- Corpora - ELRA lists

CFP: FICTA-2023, Cardiff Metropolitan University, United Kingdom || Springer SIST Series (Scopus Indexed) || Paper Submission Deadline: 10 December 2022
by Sandeep Sengar 01 Dec '22

01 Dec '22

Dear Researchers, We are happy to inform you that the Eleventh International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2023) will be organized by Cardiff Metropolitan University, United Kingdom. We invite you to participate in FICTA-2023: https://ficta.co.uk/ on 11-12 April 2023, being organized in a hybrid mode. Publication: All FICTA 2023 registered and presented papers will be published in conference proceedings by Springer-Smart Innovation, Systems and Technologies (SIST) Series (https://www.springer.com/series/8767). Topics of interest: Submissions of quality papers are expected in all areas of research and application in intelligent computing, refer call for papers at https://ficta.co.uk/call-for-papers. Call for Special Session Proposals: If interested in floating/organizing a special session please visit the link and follow the necessary guidelines: https://ficta.co.uk/call-for-sessions For any queries related to the conference you may feel free to e-mail: FICTA2023(a)cardiffmet.ac.uk Thank you -- Warm Regards, *Sandeep Singh Sengar*, Lecturer in Computer Science Cluster Leader Computer Vision / Image Processing Cardiff Metropolitan University, Cardiff, UK CF5 2YB *-------------------------------------------------------------------------------* *Email: SSSengar(a)cardiffmet.ac.uk <SSSengar(a)cardiffmet.ac.uk>* *Web: **https://sites.google.com/view/sandeepsengar <https://sites.google.com/view/sandeepsengar>*

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Research Associate (post-doc) in Machine Learning for Natural Language Processing @ The University of Sheffield (deadline 07/12)
by Carol Scarton 01 Dec '22

01 Dec '22

Hi all, We are hiring a Research Associate (post-doc) to work on one of our NLP projects at the University of Sheffield. The successful candidate will be expected to lead the design and development of strategies for more transparent machine learning models to generate accurate cross-lingual representations for idiomatic language, as well as to contribute to the design and development of resources and evaluation of downstream tasks, like machine translation. For both lines of research, you will build on state-of-the-art approaches based on deep learning. The applicants should hold a PhD (or be close to completion) or have equivalent work experience and a strong publication record. Solid knowledge of Machine Learning models applied to Natural Language Processing and Deep Learning is required, as is excellent programming skills in Python and deep learning frameworks (esp. Keras, TensorFlow or PyTorch). Previous experience developing word embedding models and/or Machine Translation is also desirable. Deadline for applications: 07/12/2022 More details, including how to apply can be found in the following link: bit.ly/3gnGP4l <https://t.co/KvevJ2LPoS> Kind regards, Carol -- *Carolina Scarton* Lecturer in Natural Language Processing Department of Computer Science University of Sheffield http://staffwww.dcs.shef.ac.uk/people/C.Scarton/

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1st CFP of the 7th International Conference on Innovations and Creativity (ICIC 2023)
by Dariush Alimohammadi 01 Dec '22

01 Dec '22

Dear All, Please share the CFP of 7th International Conference on Innovations and Creativity (ICIC 2023) to be held in Liepaja, Latvia in June 2023 with your colleagues. ICIC covers a wide range of topics from Mathematics and Computer Science to Art, Energy and Environmental Science. Check out Call For Papers and Deadlines at: http://icic.liepu.lv/ Kind regards, -- Dariush Alimohammadi, PhD, Professor, Faculty of Science and Engineering, Liepaja University, Liepaja, Latvia.

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[IberLEF 2023] Last Call for Task Proposals
by Salud María Jiménez Zafra 01 Dec '22

