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NLPerspectives 2nd CfP
by Abercrombie, Gavin 09 Jan '24

09 Jan '24

NLPerspectives: The 3rd Workshop on Perspectivist Approaches to NLP Collocated with LREC-COLING in Turin, Italy 2ND CALL FOR PAPERS https://nlperspectives.di.unito.it/w/3rd-workshop-on-perspectivist-approach… Until recently, the dominant paradigm in natural language processing (and other areas of artificial intelligence) has been to resolve observed label disagreement into a single “ground truth” or “gold standard” via aggregation, adjudication, or statistical means. However, in recent years, the field has increasingly focused on subjective tasks, such as abuse detection or quality estimation, in which multiple points of view may be equally valid, and a unique ‘ground truth’ label may not exist (Plank, 2022). At the same time, as concerns have been raised about bias and fairness in AI, it has become increasingly apparent that an approach which assumes a single “ground truth” can erase minority voices. Strong perspectivism in NLP (Cabitza et al., 2023) pursues the spirit of recent initiatives such as Data Statements (Bender and Friedman, 2018), extending their scope to the full NLP pipeline, including the aspects related to modelling, evaluation and explanation. In line with the first<https://nlperspectives.di.unito.it/w/w2022/> and second<https://nlperspectives.di.unito.it/w/2nd-workshop-on-perspectivist-approach…> editions, the third NLPerspectives (Perspectivist Approaches to Disagreement in NLP) workshop will explore current and ongoing work on: the collection and labelling of non-aggregated datasets; and approaches to modelling and including these perspectives in NLP pipelines, as well as evaluation and applications of multi-perspective Machine Learning models. We also welcome opinion pieces and literature reviews, e.g., fairness and inclusion in a perspectivist framework. Following our previous workshops, a key outcome of the third edition will be to continue the work begun at https://pdai.info/ to create a repository of perspectivist datasets with non-aggregated labels for use by researchers in perspectivist NLP modelling. Authors are, therefore, invited to share their LRs (data, tools, services, etc.) and provide essential information about resources (i.e., also technologies, standards, evaluation kits, etc.) that have been used for the work or are a result of their research. In addition, authors will be required to adhere to ethical research policies on AI and may include an ethics statement in their papers. The NLPerspectives workshop will be co-located with the 14th edition of LREC-COLING 2024<https://lrec-coling-2024.org> in Torino, Italy, in May 20-25, 2024. Submissions The papers should be submitted as a PDF document, conforming to the formatting guidelines provided in the call for papers of LREC-COLING conference: authors-kit<https://lrec-coling-2024.org/authors-kit/> We accept three types of submissions: * Regular research papers; * Non-archival submissions: like research papers, but will not be included in the proceedings; * Research communications: 4-page abstracts summarising relevant research published elsewhere. Research papers (archival or non-archival) may consist of up to 8 pages of content. Research communications may consist of up to 4 pages of content. More details will be up soon. Please make submissions at https://softconf.com/lrec-coling2024/nlperspectives2024/ Topics We invite original research papers from a wide range of topics, including but not limited to: * Non-aggregated data collection and annotation frameworks * Descriptions of corpora collected under the perspectivist paradigm * Multi-perspective Modelling and Machine Learning * Evaluation of multi-perspective models/ models of disagreement * Multi-perspective disagreement as applied to NLP evaluation * Fairness and inclusive modelling * Perspectivist approaches for social good * Applications of multi-perspective modelling * Computing with (dis)agreement * Perspectivist Natural Language Generation * Foundational aspects of perspectivism * Opinion pieces and reviews on perspectivist approaches to NLP Submissions are open to all, and are to be submitted anonymously (and must conform to the instructions for double-blind review). All papers will be refereed through a double-blind peer review process by at least three reviewers, with final acceptance decisions made by the workshop organisers. Scientific papers will be evaluated based on relevance, significance of contribution, impact, technical quality, scholarship, and quality of presentation. Attendance At least one author of each accepted paper is required to participate in the conference and present the work.. Important Dates * Friday February 23, 2024: Paper submission * Friday March 29, 2024: Notification of acceptance * Friday April 12, 2024: Camera-ready papers due * Tuesday May 21, 2024: Workshop Workshop organisers: Gavin Abercrombie, Heriot-Watt University Valerio Basile, University of Turin Davide Bernardi, Amazon Alexa Shiran Dudy, Northeastern University Simona Frenda, University of Turin Lucy Havens, University of Edinburgh Sara Tonelli, Fondazione Bruno Kessler Contact us at g.abercrombie(a)hw.ac.uk if you have any questions. Website: https://nlperspectives.di.unito.it/ ________________________________ Founded in 1821, Heriot-Watt is a leader in ideas and solutions. With campuses and students across the entire globe we span the world, delivering innovation and educational excellence in business, engineering, design and the physical, social and life sciences. This email is generated from the Heriot-Watt University Group, which includes: 1. Heriot-Watt University, a Scottish charity registered under number SC000278 2. Heriot- Watt Services Limited (Oriam), Scotland's national performance centre for sport. Heriot-Watt Services Limited is a private limited company registered is Scotland with registered number SC271030 and registered office at Research & Enterprise Services Heriot-Watt University, Riccarton, Edinburgh, EH14 4AS. The contents (including any attachments) are confidential. If you are not the intended recipient of this e-mail, any disclosure, copying, distribution or use of its contents is strictly prohibited, and you should please notify the sender immediately and then delete it (including any attachments) from your system.

