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[CFP] 1st International Conference on Recent Advances in Robust Argumentation Machines (RATIO24)
by Philipp Cimiano 24 May '23

24 May '23

The 1st International Conference on Robust Argumentation Machines (RATIO-24) will take place from June 5th-7th, 2024, in Bielefeld, Germany. https://ratio-conference.net <https://ratio-conference.net/> In recent years, we have witnessed significant advances in our ability to develop approaches that support the automated analysis, summarization, aggregation, retrieval and ranking of arguments exchanged “in the wild” at large scale. By "in the wild" we mean arguments exchanged on the web in debate portals or other online formats where users share opinions and viewpoints on topics relevant to them. Argument analysis methods have indeed reached a level of maturity and robustness that make them applicable to the analysis of real online debates, to find the main arguments exchanged, to summarize and group arguments, or even to automatically generate arguments to present different viewpoints and perspectives. We call for submissions of original research work on the following topics: automatic semantic analysis of arguments, including tasks such as stance detection, keypoint identification, attack/support classification, etc. analysis of arguments in discourse and dialogue automatic synthesis and generation of arguments summarization of arguments argument retrieval methods for predicting argument quality ranking of arguments according to, e.g., quality methods for rephrasing and repurposing arguments inferring the frame, viewpoint or perspective of an argument common sense knowledge in the automated analysis of arguments scalable reasoning methods for arguments applications of argument analysis in domains such as political discourse, law, science, education, finance, social sciences, etc. Papers will be peer-reviewed and published by Springer in the LNCS series. Two types of papers will be accepted: Long Papers (up to 15 pages including references): Description of substantive and original research. Short Papers (up to 8 pages including references): Description of work in progress or original research contribution of limited scope. Papers should be submitted via Easychair: https://easychair.org/conferences/?conf=ratio24 <https://easychair.org/conferences/?conf=ratio24> Important dates: Abstract submission deadline: October 27th, 2023 Full paper submission deadline: November 10th, 2023 Notification of Acceptance: January 26th, 2024 Camera-ready version: February 23rd, 2024 Conference Chairs: Philipp Cimiano (CITEC, Bielefeld University) Anette Frank (University of Heidelberg) Michael Kohlhase (University of Erlangen-Nürnberg) Benno Stein (Bauhaus University Weimar) Jürgen Ziegler (University Duisburg - Essen) Invited Speakers: Elena Cabrio (Université Côte d’Azur, Inria <http://www.unice.fr/>) Yufang Hou (IBM Research Europe) Henning Wachsmuth (Institute for Artificial Intelligence, Leibniz University of Hannover) Venue: The conference will be held in Bielefeld, Germany at the Cognitive Interaction Technology Center (CITEC). All questions about submissions should be emailed to Philipp Cimiano: cimiano(a)cit-ec.uni.bielefeld.de <mailto:cimiano@cit-ec.uni.bielefeld.de> Prof. Dr. Philipp Cimiano AG Semantic Computing Coordinator of the Cognitive Interaction Technology Center (CITEC) Co-Director of the Joint Artificial Intelligence Institute (JAII) Universität Bielefeld Tel: +49 521 106 12249 Fax: +49 521 106 6560 Mail: cimiano(a)cit-ec.uni-bielefeld.de Office CITEC-2.307 Universitätsstr. 21-25 33615 Bielefeld, NRW Germany

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Vacancy at CLARIN ERIC: Member of the Board of Directors
by Gorgaini, E. (Elisa) 24 May '23