01 Dec '22

================================= *IberLEF 2023 -- Call for Task Proposals* ================================= The goal of IberLEF is to encourage the research community to organize competitive text processing, understanding and generation tasks, with the aim of defining new research challenges and advancing the state of the art in Natural Language Processing challenges involving at least one of the following Iberian languages: Spanish, Portuguese, Catalan, Basque or Galician. Researchers and practitioners from all areas of Natural Language Processing and related communities are invited to submit task proposals that fit IberLEF goals *by December 5, 2022.* Proposals must be submitted (as a pdf file) to iberlef(a)googlegroups.com, and should include the following fields: ● Title of the task. ● Description of the task, highlighting: ○ Relevance and novelty of the task, and the challenges involved. ○ Evaluation measures, and other relevant methodological aspects. ○ Expected target community, and actual or potential industrial take up. ○ Related evaluation activities, if any. ○ Previous editions of the task, if any. If it has been organized previously, what the roadmap is and what the novelties for 2023 are. ○ Linguistic resources to be gathered, created and/or reused. Please include as many details on data gathering, selection and annotation procedures as possible: sources and representativity, training/validation/test sizes, harvesting procedures, profile of annotators (experts, linguists, crowdworkers, etc.), multiple annotation policy, IPR issues, baselines, etc. ● Tentative schedule (note that camera ready versions of the proceedings must be ready *by July 6, 2023*). ● Organization committee: full name and affiliation of the organizers, with a succinct description of their research interests, areas of expertise and experience organizing similar events. ● Funding, if available. ● Contact person. ● Any other relevant issues. *Task organizers duties* Note that organizers of accepted tasks are expected to: ● Setup the evaluation exercise according to the submitted proposal. ● Promote the task within the target research community. ● Manage the submission and scientific evaluation of the system description papers of the corresponding systems submitted by the participants. The accepted papers will be published in the IberLEF proceedings. ● Prepare and submit an overview of the evaluation exercise. ● Present the results of the task at IberLEF 2023. *Task selection procedure* Each submitted proposal will be reviewed by members of the IberLEF steering and program committee, and decisions will be sent back to the task organizers by* January 16, 2023*. *Proceedings* IberLEF 2023 Proceedings including the description of the participating systems will be published at CEUR-WS.org. Task Overviews will be published in the journal *Natural Language Processing* ( http://www.sepln.org/en/journal, indexed in Clarivate ESCI and Elsevier SJR) in its September 2023 issue. Task Organizers are expected to send the camera ready task and system description papers for their task to IberLEF organizers by *July 6, 2023*. *Important dates* ● Task proposals due: December 5, 2022. ● Notification of acceptance: January 16, 2023. ● Camera ready submissions due: July 6, 2023. ● IberLEF Workshop: September 2023. *IberLEF general chairs*: Salud María Jiménez Zafra, SINAI, Universidad de Jaén (Spain) Manuel Montes y Gómez, INAOE (Mexico) Francisco Rangel, Symanto Research (Spain) *Contact* E-mail: iberlef(a)googlegroups.com [image: Universidad de Jaén] <http://www.uja.es/> *Salud María Jiménez Zafra* sjzafra(a)ujaen.es Universidad de Jaén Grupo de Investigación SINAI <http://sinai.ujaen.es/> | Departamento de Informática EPS Jaén, Edificio A3, Despacho 219 Campus Las Lagunillas s/n 23071 - Jaén | +34 953212992 [image: Universidad de Jaén] <http://www.uja.es/>

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UK Jobs in Computing and Data Science
by Eric Atwell 30 Nov '22

30 Nov '22

Promotion opportunities: Head of the School of Computing<https://jobs.leeds.ac.uk/vacancy.aspx?ref=ASN-84381> University of Leeds Lecturers in Computer Science<https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSCP1116> University of Leeds Lecturer in Computer Science<https://jobs.leeds.ac.uk/vacancy.aspx?ref=SWJTU1007> University of Leeds Teaching Assistants in Computer Science<https://jobs.leeds.ac.uk/vacancy.aspx?ref=EPSCP1115> University of Leeds Data Engineering Developer<https://jobs.leeds.ac.uk/vacancy.aspx?ref=ITDSV1000> University of Leeds Data Analyst<https://jobs.leeds.ac.uk/vacancy.aspx?ref=ITDSV1002> University of Leeds Professor in Artificial Intelligence<https://www.linkedin.com/jobs/view/3375574406/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Manchester Metropolitan University Professor in Data Science<https://www.linkedin.com/jobs/view/3381166449/?eBP=JYMBII_JOBS_HOME_ORGANIC…> University of the Arts London Deputy Dean, Faculty of Computing,<https://www.linkedin.com/jobs/view/3376789059/?eBP=JYMBII_JOBS_HOME_ORGANIC…> De Montford University Leicester Professor in Creative Computing<https://www.linkedin.com/jobs/view/3381171110/?eBP=JYMBII_JOBS_HOME_ORGANIC…> University of the Arts London Programme Director - Computing<https://www.linkedin.com/jobs/view/3368580632/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Kaplan International, Leeds office Professor/Reader of Statistical Data Science<https://www.linkedin.com/jobs/view/3373317196/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Newcastle University Professor in Fintech<https://www.linkedin.com/jobs/view/3356652057/?eBP=JYMBII_JOBS_HOME_ORGANIC…> University of East London Director of Education<https://www.linkedin.com/jobs/view/3344955080/?eBP=JYMBII_JOBS_HOME_ORGANIC…> HyperionDev Computing Education Senior Lecturer/Associate Professor: Data Science<https://www.linkedin.com/jobs/view/3374847671/?eBP=JYMBII_JOBS_HOME_ORGANIC…> Falmouth University