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CFP LKE 2024
by Fernando Perez-Tellez 09 Jan '24

09 Jan '24

[We apologize for the cross-postings] CFP LKE 2024 June 4th - 6th, 2024, Dublin, Ireland https://lkesymposium.tudublin.ie/ The 9th International Symposium on Language & Knowledge Engineering will be held in Dublin, Ireland. LKE 2024 is organized by the School of Enterprise Computing and Digital Transformation of the Technological University Dublin, Grangegorman Campus. LKE 2024 will be a forum for exchanging scientific results and experiences, as well as sharing new knowledge, and increasing the co-operation between research groups in natural language processing and related areas. [[[ Seven different journals for publication are anticipated ]]] Topics: Submissions reporting original research work are invited under the following tracks: Track 1: Language and Knowledge Engineering Natural Language Processing - AI for NLP - Intelligent Techniques for Language Processing - Natural Language Inference - Knowledge Representation and Inferences - Machine Learning for Text Analytics - Deep Learning methods for Text Processing - Fuzzy Inference and Language Processing - Computational Linguistics for Language and Knowledge Engineering - Question-Answering Systems - Emotion and Sentiment analysis - Social Media Text Analytics - Intelligent Systems for Knowledge - Human Computer Interaction - Related issues and applications Note: The acepted papers in this track will appear in a Special Issue of Springer Nature Computer Science (Indexed in Scopus, Cite Score: 0.6.). Track 2: Scholarly Information Processing Information seeking & searching with scientific information - Mining the scientific literature - Academic search/recommender systems - Dataset development for bibliographic research - Scholarly Databases and their use - Science of science - Citation and co-citation analysis - Research collaboration mobility and internationalization - Knowledge dissemination and interdisciplinarity - Bibliometric indicators - Webometrics and altmetrics - Science mapping and visualization - Communication channels: periodicals, proceedings, books, and electronic publications - Knowledge discovery - AI and data mining - Bibliometrics-aided information retrieval - Open science – open access and open data - AI assisted peer review Note: The accepted papers in this track will appear in a Special Issue of Journal of Scientometric Research (Indexed in Scopus, Cite Score: 1.7, Indexed in ESCI, Impact Factor: 0.8). Track 3: Computational approaches to Language & Knowledge Engineering Combinatorial Optimization Problems - Computer Science Security - Computational Complexity - Computational aspects in Science of life - Computational Intelligence - Meta-heuristic and heuristics algorithms - Operations Research - Semantic Web - Software engineering - Web Technologies - Smart Cities and related topics - Robotics - Language and knowledge engineering Note: These papers will go to Special Issue of International Journal of Combinatorial Optimization Problems and Informatics (IJCOPI) (Indexed in ESCI, Impact Factor: 0.3, CONACYT-Mexico). Track 4: Artificial Intelligence and Ethics Human-Centred AI approaches to its application - Legal, regulatory-compliant, and ethical adoption of AI (Compliance and Legality) - AI risks - AI development lifecycle - Human values and fundamental rights on development, deployment, use and monitoring of AI systems - Natural and social environment in which AI tools operate - Socially Responsible AI - Trustworthy AI Note: These papers will go to Special Issue of Springer Nature Transformative Journal in AI and Ethics. Note: It is mandatory for authors to register and present their papers in the conference. Paper Submission and Review Process All the papers will be blind submitted (author’s names