24 May '23

As of September 2023, the CLARIN European Research Infrastructure Consortium (CLARIN ERIC) will have an opening for the position of member of the Board of Directors (0.2 fte) who will work closely together with the other directors. The appointment will be for a term of two years, with the possibility of prolongation for another term of two years. The mission of CLARIN ERIC<https://www.clarin.eu/> is to develop and maintain Europe’s common language resources and technology infrastructure. At the same time CLARIN serves as an ecosystem for the exchange of knowledge and experience that is crucial for the uptake of CLARIN within the domains in which digital scholarship is rapidly developing, in particular in the social sciences and humanities. Responsibilities and Tasks The tasks to be taken up by the new member of the Board of Directors<https://www.clarin.eu/governance/board-directors> (BoD) follow on from the responsibilities of CLARIN's executive body: * to prepare and implement strategic action lines needed for the smooth operation of CLARIN ERIC, the further articulation and implementation of the prevailing value proposition<https://office.clarin.eu/v/CE-2021-1830-ValueProposition.pdf> and the consolidation of the technological maturity of CLARIN * to optimise the conditions for a sustainable future of CLARIN ERIC * to foster the effective collaboration between the various bodies that are responsible for the governance<https://www.clarin.eu/content/governance> of CLARIN ERIC * to ensure optimal alignment of the agenda of the BoD with the strategy and activities of the National Coordinators’ Forum<https://www.clarin.eu/governance/national-coordinators-forum> (NCF) and the Strategy and Management Board<https://www.clarin.eu/governance/strategy-and-management-board> (SAMBA), and to support the coordination between the national consortia Instruments are in place to implement the CLARIN strategy and the envisaged activities to be undertaken, but the development of new action lines that would support the agreed strategic planning would be welcomed. Envisaged Profile In view of the current stage of development of the CLARIN infrastructure, the profiles of the other members of the BoD, and the challenges that CLARIN is facing, applications are solicited from candidates with a profile that ideally would include the following elements: * a clear vision on how CLARIN can reach out to existing and new scholarly communities of use * a good insight into instruments that could be deployed to increase the awareness of what CLARIN has on offer among non-academics (industry, GLAM sector, public administration, society at large) * good understanding of what is needed to increase the potential of a research infrastructure such as CLARIN for generating impact along the dimension of societal challenges and non-academic impact at large * proven experience in setting up and/or deploying instruments for the exchange of knowledge and expertise in a cross-national and/or multidisciplinary context * proven expertise in the field of natural language processing, AI and technical infrastructure In addition we expect that the suitability of candidates is also evidenced by: * familiarity with CLARIN, its mission and vision, and the concept of a research infrastructure (RI) in general * ample engagement in one or more of the relevant networks in which the European Open Science agenda is guiding the developments * familiarity with the dynamics in the European landscape of RI’s (e.g. ESFRI, EOSC) * familiarity with the major scholarly paradigms in the social sciences and humanities (SSH) and the role of infrastructural support * established connections with and good visibility in one or more of the research communities that CLARIN aims to serve and/or that contribute to the spectrum of services that CLARIN is making available * a relevant academic track record (PhD-level, plus a convincing combination of publications and/or involvement in the development of use cases, demonstrators, tools or data sets) * a relevant institutional affiliation that is guaranteed until at least the end of 2023 * excellent communication skills. A balanced diversity in the composition of the BoD as a whole will be sought along all relevant dimensions, including gender and regional background. Conditions of Employment The tasks can be carried out from the applicant’s home institute on the basis of a secondment agreement. The applicant’s home institute will be reimbursed for the release time provided to CLARIN ERIC on the basis of the applicant’s regular salary including overhead. Occasional travel to CLARIN events and participation in (virtual) meetings of the CLARIN ERIC Board of Directors is required. Funds for administrative support and a travel budget will be provided. How to Apply * Applications (including CV, publication list, statement of motivation) as well as requests for information should be sent to Patris van Boxel, CLARIN ERIC’s Chief Operations Officer, by email: patris(a)clarin.eu<https://mailto:patris@clarin.eu>; the phrase "BoD vacancy" should be included in the subject header. * The application deadline is 30 June 2023. More information about CLARIN can be found on our website www.clarin.eu<http://www.clarin.eu/>. — Elisa Gorgaini CLARIN ERIC External Relation Officer elisa(a)clarin.eu +31648213015 www.clarin.eu

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2nd announcement: Utrecht PhD positions on "Dealing with Meaning Variation in NLP" (Deadline: May 29th)
by Massimo Poesio 24 May '23

