arising in this connection. The latter includes, among others, insights from Second Language Acquisition (SLA) research, on the one hand, and promote development of “Computational SLA” through setting up Second Language research infrastructure(s), on the other.
The intersection of Natural Language Processing (or Language Technology / Computational Linguistics) and Speech Technology with Computer-Assisted Language Learning (CALL) brings “understanding” of language to CALL tools, thus making CALL intelligent. This fact has given the name for this area of research – Intelligent CALL, ICALL. As the definition suggests, apart from having excellent knowledge of Natural Language Processing and/or Speech Technology, ICALL researchers need good insights into second language acquisition theories and practices, as well as knowledge of second language pedagogy and didactics. This workshop invites therefore a wide range of ICALL-relevant research, including studies where NLP-enriched tools are used for testing SLA and pedagogical theories, and vice versa, where SLA theories, pedagogical practices or empirical data are modeled in ICALL tools.
The NLP4CALL workshop series is aimed at bringing together competences from these areas for sharing experiences and brainstorming around the future of the field.
We welcome papers:
- that describe research directly aimed at ICALL;
- that demonstrate actual or discuss the potential use of existing Language and Speech Technologies or resources for language learning;
- that describe the ongoing development of resources and tools with potential usage in ICALL, either directly in interactive applications, or indirectly in materials, application or curriculum development, e.g. learning material generation, assessment of learner texts and responses, individualized learning solutions, provision of feedback;
- that discuss challenges and/or research agenda for ICALL
- that describe empirical studies on language learner data.
This year a special focus is given to work done on error detection/correction and feedback generation.
We encourage paper presentations and software demonstrations describing the above- mentioned themes primarily, but not exclusively, for the Nordic languages.
==Shared task==
NEW for this year is the MultiGED shared task on token-level error detection for L2 Czech, English, German, Italian and Swedish, organized by the Computational SLA working group.
For more information, please see the Shared Task website: https://github.com/spraakbanken/multiged-2023
==Invited speakers==
This year, we have the pleasure to announce two invited talks.
The first talk is given by Marije Michel from the University of Amsterdam.
The second talk is given by Pierre Lison from the Norwegian Computing Center.
==Submission information==
Authors are invited to submit long papers (8-12 pages) alternatively short papers (4-7 pages), page count not including references.
We will be using the NLP4CALL template for the workshop this year. The author kit can be accessed here, alternatively on Overleaf:
<https://spraakbanken.gu.se/sites/default/files/2023/NLP4CALL%20workshop%20t…>
<https://spraakbanken.gu.se/sites/default/files/2023/nlp4call%20template.doc>
<https://www.overleaf.com/latex/templates/nlp4call-workshop-template/qqqzqqy…>
Submissions will be managed through the electronic conference management system EasyChair <https://easychair.org/conferences/?conf=nlp4call2023>. Papers must be submitted digitally through the conference management system, in PDF format. Final camera-ready versions of accepted papers will be given an additional page to address reviewer comments.
Papers should describe original unpublished work or work-in-progress. Papers will be peer reviewed by at least two members of the program committee in a double-blind fashion. All accepted papers will be collected into a proceedings volume to be submitted for publication in the NEALT Proceeding Series (Linköping Electronic Conference Proceedings) and, additionally, double-published through the ACL anthology, following experiences from the previous NLP4CALL editions (<https://www.aclweb.org/anthology/venues/nlp4call/>).
==Important dates==
03 April 2023: paper submission deadline
21 April 2023: notification of acceptance
01 May 2023: camera-ready papers for publication
22 May 2023: workshop date
==Organizers==
David Alfter (1), Elena Volodina (2), Thomas François (3), Arne Jönsson (4), Evelina Rennes (4)
(1) Gothenburg Research Infrastructure for Digital Humanities, Department of Literature, History of Ideas, and Religion, University of Gothenburg, Sweden
(2) Språkbanken, Department of Swedish, Multilingualism, Language Technology, University of Gothenburg, Sweden
(3) CENTAL, Institute for Language and Communication, Université Catholique de Louvain, Belgium
(4) Department of Computer and Information Science, Linköping University, Sweden
==Contact==
For any questions, please contact David Alfter, david.alfter(a)gu.se
For further information, see the workshop website <https://spraakbanken.gu.se/en/research/themes/icall/nlp4call-workshop-serie…>
Follow us on Twitter @NLP4CALL <https://twitter.com/NLP4CALL/>
[Apologies for cross-posting]
Dear colleagues
We are inviting submissions for the next issue of Asia Pacific Journal of
Corpus Research, to appear on 31 December 2023.