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NLDB 2023 CFP
by Max Silberztein 30 Nov '22

30 Nov '22

Dear Madam/Sir, Please forward this CFP to corpora-list's members Regards --Max Silberztein NLDB 2023 The 28th International Conference on Natural Language & Information Systems 21-23 June 2023, University of Derby, United Kingdom. https://www.derby.ac.uk/events/latest-events/nldb-2023/ About NLDB The 28th International Conference on Natural Language & Information Systems will be held at the University of Derby, United Kingdom and will be a face to face event. Since 1995, the NLDB conference brings together researchers, industry practitioners, and potential users interested in various application of Natural Language in the Database and Information Systems field. The term "Information Systems" has to be considered in the broader sense of Information and Communication Systems, including Big Data, Linked Data and Social Networks. The field of Natural Language Processing (NLP) has itself recently experienced several exciting developments. In research, these developments have been reflected in the emergence of neural language models (Deep Learning, Word Embeddings, Transformers) and the importance of aspects such as transparency, bias and fairness, a (renewed) interest in various linguistic phenomena, such as in discourse and argumentation mining, and in new problems such as the detection of disinformation and hate speech in social media, as well of mental health disorders that increased during the recent pandemic. Regarding applications, NLP systems have evolved to the point that they now offer real-life, tangible benefits to enterprises. Many of these NLP systems are now considered a de-facto offering in business intelligence suites, such as algorithms for recommender systems and opinion mining/sentiment analysis. It is against this backdrop of recent innovations in NLP and its applications in information systems that the 28th edition of the NLDB conference takes place. We welcome research and industrial contributions, describing novel, previously unpublished works on NLP and its applications across a plethora of topics as described in the Call for Papers. Call for Papers NLDB 2023 invites authors to submit papers for oral or poster presentations on unpublished research that addresses theoretical aspects, algorithms, applications, architectures for applied and integrated NLP, resources for applied NLP, and other aspects of NLP, as well as survey and discussion papers. This year's edition of NLDB also introduces an Industry Track, to foster fruitful interaction between the industry and the research community. Topics of interest include but are not limited to: Social Media and Web Analytics: Opinion mining/sentiment analysis, irony/sarcasm detection; detection of fake reviews and deceptive language; detection of harmful information: fake news and hate speech; sexism and misogyny; detection of mental health disorders; identification of stereotypes and social biases; robust NLP methods for sparse, ill-formed texts; recommendation systems. Deep Learning and eXplainable Artificial Intelligence (XAI): Deep learning architectures, word embeddings, transparency, interpretability, fairness, debiasing, ethics. • Argumentation Mining and Applications: Automatic detection of argumentation components and relationships; creation of resource (e.g. annotated corpora, treebanks and parsers); Integration of NLP techniques with formal, abstract argumentation structures; Argumentation Mining from legal texts and scientific articles. • Question Answering (QA): Natural language interfaces to databases, QA using web data, multi-lingual QA, non-factoid QA(how/why/opinion questions, lists), geographical QA, QA corpora and training sets, QA over linked data (QALD). • Corpus Analysis: multi-lingual, multi-cultural and multi-modal corpora; machine translation, text analysis, text classification and clustering; language identification; plagiarism detection; information extraction: named entity, extraction of events, terms and semantic relationships. • Semantic Web, Open Linked Data, and Ontologies: Ontology learning and alignment, ontology population, ontology evaluation, querying ontologies and linked data, semantic tagging and classification, ontology-driven NLP, ontology-driven systems integration. • Natural Language in Conceptual Modelling: Analysis of natural language descriptions, NLP in requirement engineering, terminological ontologies, consistency checking, metadata creation and harvesting. • Natural Language and Ubiquitous Computing: Pervasive computing, embedded, robotic and mobile applications; conversational agents; NLP techniques for Internet of Things (IoT); NLP techniques for ambient intelligence • Big Data and Business Intelligence: Identity detection, semantic data cleaning, summarisation, reporting, and data to text. Important Dates: Full paper submission: 14 March, 2023 Paper notification: 10 April, 2023 Camera-ready deadline: 24 April, 2023 Conference: 21-23 June 2023 Submission Guidelines Authors should follow the LNCS format (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu… ) and submit their manuscripts in pdf via Easychair (https://easychair.org/conferences/?conf=nldb2023 ) Submissions can be full papers (12 pages maximum including references), short papers (8 pages including references) or papers for a poster presentation or system demonstration (6 pages including references). The programme committee may decide to accept some full papers as short papers or poster papers. The reviewing process of NLDB 2023 is double-blind, i.e., submissions to the main conference and to the industry track must not contain author names or other identifying information, such as funding sources, acknowledgments and must use the third person to refer to work the authors have previously undertaken. System demonstration papers may not be anonymous. Committee Conference Chairs: Manning Warren, University of Derby, UK Métais Elisabeth, Conservatoire des Arts et Métiers, Paris, France Meziane Farid, University of Derby, UK Program Chairs: Reiff-Marganiec Stephan, University of Derby, UK Sugumaran Vijayan, Oakland University, Rochester, USA Programme Committee: Abdi Asad, University of Derby, UK. Akoka Jacky, CNAM & TEM, France Anselma Luca, University of Turin, Italy Bajaj Ahsaas, University of Massachusetts Amherst, USA Balakrishna Mithun, Limba Corp, USA Banerjee Somnath, University of Milano-Bicocca, Italy Bensalem Imene, MISC Lab, Constantine 2 University, Algeria Bosco Cristina, University of Turin, Italy Braschler Martin, ZHAW School of Engineering, Switzerland Buscaldi Davide, University Sorbonne Paris Nord, France Cabrio Elena, Université Côte d’Azur, Inria, CNRS, I3S, France Caselli Tommaso, Rijksuniversiteit Groningen, The Netherlands Chiruzzo Luis, Universidad de la República, Uruguay Cignarella Alessandra Teresa, University of Turin, Italy Cimiano Philipp, Bielefeld University, Germany Croce Danilo, University of Rome "Tor Vergata", Italy Delgado Agustín, Universidad Nacional de Educación a Distancia, Spain Dinu Liviu, University of Bucharest, Romania Doucet Antoine, La Rochelle University, France Fersini Elisabetta, University of Milano-Bicocca, Italy Florio Komal, University of Turin, Italy Fomichov Vladimir, Moscow Aviation Institute, Russia Fornaciari Tommaso, Bocconi University Milan, Italy Franco Marc, Symanto, Germany/Spain Frasincar Flavius, Erasmus University Rotterdam, The Netherlands Hacohen-Kerner Yaakov, Jerusalem College of Technology, Israel Horacek Helmut, DFKI, Germany Ienco Dino, IRSTEA, France Iglesias Carlos A., Universidad Politécnica de Madrid, Spain Ittoo Ashwin, HEC, Univ. of Liege, Belgium Kapetanios Epaminondas, University of Hertfordshire, UK Kedad Zoubida, UVSQ, France Kop Christian, University of Klagenfurt, Austria Koufakou Anna, Florida Gulf Coast University, USA Laatar Rim, University of Sfax, Tunisia Lai Mirko, University of Turin, Italy Lopez Cédric, Emvista, Montpellier, France Loukachevitch Natalia, Moscow State University, Russia Aaisha Makkar, University of Derby Mandl Thomas, University of Hildesheim, Germany Martínez Paloma, Universidad Carlos III de Madrid, Spain Martínez Patricio, Universidad de Alicante, Spain Martínez Unanue Raquel, Universidad Nacional de Educación a Distancia, Spain Masmoudi Abir, LIUM, University of Le Mans, France Mazzei Alessandro, University of Turin, Italy Métais Elisabeth, Conservatoire des Arts et Métiers, France Meziane Farid, University of Derby, UK Mich Luisa, University of Trento, Italy Mimouni Nada, Conservatoire des Arts et Métiers, France Mitrović Jelena, University of Passau, Germany Montalvo Soto, Universidad Rey Juan Carlos, Spain Montes y Gómez Manuel, INAOE Puebla, Mexico Monti Johanna, L'Orientale University of Naples, Italy Muñoz Rafael, Universidad de Alicante, Spain Okky-Ibrohim Muhammad, University of Turin, Italy Passaro Lucia, University of Pisa, Italy Patti Viviana, University of Turin, Italy Picca Davide, Columbia University, USA Plaza Laura, Universidad Nacional de Educación a Distancia, Spain Rangel Francisco, Symanto, Germany/Spain Reyes Antonio, Autonomous University of Baja California, Mexico Roche Mathieu, Cirad, TETIS, France Rosso Paolo, Universitat Politècnica de València, Spain Saggion Horacio, Universitat Pompeu Fabra, Spain Sakketou Flora, Philipps-Marburg University Sanguinetti Manuela, Università degli Studi di Cagliari, Italy Silberztein Max, Université de Franche-Comté, France Sprugnoli Rachele, Catholic University of the Sacred Heart Milan, Italy Sugumaran Vijayan, Oakland University, Rochester, USA Tagarelli Andrea, University of Calabria, Italy Taulé Mariona, Universitat de Barcelona, Spain Teisseire Maguelonne, Irstea, TETIS, France Tomás David, Universidad de Alicante, Spain Tufis Dan, RACAI, Bucharest, Romania Uban Ana Sabina, University of Bucharest, Romania Ureña-López Alfonso, Universidad de Jaén, Spain Vadera Sunil, University of Salford, UK Valencia-Garcia Rafael, Universidad de Murcia, Spain Villatoro Esaú, Idiap Research Institute, Switzerland Wattiau Isabelle, ESSEC, France Zaghouani Wajdi, Hamad Bin Khalifa University, Qatar Zubiaga Arkaitz, Queen Mary University of London, UK