24 May '23

** Job openings: PhD studentships on meaning variation in NLP ** Utrecht University, The Netherlands The Natural Language Processing (NLP) group in the Computing and Information Sciences department of Utrecht University (UU) is looking for young researchers who want to jump-start their career in AI / NLP by taking up a PhD position. Two four-year positions are available now. They are part of the AiNed project “Dealing with Meaning Variation in NLP”, which will be led by Prof. Massimo Poesio. Vacancies for 4 further PhD positions on this project will become available over the coming 1-2 years. The overall aim of the project is to allow NLP models to make better sense of variations in the ways that different speakers and readers interpret language. The plan is for each of the 6 PhD projects to be supervised by one researcher from the NLP group and one from UU's Institute for Language Sciences. PhD PROJECT 1: Formal semantics for vagueness in interpretation This project is concerned with vagueness, a pervasive phenomenon in which the meanings of words have imprecisely defined boundaries, which are applied differently in different contexts and by different people (for example when the air temperature is described as "warm"). This PhD project will study mathematical and computational models of uncertainty and vagueness. In recent years, the theoretical literature in this area has shifted away from 2-valued towards multi-valued models, but these models have rarely been tested with real data. This PhD project will use existing “big” datasets (which are available in the weather domain, for example) to find out which models predict and explain the data best. The successful candidate will hold a Master’s degree in an area relevant to this project; this could be Artificial Intelligence, Computational Cognitive Science, Computing Science, or Linguistics. A good mastery of NLP and Excellent English communication skills (oral and written) is essential. We would also like you to take a strong interest in multi-valued and other models of natural language meaning, and in machine learning. PhD PROJECT 2: Learning under disagreements between annotators In NLP, human annotators are frequently needed to tell researchers what a given expression “means”, by assigning the expression a label. When human judges disagree about a label (e.g., whether an utterance is offensive or not), it is important that these disagreements be taken into account, as opposed to simply aggregating the values e.g., using reconciliation or majority voting. Such disagreements are now generally recognized to provide information rather than being noise. This PhD project will investigate whether the differences between various sources of disagreement (e.g., noise, ambiguity, and subjective bias) can be detected using statistical models (e.g. cross-entropy, Kullback-Leibler divergence). Last but not least, it will investigate to what extent variations in one person’s verbal behaviour can be understood mathematically in the same way as variations between different speakers. The proposed research would ideally be carried out by someone well versed in information theory and the design and analysis of experiments with human participants. The successful candidate will hold a Master’s degree in an area relevant to this project; this area could be Artificial Intelligence, Computational Cognitive Science, Computing Science, Linguistics, or Statistics. A good mastery of statistics and deep learning is essential; experience with NLP would be beneficial. A good mastery of NLP and Excellent English communication skills (oral and written) is essential. You take a strong interest in at least two of the three following areas: (1) machine learning, (2) natural language, and (3) experimental psychology. Further information about these vacancies can be found at PhD position in Natural Language Processing: statistical models of disagreement between annotators (0.8 – 1.0 FTE) - Working at Utrecht University - Utrecht University (uu.nl) <https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-po…> PhD position in Natural Language Processing: verbal expression of quantities (0.8 - 1.0 FTE) - Working at Utrecht University - Utrecht University (uu.nl) <https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-po…> Deadline for application is 29 May 2023. We’re looking for someone to start as soon as possible after the recruitment process is concluded but we understand that it will normally take a few months before the candidate will be ready to start. Applications should be made through the University's site (see links above). For further information, please contact: - Prof. Massimo Poesio (m.poesio AT uu.nl). - Prof. Kees Van Deemter (c.j.vandeemter AT uu.nl).

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CFPs: PHRAME project closing event
by Luciana Forti 24 May '23

24 May '23