*ABOUT*The Asia Pacific Journal of Corpus Research (APJCR, e-ISSN
2733-8096, DOI: https://doi.org/10.22925/apjcr) is an international and
interdisciplinary peer-reviewed journal intended to explore corpus research
in the Asia Pacific region. APJCR addresses areas of methodological,
applied and theoretical work in the field of corpus research. Examples of
such include discourse analysis, lexical studies, grammatical studies,
language acquisition, language learning, language education, lexicography,
pragmatics, sociolinguistics, (machine) translation studies, (digital)
literary studies, computational linguistics, speech, phonetics, deep
learning and natural language understanding in conjunction with corpus.
*NO ARTICLE PROCESS CHARGE*APJCR does not charge authors an Article
Processing Fee (APF).
*OPEN ACCESS POLICY*APJCR provides open access to its content under the
principle in the academic field that making research freely available to
the public supports a greater global exchange of knowledge.
*SUBMISSION*
Papers (in English or Korean) should be sent to *apjcreditor(a)icr.or.kr
<apjcreditor(a)icr.or.kr>*
*Full instruction can be found on http://icr.or.kr/apjcr
<http://icr.or.kr/apjcr>*
*IMPORTANT DATES*- Manuscript submission: 15 October 2023
- First decision (articles assessed by editors): October 2023
- Final decision: November 2023
- Production: December 2023
- Online publication: 31 December 2023
*APJCR ARCHIVE*- Google Scholar:
https://scholar.google.co.kr/scholar?hl=ko&as_sdt=0%2C5&q=apjcr&btnG=
- KoreaScience: http://koreascience.or.kr/journal/CPSOBX/v1n1.page
*ENQUIRIES*
help(a)icr.or.kr
---
*CK Jung BEng(Hons) Birmingham MSc Warwick EdD Warwick Cert Oxford*
Associate Professor | Department of English Language and Literature,
Incheon National University, *South Korea*
President | The Korea Association of Secondary English Education, *South
Korea *(http://kasee.org)
Vice President | The Korea Association of Primary English Education), *South
Korea *(http://kapee.or.kr)
Director | Institute for Corpus Research, Incheon National University, *South
Korea* (http://icr.or.kr)
Editor-in-Chief | Asia Pacific Journal of Corpus Research, ICR,
*International* (http://icr.or.kr/apjcr)
Editorial Board | Corpora, Edinburgh University Press, *UK*
Editorial Board | English Today, Cambridge University Press, *UK*
E: ckjung(a)inu.ac.kr / T: +82 (0)32 835 8129
We're hiring a postdoc to work on multimodal coreference resolution. The
position is at CLASP, University of Gothenburg, Sweden, for 2 years with
possibility of 1 year extension. I'm happy to answer questions if you're
interested.
https://web103.reachmee.com/ext/I005/1035/job?site=7&lang=UK&validator=9b89…
Sharid
Hi there,
Could you please distribute the following job offer? Thanks.
Best,
Pascal
-------------------------------------------------------------------------------------
We invite applications for a 3-year PhD position co-funded by Inria,
the French national research institute in Computer Science and Applied
Mathematics, and LexisNexis France, leader of legal information in
France and subsidiary of the RELX Group.
The overall objective of this project is to develop an automated
system for detecting argumentation structures in French legal
decisions, using recent machine learning-based approaches (i.e. deep
learning approaches). In the general case, these structures take the
form of a directed labeled graph, whose nodes are the elements of the
text (propositions or groups of propositions, not necessarily
contiguous) which serve as components of the argument, and edges are
relations that signal the argumentative connection between them (e.g.,
support, offensive). By revealing the argumentation structure behind
legal decisions, such a system will provide a crucial milestone
towards their detailed understanding, their use by legal
professionals, and above all contributes to greater transparency of
justice.