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Research internship: Quantifying diversity of language phenomena: Case study of multiword expressions (5-6 months, LIFAT, Blois, France)
by Agata Savary 30 Nov '22

30 Nov '22

RESEARCH INTERNSHIP *Quantifying diversity of language phenomena: Case study of multiword expressions* (LIFAT, Blois, France) We propose a master internship position in Blois (France). Please send an email to apply, with a CV, a transcript of bachelor and master grades, and a few lines explaining your motivation to Arnaud Soulet <arnaud.soulet(a)univ-tours.fr> <mailto:arnaud.soulet@univ-tours.fr>, as well as Agata Savary and Thomas Lavergne <first.last(a)universite-paris-saclay.fr> <mailto:first.last@universite-paris-saclay.fr>. Internship proposal description: https://selexini.lis-lab.fr/jobs/2022/11/26/internship Application deadline: *December 8*, 2022 (or until filled) ------ MOTIVATION AND CONTEXT *Diversity* of naturally occurring phenomena is a vital heritage to be preserved in the current progress- and optimization-driven globalization era. Diversity has been quantified in many domains: ecology, economy, information science, etc. but less so in *Natural Language Processing* (NLP). Recently, we have been addressing this aspect with respect to a particular linguistic phenomenon: the one of *multiword expressions * (MWEs). MWEs, such as (FR) /casser sa pipe/ ‘to die’ (literally to break one’s pipe) or (FR) /sortir du lot /'to be better than others' (literally to quit the batch), are groups of words which exhibit unexpected properties (Baldwin & Kim, 2010; Constant et al. 2017). Most prominently, their meaning does not straightforwardly derive from the meanings of their components. Language resources dedicated to MWEs include MWE lexicons and MWE-annotated corpora (Savary et al., 2017), while a major computational task is to *automatically identify MWEs *in running text. The PARSEME network has been addressing the MWE identification task via a series of *shared tasks* on automatic identification of verbal MWEs (Ramisch et al. 2020). Our recent work (Lion-Bouton, 2021; Lion-Bouton et al. 2022) is explicitly dedicated to *quantifying diversity in MWE language resources and MWE identification systems*. We have adapted measures of *variety* (number of types in a system), *balance* (equity of items in various types) and *disparity* (differences between types), stemming notably from ecology and information theory (Morales 2021). ------ OBJECTIVE The objective of this internship is to extend the formalisation of the diversity by benefiting from *Good-Turing frequency estimation*. Successfully used to estimate the biomass, Good-Turing frequency estimation is a statistical technique for estimating the probability of encountering an object of an unseen species, given a set of past observations of objects from different species (Good, 1953). Under this same principle, the idea would be to *estimate the number of unseen MWEs from the MWEs observed *in the corpus. Thus, it will be possible to correct the diversity measures to take the unseen MWEs into account and to evaluate the possible selection bias of the corpus.