PHRAME: Phraseological complexity measures in learner Italian. Integrating eye tracking, computational and learner corpus methods to develop second language pedagogical resources Closing event Perugia, 27-28 November 2023 CALL FOR PAPERS Phraseological units are ubiquitous in language use (Altenberg, 1998; Sinclair, 1991), crucial in the assessment of overall language proficiency (Paquot, 2018) and central in language processing and development (Siyanova-Chanturia & Pellicer-Sánchez, 2019). But what’s in a phraseological unit? The most recently published literature will point us towards different answers, depending on the different possible perspectives that we may adopt, such as that of corpus linguistics, psycholinguistics or language testing. Our “PHRAME” project has spent the last four years trying to merge these three fields and is now approaching its final phases. The closing event for the “PHRAME” project will take place at the University for Foreigners of Perugia (Italy) on 27th and 28th November 2023. Its aim will be twofold. First, to gather scholars working in the field of phraseology, using a variety of methods to investigate this area of language use, processing, and development. Second, to present the findings of our research project not only in relation to the different adjoining fields upon which it is based (corpus linguistics, psycholinguistics, and computational sciences), but also with respect to the theoretical premises within which it is grounded (complexity theory, usage-based linguistics) and its applicative outputs (a syllabus for teaching Italian phraseology and a language test for assessing phraseological competence in Italian L2). We invite contributions including, but not limited to, the following areas of research: - Corpus-based approaches in the study of L2 phraseology - Psycholinguistic approaches in the study of L2 phraseology - Computational and NLP approaches in the study of L2 phraseology - Complexity theory and second language acquisition studies - Mixed-methods approaches in the study of L2 phraseology - Syllabus design for the development of phraseological competence - Testing and assessing L2 phraseological competence The abstracts for full paper presentations should be written in English. They should not exceed 500 words, references included. The abstract should be sent to progettophrame(a)gmail.com in a Word document containing the following information: - Title of the proposed presentation - Name of the author(s) - Affiliation of the author(s) Keynote speakers of the event will be: - Philip Durrant (University of Exeter) - Gabriele Pallotti (University of Modena and Reggio Emilia) - Anna Siyanova-Chanturia (University of Wellington and Ocean University of China) The presented papers will be collected and published. Participation to the event will be free, but registration will be required. The official languages of the event are Italian and English. Live-streaming of the event will be available. Registration for in-person participation will close on 10th November 2023. Important dates 30 May 2023: First Call for submission of abstracts. Abstract submission opens 30 June 2023: Second and final Call for submission of abstracts 16 July 2023: Abstract submission closes 30 August 2023: Abstract reviews assigned 17 September 2023: Abstract reviews completed 22 September 2023: Notification to authors 10 November 2023: Registration for in-person participation closes 27-28 November 2023: PHRAME closing event Any questions regarding the call for papers and the event may be directed to progettophrame(a)gmail.com. Scientific and organising committee: Giulio Biondi, Veronica D’Alesio, Irene Fioravanti, Luciana Forti, Valentina Franzoni, Sabine Koesters Gensini, Francesca La Russa, Francesca Malagnini, Alfredo Milani, Maria Roccaforte, Valentino Santucci, Stefania Spina, Fabio Zanda. References - Altenberg, B. (1998). On the phraseology of spoken English: The evidence of recurrent word-combinations. In A. P. Cowie (Ed.), Phraseology: Theory, analysis and applications (pp. 101–122). Oxford University Press. - Paquot, M. (2018). Phraseological Competence: A Missing Component in University Entrance Language Tests? Insights From a Study of EFL Learners’ Use of Statistical Collocations. Language Assessment Quarterly, 1–15.< - Sinclair, J. M. (1991). Corpus, Concordance, Collocation. Oxford University Press. - Siyanova-Chanturia, A., & Pellicer-Sánchez, A. (2019). Understanding Formulaic Language A Second Language Acquisition Perspective. Routledge. Web page of the event: PHRAME: Phraseological complexity Measures in learner Italian (Closing event) | | | | | | | | | | | PHRAME: Phraseological complexity Measures in learner Italian (Closing e... Call for Papers Phraseological units are ubiquitous in language use (Altenberg, 1998; Sinclair, 1991), crucial i... | | | --Luciana Forti Ricercatrice t.d. - tipo AL-LIN/01 Glottologia e linguisticaUniversità per Stranieri di PerugiaPiazza Fortebraccio, 4 - 06123 Perugia, Italia