are not allowed) in English. All submissions will be peer reviewed by the Scientific Committee, for originality, technical content and relevance. The final acceptance will be based upon double blind peer review of the full-length paper, and based on this the final decision will be to be considered either as ORAL or POSTER presentation. All papers accepted in the main conference (oral presentation) will be published in one of these journals: - “Springer Nature Computer Science (SNCS)“, SCOPUS ISSN: 2662-995X. - “Journal of Scientometric Research“, SCOPUS ISSN : [Print -2321-6654, Online - 2320-0057]. - “International Journal of Combinatorial Optimization Problems and Informatics (IJCOPI)“, Web of Science Core Collection: Emerging Sources Citation Index (ESCI) SCOPUS CONACYT ISSN: 2007-1558. - “Springer Nature Transformative Journal in AI and Ethics“, Electronic ISSN: 2730-5961. Submissions are invited for papers presenting high quality, previously unpublished research. Selection criteria include originality of ideas, correctness, clarity and significance of results and quality of presentation. Papers must be formatted according to the author guidelines for SN Computer Science. Please prepare your paper using either the LaTeX (recommended) or the Ms Word Text Formating guide. Please limit the size of your paper to the suggested number of pages and the provided journal format. Papers that do not follow these format requirements may be rejected without review or may be not included in the journal even if they were accepted for publication. Other Journal Special Issues from the Conference Organizers: The organizers of the conference are also organizing related Special Issues of the following journals. Authors of some accepted good quality papers in LKE 2024 will be invited to submit extended/revised versions of their submissions to these venues: - Special Issue of ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) (Clarivate: Science Citation Index Expanded (SCIE), Impact Factor: 2.0), Print ISSN:2375-4699, Electronic ISSN:2375-4702. - Special Issue of Computer Speech and Language (CS&L) (Clarivate: SCI, Impact Factor: 4.3), Print ISSN: 0885-2308, Online ISSN: 1095-8363. - Special Issue of Journal of Natural Language Engineering (Cambridge University Press) (Clarivate: SCI, Impact Factor: 1.841), ISSN: 1351-3249 (Print), 1469-8110 (Online). Language: Manuscripts must be written in English. Authors whose native language is not English are recommended to seek the advice of a native English speaker, if possible, before submitting their manuscripts. The papers should be submitted electronically at the Microsoft CMT system: CMT - LKE2024: https://cmt3.research.microsoft.com/LKE2024 Submission implies the willingness of at least one of the authors to register and to present the communication at the conference, if it is accepted. Size: We are accepting papers of sizes 14 - 16 pages using the suggested format. Registration fee for authors includes publication of a paper of up to 16 pages. The additional fee is charged for the pages exceeding the page limit in either the version submitted for review or in the camera-ready version, whichever is greater. In particular, you must not shorten the camera-ready version in comparison with the version submitted for review unless the reviewers required this (contact us if you feel you should do shorten it; in any case this would not reduce the fee). Double blind review policy: The review procedure is double blind. Thus the papers submitted for review must not contain the authors’ names, affiliations, or any information that may disclose the authors’ identity (this information is to be restored in the camera-ready version upon acceptance). In particular, in the version submitted for review please avoid explicit auto-references. https://lkesymposium.tudublin.ie/