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Job announcement: PhD/Postdoc in the NLP group at the University of Mannheim
by Simone Paolo Ponzetto 30 Nov '22

30 Nov '22

The NLP Group at the University of Mannheim [1] invites applications for ONE PHD/POSTDOCTORAL RESEARCHER IN NATURAL LANGUAGE PROCESSING Applicants should have a strong (undergraduate/graduate) profile in computer science, NLP, AI, machine learning or a related discipline. Applicants for the postdoc position are expected to have a proven academic track record (as demonstrated by publications at top-tier conferences) and be good team players. The researcher will be located at the NLP group of the University of Mannheim, which is part of the larger DWS Group [2] – see DBLP [3] for a list of publications and research topics we work on. Mannheim is a very multicultural city in the south-west of Germany, we offer a sustainable life/work balance and non-toxic academic environment. We are strongly committed to diversity and welcome applications from members of underrepresented groups. Duration: 2-3 years depending on the position and qualification. Salary range: according to German public scale TV-L E13 100% (full time, commensurate with experience and qualifications). Applications can be made per e-mail (jobs(a)informatik.uni-mannheim.de<mailto:jobs@informatik.uni-mannheim.de>) and should include a research statement and CV including a list of publications and published software. All documents should be e-mailed as a single PDF. All applications sent before December 20 2022 will receive full consideration. The positions remain open until filled. Potential applicants are welcome to get in touch with Simone Paolo Ponzetto for informal enquiries before applying. Thanks! Simone [1] http://dws.informatik.uni-mannheim.de/nlp [2] http://dws.informatik.uni-mannheim.de [3] https://dblp.org/pid/04/2532 -- Simone Paolo Ponzetto Data and Web Science Group University of Mannheim, Germany http://dws.informatik.uni-mannheim.de/ponzetto Tel: +49 621 181 2647

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Learning With Disagreements - task11 @Semeval2023: presentation of task and Invitation to online meeting with organizers
by Elisa Leonardelli 30 Nov '22