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[Deadline Extended]: The KDD '23 Workshop on Robust NLP for Finance (RobustFin)
by Xiaomo Liu 24 May '23

24 May '23

*The KDD '23 Workshop on Robust NLP for Finance (RobustFin)* Financial services is a document-rich industry. This has led to great demand for advanced NLP techniques to process financial corpora in order to curate knowledge, augment human intelligence, and support industry professionals in making informed business decisions. Recent advances in the NLP domain have motivated the emergence of key applications such as the automation of due diligence protocols, financial question answering (QA) and reasoning, conversational AI in finance, summarizing business entity earnings calls, and analyzing investment sentiment of social media posts. Due to the unique industry standards and regulations, robustness is a fundamental consideration underlying nearly all financial NLP applications. The concept of robsustness may connote many specific definitions and real-life considerations. In finance, the key concerns of robustness refer to better generalizability, higher explainability, lower risk of catastrophic failure in unforeseen circumstances, and diligent fairness considerations. Common NLP models like large language models trained on generic corpora usually deteriorate when processing financial texts despite having achieved state-of-the-art results in other applications. The business and regulatory requirements for explainability and the reasoning behind decision makings for the financial industry are often uncompromising, while many NLP modeling techniques still lack this characteristic. Based on years of research experience in this domain, the organizers recapitulate the key aspects of these challenges: massive volume of data, large variation in the data format, low signal-to-noise ratio, scarcity of expert annotated datasets, task ambiguity, challenges regarding data integrity and privacy, domain shift, and high performance requirements set by industry and regulatory standards. While these challenges have been studied in many generic contexts, we believe working on this vertical high-stakes domain, i.e. finance, will help consolidate the development of solutions. The workshop welcomes original research submissions related to robustness and explainability research on NLP, with a focus on the financial domain and/or financial corpora, which will include, but not be limited to, the topics listed below. The workshop will welcome both position and regular research papers.Topics of Interest The topics of the workshop include, but are not limited to, the following areas: · Adversarial attacks and defense to improve NLP model robustness and privacy protection.· Transfer learning applications and their robustness and explainability studies.· Robustness research against concept drift, domain shift, and noisy datasets; NLP model generalization.· Language modeling on financial corpora including tabular and numerical data, and multi-modal modeling; numeracy and quantitative reasoning, fact verification, and QA over tabular data.· Reconciling structured and unstructured knowledge to improve model interpretability; financial knowledge graph construction.· Few-shot learning and prompt methods.· Synthetic or genuine financial textual datasets and benchmarks.· Reasoning and textual entailment in financial applications.· Empirical studies on robust NLP modelsSubmission GuidelinesWe invite submissions of relevant work that be of interest to the workshop. All submissions must be original contributions that have not been previously published and that are not currently under review by other conferences or journals. Submissions will be peer reviewed, single-blinded. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. All submissions must be in PDF format and follow the current ACM two-column conference format https://www.acm.org/publications/proceedings-template. We accept two types of submissions:· full research paper: no longer than 9 pages (including references, proofs, and appendixes).· short/poster paper: no longer than 4 pages (including references, proofs, and appendixes).Submission will be accepted via Microsoft CMT https://cmt3.research.microsoft.com/RobustFin2023. All accepted papers will be presented in the workshop. At least one author of each accepted submission must attend the workshop to present their work.Important Dates - Paper abstract due: May 16, 2023 AoE - Paper submission due: June 4, 2023 AoE - Submission notification: June 23, 2023 - Workshop: August 7-8, 2023 Organizing Committee· Sameena Shah - JPMorgan AI Research· Xiaodan Zhu - Queen's University· Gerard de Melo - Hasso Plattner Institute and the University of Potsdam· Armineh Nourbakhsh - JPMorgan AI Research· Xiaomo Liu - JPMorgan AI Research· Zhiqiang Ma - JPMorgan AI Research· Charese Smiley - JPMorgan AI Research· Zhiyu Chen - MetaWorkshop Website https://robustfin.github.io/2023/ *Contact* For general inquiries about the workshop, please write to the organizers at robustfin.workshop(a)gmail.com. -- Best, Xiaomo