The main challenges and milestones of this project start with the
creation and release of a large-scale dataset of French legal
decisions annotated with argumentation structures. To minimize the
manual annotation effort, we will resort to semi-supervised and
transfer learning techniques to leverage existing argument mining
corpora, such as the European Court of Human Rights (ECHR) corpus, as
well as annotations already started by LexisNexis. Another promising
research direction, which is likely to improve over state-of-the-art
approaches, is to better model the dependencies between the different
sub-tasks (argument span detection, argument typing, etc.) instead of
learning these tasks independently. A third research avenue is to find
innovative ways to inject the domain knowledge (in particular the rich
legal ontology developed by LexisNexis) to enrich enrich the
representations used in these models. Finally, we would like to take
advantage of other discourse structures, such as coreference and
rhetorical relations, conceived as auxiliary tasks in a multi-tasking
architecture.
The successful candidate holds a Master's degree in computational
linguistics, natural language processing, machine learning, ideally
with prior experience in legal document processing and discourse
processing. Furthermore, the candidate will provide strong programming
skills, expertise in machine learning approaches and is eager to work
at the interplay between academia and industry.
The position is affiliated with the MAGNET [1], a research group at
Inria, Lille, which has expertise in Machine Learning and Natural
Language Processing, in particular Discourse Processing. The PhD
student will also work in close collaboration with the R&D team at
LexisNexis France, who will provide their expertise in the legal
domain and the data they have collected.
Applications will be considered until the position is filled. However,
you are encouraged to apply early as we shall start processing the
applications as and when they are received. Applications, written in
English or French, should include a brief cover letter with research
interests and vision, a CV (including your contact address, work
experience, publications), and contact information for at least 2
referees. Applications (and questions) should be sent to Pascal Denis
(pascal.denis(a)inria.fr).
The starting date of the position is 1 November 2022 or soon
thereafter, for a total of 3 full years.
Best regards,
Pascal Denis
[1] https://team.inria.fr/magnet/
[2] https://www.lexisnexis.fr/
--
Pascal
----
Pour une évaluation indépendante, transparente et rigoureuse !
Je soutiens la Commission d'Évaluation de l'Inria.
----
+++++++++++++++++++++++++++++++++++++++++++++++
Pascal Denis
Equipe MAGNET, INRIA Lille Nord Europe
Bâtiment B, Avenue Heloïse
Parc scientifique de la Haute Borne
59650 Villeneuve d'Ascq
Tel: ++33 3 59 35 87 24
Url: http://researchers.lille.inria.fr/~pdenis/
+++++++++++++++++++++++++++++++++++++++++++++++
Dear colleagues,
We are inviting contributions to the Special Issue of AI Communications on "Human-Aware AI".
Contributions are sought that report on mature and highly interdisciplinary research with a focus on the human involvement in the development of meaningful paradigms of AI-enabled human-human interactions, human-AI interactions, and human-centered AI-AI interactions. An indicative list of disciplines and sub-disciplines that we expect to be relevant are: Autonomous Agents and Multi-Agent Systems, Ethics, Human-Computer Interaction, Knowledge Representation and Reasoning, Machine Learning, Ontologies, Privacy, Social Computing, Social Psychology, Social Sciences.
Any contribution relating to the general theme is welcome. The following is a non-exhaustive list of suggested topics:
• Models of human diversity and human awareness
• Models of AI diversity and human-aware AI
• Perception of diversity versus models of diversity
• Models of diverse human-AI societies and interactions
• Experimental studies on human and social diversity
• Experimental studies on hybrid human-AI diversity
• Representation and visualization of diversity
• Incentive models for Human-AI collaboration
• Human-aware machine learning technologies
• Interpretability and explainability of human-aware machine learning
• Diversification and unbiasing of machine learning
• Metrics for diversity-aware machine learning
• Diversity-aware and diversity-preserving inference and reasoning
• Ethical and privacy considerations on diversity
• Ethical and legal considerations on diversity-misuse scenarios
• Data economics, business models, and/or non-profit use
• Insights from Critical Diversity Studies
• Diversity-sensitive communication
• Content moderation for diversity-aware social interaction
More information about the Special Issue can be found here:
https://www.iospress.com/sites/default/files/media/files/2023-09/AIC_Human-…
The submission deadline is November 30, 2023. However, we would appreciate it if you could register your interest to submit a paper by completing the following form at your earliest convenience: https://forms.gle/vsVjJrCwXE8Nh9YU6
We look forward to your contributions!