30 Nov '22

Dear All, We are pleased to announce an online meeting with the organizers of the task Learning With Disagreements (LeWiDi) shared task @Semeval2023, to find out more about the task. *WHEN?* FRIDAY, 2TH DEC 2022, 1 p.m. CET *WHERE?* ON ZOOM *WHO?* The online meeting is open to everyone who is interested in the task, also who's not subscribed yet *WHAT?* The meeting will be structured as follow: - introduction to datasets and task from the organisers - Q&A time *HOW?* find the details of the meeting: - on the pages of our codalab competition https://codalab.lisn.upsaclay.fr/competitions/6146 - by adding the event on your calendar at the following link *https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=N3RzMHJmcHBib29jYTZlNG9wcXBwYWhpb3AgbGV3aWRpc2VtZXZhbDIwMjNAbQ&tmsrc=lewidisemeval2023@gmail.com <https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=N3RzMHJmcH…>* We hope to see you numerous at the meeting! ------------------------------------------------------------------------------- *ABOUT THE TASK * The assumption that natural language expressions have a single and clearly identifiable interpretation is more and more recognized as just a convenient idealization. Focus of LeWiDi task is entirely on subjective tasks, where usage of aggregated labels makes much less sense. The objective of the LeWiDi task is to provide a unified testing framework for learning from disagreements and developing methods able to capture them, using datasets containing disaggregated annotations. We propose 4 diverse (textual) datasets: - with different characteristics in terms of genres (social media and conversations), languages (English and Arabic), tasks (misogyny, hate speech, offensiveness detection) and annotations' methodology (experts, specific demographic groups, AMT-crowd) - all datasets are equipped with disaggregated annotations - all datasets provides relevant information about annotators We developed an *harmonized json format* for the 4 datasets so to encourage participants in *developing methods able to capture agreements/disagreements*, rather than focusing on developing the best model for each dataset Performance is evaluated using two metrics: 1. 'classical hard evaluation' (F1): how well the model predicts the aggregated labels (binary, based on majority) 2. 'soft' evaluation' (cross-entropy): how well the model's probabilities reflect the level of agreement among annotators An ideal model would have high F1 and low cross-entropy results. PARTECIPATE: get the data and participate https://codalab.lisn.upsaclay.fr/competitions/6146 CONTACT US: le-wi-di-semeval2023_contactus(a)googlegroups.com DATES: Current status: train and dev are released, unlimited submissions via Codalab are allowed (evaluation on dev) January 10, 2023: evaluation phase starts, unlabeled test is released. Limited submissions on Codalab are allowed (evaluation on test) February 2023: Participant paper submission March 2023: Peer review notification April 2023: Camera-ready participant papers submission Summer 2023: SemEval workshop (co-located with a major NLP conference) ORGANIZERS: Elisa Leonardelli, Fondazione Bruno Kessler (FBK), Italy Gavin Abercrombie, Heriot-Watt University, United Kingdom Valerio Basile, Torino University, Italy Tommaso Fornaciari, Bocconi University, Italy Barbara Plank, IT University of Copenhagen, Denmark Verena Rieser, Heriot-Watt University, United Kingdom Massimo Poesio, Queen Mary University of London, United Kingdom Alexandra Uma, Queen Mary University of London, United Kingdom Best regards, the LeWiDi organizers -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material. -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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Monthly online ILFC Seminar: interactions between formal and computational linguistics
by Timothée Bernard 30 Nov '22

30 Nov '22

*Monthly online ILFC Seminar: interactions between formal and computational linguistics* https://gdr-lift.loria.fr/monthy-online-ilfc-seminar/ GdR LIFT is happy to announce the three forthcoming sessions of the ILFC seminar on the interactions between formal and computational linguistics: - 2022/12/14 16:00-17:00 UTC+1: *Guy Emerson* (University of Cambridge; 15:00-16:00 UTC+0) Title: *Learning meaning in a logically structured model: An introduction to Functional Distributional Semantics* Abstract: *The aim of distributional semantics is to design computational techniques that can automatically learn the meanings of words based on the contexts in which they are observed. The mainstream approach is to represent meanings as vectors (such as Word2Vec embeddings, or contextualised BERT embeddings). However, vectors do not provide a natural way to talk about basic concepts in logic and formal semantics, such as truth and reference. While there have been many attempts to extend vector space models to support such concepts, there does not seem to be a clear solution. In this talk, I will instead go back to fundamentals, questioning whether we should represent meaning as a vector I will present the framework of Functional Distributional Semantics, which makes a clear distinction between words and the entities they refer to. The meaning of a word is represented as a binary classifier over entities, identifying whether the word could refer to the entity – in formal semantic terms, whether the word is true of the entity. The structure of the model provides a natural way to model logical inference, semantic composition, and context-dependent meanings, where Bayesian inference plays a crucial role. The same kind of model can also be applied to different kinds of data, including both grounded data such as labelled images (where entities are observed) and also text data (where entities are latent). I will discuss results on semantic evaluation datasets, indicating that the model can learn information not captured by vector space models like Word2Vec and BERT. I will conclude with an outlook for future work, including challenges and opportunities of joint learning from different data sources.* - 2023/01/18 17:00-18:00 UTC+1: *Carolyn Anderson* (Wellesley College; 11:00-12:00 UTC-5) Title: [TBA] Abstract: [TBA] - 2023/02/15: *Steven T. Piantadosi* (UC Berkeley) Title: [TBA] Abstract: [TBA] The seminar is held on Zoom. To attend the seminar and get updates, please subscribe to our mailing list (we now only rarely communicate through other mailing lists): https://sympa.inria.fr/sympa/subscribe/seminaire_ilfc

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2024

2023

2022