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Reminder: Professorship in Machine Learning / Data Science, application deadline 4th of June
by Wiegand, Michael 24 May '23

24 May '23

Dear colleagues, applications are still possible for the following professorship: Professor of Machine Learning / Data Science at the University of Klagenfurt, Austria, deadline 4th of June 2023 We are looking for a highly qualified and internationally recognised scientist with high engagement in developing and sustaining an ambitious and innovative research programme. A focus on Explainable AI (XAI), Responsible AI or Trustworthy AI is particularly welcome. The University of Klagenfurt strives to appoint a greater number of women to professorships. Link to advert: https://jobs.aau.at/en/job/professor-of-machine-learning-data-science/ Please spread the word! Best Regards, Michael Wiegand

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Final Call for Papers: KONVENS Teaching for NLP Workshop
by Annemarie Friedrich 24 May '23

24 May '23

KONVENS Teaching for NLP Workshop News: *Submission open*Workshop Date & Venue * September 18, 12pm - 6pm + Workshop Dinner * TH Ingolstadt * Co-located with KONVENS 2023 * Submission Deadline: June 9, 2023 * Notification: July 5, 2023 * Camera Ready Deadline: July 15, 2023Contact konvens-teach4nlp(a)googlegroups.com Workshop website: https://gscl.org/en/events/teach4nlp2023Aim of the Workshop The fast-paced nature of progress in NLP poses unique challenges to educators engaging in curriculum design for NLP courses and NLP-related degree programs. Its rapid growth has led to the creation and revision of thousands of courses and degree programs at universities and online, as well as new educational materials focused on emerging subareas of NLP (e.g., prompting, ethics in NLP systems). For the Workshop on Teaching NLP we propose to bring the NLP community together at KONVENS 2023 to discuss the following topics: * What are key elements of NLP and/or CL curricula? * What adaptations are necessary to cater to different groups (i.e. core computer science students vs. core CL students vs. Digital Humanities students) * What topics should be covered for students studying NLP/CL as major subject, which topics should be covered for students studying NLP/CL as minor subjects? * What is unique about teaching NLP/CL in German speaking contexts? * What challenges do we face when working with German or other non-English languages as a language, data sets, etc.? * What are key differences between regular universities and universities of applied sciences? We invite submissions relating to teaching CL/NLP in applied linguistics, digital humanities, computational linguistics, data science, or computer science.Call for Contributions One of our major goals is to provide resources for teachers and instructors that can last beyond the discussions held on the day of the workshop. We invite 2-3 page short papers or 6-8 page long papers (with unlimited pages of references) that can be position papers on teaching methodology and theory or teaching materials (lecture slides, exercises, project descriptions) with 2-3 page short papers describing the materials. * Tools and methodologies (e.g. teaching with code, active learning, flipped classroom) * Adapting existing curriculum to incorporate new NLP advancements * Choice of topics to cover for different target audiences * Developing courses for (IT) students without linguistics background * Developing courses for students who have non-computer science backgrounds * Teaching NLP in German speaking context (or using other languages than English in general) * Position of NLP in curricula at universities of applied sciences * Ethics, reproducibility, and responsible practices Existing resources for teaching NLP are often scattered across course and faculty web pages or they are outdated, such as the ACL Wiki’s page on Teaching. We plan to join forces with the ACL-wide Teaching NLP workshop to add resources to their repository in order to make our material more generally available. Submission will be single-blind (i.e., they should not be anonymous) and follow the ACL style guidelines. Submission must be electronic via the KONVENS CMT System. Select the Teach4NLP Workshop track during submission. After submitting your paper, you can submit attachments in a second step.Organizers * Margot Mieskes is a Professor for Information Science at the University of Applied Sciences, Darmstadt. She has studied computational linguistics in Stuttgart, Edinburgh, and Cambridge, and did her PhD in Heidelberg. * Jannik Strötgen is a faculty member of FH Karlsruhe. He holds a PhD from the University of Heidelberg. * Christian Wartena holds a PhD from the University of Potsdam. He worked for several companies in Germany and the Netherlands on machine translation, morphological analysis, keyword extraction and recommender systems. Since 2011 he is professor for knowledge and language processing at the University of applied sciences and arts in Hannover, where he teaches courses on natural language processing, text mining, information retrieval and semantic web in the Information Management program. He also regularly teaches NLP courses at the University of Hildesheim. * Annemarie Friedrich is a Professor for Natural Language Understanding at the Faculty of Applied Computer Science at the University of Augsburg, and the Vice President of the GSCL. She holds a PhD in Computational Linguistics from Saarland University and is highly interested in activation concepts in university teaching. * Stefan Grünewald is a PhD student working at Stuttgart University and the Bosch Center for Artificial Intelligence. He is a member of the Enabling team at Bosch, teaching machine learning to Bosch employees with a wide range of job roles. His research interests include syntax (specifically syntactic dependencies) and neural architectures for structured prediction in NLP. Furthermore, his responsibilities within Bosch involve teaching NLP and ML concepts to non-experts.Program Committee * Margot Mieskes * Jannik Strötgen * Christian Wartena * Annemarie Friedrich * Stefan Grünewald * Torsten Zesch * Barbara Plank * Cerstin Mahlow * Ines Rehbein * Alessandra Zarcone * Heike Adel * Nils Reiter * Anette Frank * Heike Adel * Jakob Prange * Ulrike Padó

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Postdoc in grounding language in vision and robotics and others, application deadline: 1 June
by Simon Dobnik 24 May '23

24 May '23

[apologies for x-posting] CLASP Centre for Linguistic Theory and Studies in Probability, at University of Gothenburg has several (2-3 year) postdoctoral positions in computational linguistics and/or natural language processing. Application deadline on June 1, 2023 23:59 (CEST, UTC+2) For details please see https://gu-clasp.github.io/recruitment/ and https://www.gu.se/en/work-at-the-university-of-gothenburg/vacancies If you are interested in the project on grounding language in vision and/or robotics, please contact me at simon.dobnik(a)gu.se Project description: https://web103.reachmee.com/ext/I005/1035/job?site=7&lang=UK&validator=9b89… I am looking for candidates with a strong background in computational linguistics, natural language processing and machine learning, ideally with experience with computational semantics, language modelling and working with multi-modal representations. There is also an opening for a PhD position with specialisation on data privacy, psedonymisation and bias of both training data and ML models within within the Grandma Karl research environment, deadline 27 June, https://web103.reachmee.com/ext/I005/1035/job?site=7&lang=UK&validator=9b89… Best regards, Simon — Simon Dobnik Professor of Computational Linguistics CLASP & FLoV, University of Gothenburg https://www.gu.se/en/about/find-staff/simondobnik

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GenChal proposals @INLG 2023: final call for submissions
by Simon Mille 24 May '23