Regards,
Loizos
Dear colleagues,
Last month, we shared the result of our collaborative work on a core metadata scheme for learner corpora with LCR2022 participants. Our proposal builds on Granger and Paquot (2017)'s first attempt to design such a scheme and during our presentation, we explained the rationale for expanding on the initial proposal and discussed selected aspects of the revised scheme.
Our proposal is available at https://docs.google.com/spreadsheets/d/1-RbX5iUCUtCBkZU9Rfk-kv-Vzc--F-eUW2O…<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdocs.goog…>
We firmly believe that our efforts to develop a core metadata scheme for learner corpora will only be successful to the extent that (1) the LCR community is given the opportunity to engage with our work in various ways (provide feedback on the general structure of the scheme, the list of variables that we identified as core and their operationalization; test the metadata on other learner corpora; use the scheme to start a new corpus compilation, etc.) and (2) the core metadata scheme is the result of truly collaborative work.
As mentioned at LCR2022, we will be collecting feedback on the metadata scheme until the end of October. The online feedback form is available at:
https://docs.google.com/document/d/1NeDUuxGJlPSJI9wHVA1xgGM-aV8jXTa8Qlb45K-…<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdocs.goog…>
We'd like to thank all the colleagues who already got back to us (at LCR2022, by email or via the online form). We also thank them for their appreciation and enthusiasm for our work! We'd also like to encourage more colleagues (and particularly those of you who have experience in learner corpus compilation) to provide feedback! We need help in finalizing the core metadata scheme to make sure that it can be applied in all learner compilation contexts. In short, we need you to make sure the scheme meets the needs of the LCR community at large.
With very best wishes,
Magali Paquot (also on behalf of Alexander König, Jennifer-Carmen Frey, and Egon W. Stemle)
Reference
Granger, S. & M. Paquot (2017). Towards standardization of metadata for L2 corpora. Invited talk at the CLARIN workshop on Interoperability of Second Language Resources and Tools, 6-8 December 2017, University of Gothenburg, Sweden.
Dr. Magali Paquot
Centre for English Corpus Linguistics
Institut Langage et Communication
UCLouvain
https://perso.uclouvain.be/magali.paquot/
The Department of Computer Science at Brandeis University invites
applications for a tenure-track assistant professor in computational
linguistics, beginning Fall 2024. Qualifications required of all applicants
include a Ph.D., in hand by Fall 2024, in Computer Science or a related
discipline, a strong research record, and a commitment to teaching at the
undergraduate and graduate levels. Particular attention will be given to
candidates pursuing research in the broad area of speech, dialogue, or
multimodal language processing. This position is subject to budgetary
approval.
The Department consists of a diverse group of 20 full-time faculty members
and researchers and offers programs leading to B.A./B.S., M.S., and Ph.D.
degrees in Computer Science and an M.S. in Computational Linguistics. The
Department has research strengths in computational linguistics, theoretical
linguistics, machine learning, computer vision, data mining, networking,
distributed systems, operating systems, databases, algorithms, and software
design and implementation. In addition, members of the Department
collaborate closely with faculty across the university including biology,
neuroscience, economics, physics, political science, among others.
At Brandeis, we believe that diversity, equity, and inclusion are essential
components of academic excellence. Brandeis University is an affirmative
action, equal opportunity employer that is committed to creating equitable
access and opportunities for applicants to all employment positions.
Because diversity, equity, and inclusion are at the core of Brandeis’
history and mission, we value and are seeking candidates that represent a
variety of social identities, including those that have been
underrepresented in higher education, who possess skills that spark
innovation, and who, through their scholarly pursuits, teaching, and/or
service experiences, bring expertise in building, engaging, and sustaining
a pluralistic, just, and inclusive campus community.
Applicants should submit a CV, research statement, and teaching statement,
and arrange for at least three reference letters to be submitted to
Academic Jobs Online (AJO). Qualified applicants should apply at
https://academicjobsonline.org/ajo/jobs/25467. First consideration will be
given to applications received by December 20, 2023. Questions about the
position can be directed to Professor James Pustejovsky . Additional
information about the Department is available at
https://www.brandeis.edu/computer-science/, and information about the
Computational Linguistics program is available at
https://www.brandeis.edu/computer-science/computational-linguistics/index.h…
.