24 May '23

Hi everyone, if you have any proposal for a shared task related to NLG, don't hesitate to submit it to the GenChal special session at the next INLG, for publicising and/or discussing it with the NLG community! Info below. ======================================= GenChal @ 16th International Conference on Natural Language Generation Prague, Czech Republic, September 11-15 2023 INLG Twitter: @inlgmeeting INLG website:https://inlg2023.github.io/ ======================================= Call for new Shared Task proposals Submission deadline: June 5th 2023 We invite submissions of papers describing ideas for future shared tasks in the general area of language generation (Generation Challenges 2023). Proposed tasks can be in the area of core NLG, or in other research areas in which language is generated. Examples include, but are not limited to: data-to-text NLG, text-to-text generation (including MT and summarisation), combining core NLG and MT, combining core NLG and text summarisation, NLG quality estimation, NLG evaluation metrics, and/or generating language from heterogeneous data, including image and video. The Generation Challenges (GenChal) are an umbrella event designed to bring together a variety of shared-task efforts that involve the generation of natural language. This year, Generation Challenges will be held during a special session at the 16th International Conference on Natural Language Generation (INLG 2023 <https://inlg2023.github.io/>), scheduled on September 11-15 2023. The session will follow the format of previous GenChal results sessions, with presentations of results by the organisers of the generation challenges that are currently running, a poster session for task participants to present their submissions, as well as presentations of proposals for new shared tasks in the Task Proposals Track, and discussion sessions. You can see the previous GenChal tasks on the dedicated repository <https://sites.google.com/view/genchalrepository/home>. Submissions should describe possible future tasks in detail, including information regarding organisers, task description, motivating theoretical interest and/or application context, size and state of completion of data to be used, schedule and evaluation plans. Accepted shared tasks will be run in the 2024 iteration of INLG. Important dates (the dates on the website will be updated soon) - Submission deadline: June 5th 2023 - Notification: July 11th 2023 - Camera-ready submission: July 25th 2023 - INLG conference: September 11th-15th 2023 All deadlines are 11.59 pm UTC -12h ("anywhere on Earth"). Submissions and format Submissions in the Shared Task Proposals track should be no more than 4 (four) pages long excluding citations, and should follow the ACLPUB formatting guidelines <https://acl-org.github.io/ACLPUB/formatting.html> and template files <https://2021.aclweb.org/downloads/acl-ijcnlp2021-templates.zip>. Proposals should be uploaded to the SoftConf <https://softconf.com/n/inlg2023/user/scmd.cgi?scmd=submitPaperCustom&pageid…> GenChal submission page, using the Submission type New shared task proposal. Submissions will be peer-reviewed by the program committee. As reviewing will not be blind, there is no need to anonymise papers. This is not intended to be a selective process, since the aim is to discuss new potential shared tasks with INLG delegates. However, the organisers reserve the right to reject proposals which do not fall within the scope of the GenChal initiative, or which do not follow guidelines. Accepted submissions will be published in separate GenChal 2023 proceedings on the ACL Anthology, as was done in 2022 <https://aclanthology.org/volumes/2022.inlg-genchal/>. Looking forward to seeing you at INLG! Simon, GenChal chair, on behalf of the INLG'23 organisers simon.mille(a)adaptcentre.ie *ADAPT Research Centre / Ionaid Taighde ADAPT* *-* *School of Computing, Dublin City University, Glasnevin Campus / Scoil na Ríomhaireachta, Campas Ghlas Naíon, Ollscoil Chathair Bhaile Átha Cliath*

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PHD THESIS (UClouvain) - CMesure: reliable and adaptive modeling of text readability in French as a foreign language
by Thomas François 24 May '23

24 May '23

Job : Ph.D. student (UClouvain) : CMesure: reliable and adaptive modeling of text readability in French as a foreign language L'UCLouvain recherche un chercheur ou une chercheuse pour un doctorat en traitement automatique du langage - bourse de doctorat à temps plein (100%) pour une durée de quatre ans - pour le Centre de traitement automatique du langage (Cental), de l'Institut langage et communication (ILC) à l’UCLouvain (Louvain-la-Neuve) - entrée en fonction: 1er septembre 2023 (négociable) Cette proposition de bourse de doctorat s’intègre dans le cadre d’un projet de recherche réalisé par le Centre de traitement automatique du langage (CENTAL, https://uclouvain.be/fr/instituts-recherche/ilc/cental), en collaboration avec FEI (France Éducation International, https://www.france-education-international.fr/). Le projet visera à développer un modèle d’évaluation automatisé de la lisibilité des textes pour le français langue étrangère (FLE). Il s’agira d’évaluer comment des algorithmes d’intelligence artificielle poussés permettraient de rendre des formules de lisibilité plus personnalisées, notamment en prenant en compte le type de lecture pratiquée, le genre du texte et la langue maternelle du lecteur. Dans un second temps, le projet visera à intégrer cette formule adaptative au sein d’un moteur de recherche pédagogique de textes en FLE, dont la pertinence des résultats sera évaluée par des professionnels du FLE. Ce projet bénéficie de plusieurs atouts. D’une part, il est ancré au sein d’un laboratoire dans les recherches en lisibilité sont reconnus internationalement. D’autre part, il profitera d’un partenariat stratégique avec France Éducation Internationale et d’un accès à des textes utilisés pour les examens certificatifs du DELF et du DALF, textes calibrés sur l’échelle du cadre européen commun de référence pour les langues (CECR). Cela constituera en un point de départ pour l’élaboration d’un modèle de lisibilité pour le FLE qui soit (1) plus fiable, car entraîné sur des données rigoureusement calibrées, et qui permette (2) d’explorer une question fondamentale en lisibilité, mais jamais étudiée à notre connaissance : l’impact de la langue maternelle sur les modèles, ainsi que celui du genre de texte et du type de lecture. Au sein de projet, le rôle du doctorant ou de la doctorante engagé consistera à mener l’essentiel de la recherche, à savoir (1) développer de nouvelles variables de lisibilité aptes à prendre en compte les caractéristiques pédagogiques et de genre des textes analysés ; (2) mettre au point un modèle machine learning (classique et/ou deep learning) non adaptatif à partir des textes du DELF et du DALF ; (3) mettre au point un modèle adaptatif et le comparer à sa version non adaptative et (4) intégrer ce modèle de lisibilité au sein d’un moteur de recherche adaptatif. Le chercheur ou la chercheuse devra également assurer la diffusion des résultats obtenus via des publications scientifiques et rédiger une thèse de doctorat. Il ou elle sera amené à collaborer étroitement avec les autres membres de l’équipe en vue d’assurer la bonne réalisation de ces tâches. Environment de travail : Le CENTAL est rattaché à l’Institut Langage & Communication (https://uclouvain.be/fr/instituts-recherche/ilc), qui fait partie de l’UCLouvain. Cette université est située à Louvain-la-Neuve (https://uclouvain.be/fr/sites/louvain-la-neuve), une ville piétonne, agréable à vivre et très dynamique. Le projet de recherche sera réalisé sous la direction du Pr. Thomas François (https://thomasfrancoisucl.wixsite.com/homepage), expert en lisibilité et en simplification automatique de la langue. Des missions à Paris (Sèvres) sont prévues afin d’assurer une bonne collaboration avec FEI. Cet organisme est mondialement reconnu pour son expertise dans le domaine de l’évaluation des niveaux de compétence en français langue étrangère (FLE) et est en charge de l’organisation des principaux tests de langues en français, à savoir le TCF, le DELF, ou le DAFL. Qualifications et aptitudes requises Le candidat répondra aux qualifications suivantes : * Être porteur d’un master en Linguistique computationelle, en Traitement automatique du langage (TAL), ou en Informatique (option en Intelligence artificielle). * Faire montre d’un excellent parcours académique * Disposer de bonnes compétences informatiques : * langages de programmation : Python, R (ou similaire) * la connaissance de scikit-learn, pandas, tensorflow/keras et/ou pytorch * systèmes : Linux de préférence * Bonne connaissance des principaux outils et algorithmes du TAL. La connaissance des réseaux de neurones profonds est un plus. * Excellente maîtrise du français (niveau C1 minimum) et bonne connaissance de l’anglais (niveau B2 minimum) * Autonomie, curiosité, sens du travail en équipe, capacité d’écoute et d’analyse des besoins, réactivité. Conditions d’engagement : Cette bourse de doctorat est soumise aux conditions suivantes : * À la date d’engagement, le doctorant doit être titulaire depuis au maximum 3 ans* d’un grade académique de master 120 crédits ou d’un grade reconnu comme équivalent. * Le montant net de la bourse est d’environ 2 370 euros par mois. * Le délai maximum fixé ci-dessus est augmenté d’une année par accouchement et/ou par adoption. Dossier de candidature : Date limite de remise du dossier : 22 juin Si vous êtes intéressé par ce poste, merci d'envoyer votre dossier de candidature à Thomas François par mail (thomas.francois(a)uclouvain.be). Celui-ci devra inclure : 1. un curriculum vitae détaillé en français ou anglais reprenant les différentes qualifications et aptitudes requises, les détails de votre parcours académique (grades, listes de cours), ainsi que les éventuelles publications et autres expériences académiques et scientifiques ; 2. une lettre de motivation en français, décrivant votre intérêt pour le poste, comment votre profil répond à la description du poste et aux objectifs du projet, etc. (maximum 2 pages) ; 3. une lettre de référence en français ou en anglais de la part d’un ou d’une de vos professeur(e)s. Les candidats retenus seront invités à participer à un entretien via vidéo-conférence selon des modalités qui leur seront ensuite transmises par mail. Plus d'informations : Les questions concernant le poste ou la procédure de candidature doivent être envoyées par e-mail à Thomas François (thomas.francois(a)uclouvain.be) avant le 15 juin. Pr. Thomas François Chargé de cours en linguistique appliquée Faculté de Philosophie, Arts et Lettres Université catholique de Louvain Institut Langage et Communication, PLIN, CENTAL et TeaMM Place Montesquieu, 3 - box L2.06.04 • B-1348 Louvain-la-Neuve • Belgium Tél. : +32 (0)10 / 47 37 36

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