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36th International Conference on Advanced Information Systems Engineering: Second Call for Workshop Papers
by Announce 09 Jan '24

09 Jan '24

*** Second Call for Workshop Papers *** 36th International Conference on Advanced Information Systems Engineering (CAiSE'24) June 3-7, 2024, 5* St. Raphael Resort and Marina, Limassol, Cyprus https://cyprusconferences.org/caise2024/ (*** Submission Deadline: 26th February, 2024 AoE ***) CAiSE is a well-established, highly visible conference series on Advanced Information Systems (IS) Engineering. It covers all relevant topics in the area, including methodologies and approaches for IS engineering, innovative platforms, architectures and technologies, and engineering of specific kinds of IS. CAiSE conferences also have the tradition of hosting workshops in related fields. Workshops are intended to focus on particular topics and provide ample room for discussions of new ideas and developments. CAiSE'24, the 36th edition of the CAiSE series, will host the following workshops. For more information for each workshop please visit the workshops' web sites. CAiSE'24 Workshops • 3rd International Workshop on Agile Methods for Information Systems Engineering (Agil-ISE) https://agilise.github.io/2024/index.html • International Workshop on Blockchain for Information Systems (BC4IS24) and Blockchain for Trusted Data Sharing (B4TDS) https://pros.unicam.it/bc4isb4tds/ • 2nd International Workshop on Hybrid Artificial Intelligence and Enterprise Modelling for Intelligent Information Systems (HybridAIMS) https://hybridaims.com/ • 2nd Workshop on Knowledge Graphs for Semantics-driven Systems Engineering https://www.omilab.org/activities/events/caise2024_kg4sdse/ • 16th International Workshop on Enterprise & Organizational Modeling and Simulation (EOMAS 2024) https://eomas2024.fel.cvut.cz/ • Digital Transformation with Business Process Mining (DigPro2024) https://digpro.iiita.ac.in/ IMPORTANT DATES • Paper Submission Deadline: 26th February, 2024 (AoE) • Notification of Acceptance: 27th March, 2024 • Camera-ready Deadline: 5th April, 2024 • Author Registration Deadline: 5th April, 2024 Workshop Chairs • João Paulo A. Almeida, Federal University of Espírito Santo, Brazil • Claudio di Ciccio, Sapienza University of Rome, Italy • Christos Kalloniatis, University of the Aegean, Greece

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18-month post-doctoral (or research engineer) position in argument mining at I3S, Sophia Antipolis
by victor.david＠inria.fr 09 Jan '24

09 Jan '24

(Apologies for potential cross-posting) Dear all, An 18-month post-doctoral (or research engineer) position in argument mining (mainly) is available in the WIMMICS team at the I3S laboratory in Sophia Antipolis, France. A detailed description of the position and the AGGREY project is provided at the end of the e-mail. Required Qualifications ● A PhD: preferably in computer science, but not necessarily. (If post-doctorate, otherwise a Master's degree for a research engineer) ● Research interest in one or more of the following: Argument Mining, Natural Language Processing (NLP), Argumentation Theory, Computational Argumentation, E-democracy, Graph Theory, Game Theory, Similarity Measure, Explainable AI. ● Interest in interdisciplinary research. ● Excellent critical thinking, written and spoken English. Application Materials – send by email to Victor DAVID: victor.david(a)inria.fr ● Current CV ● Short statement of interest Application deadline: February 05, 2024. Questions about the position can also be sent to Victor DAVID: victor.david(a)inria.fr ========================================================================================================================================================== Description of the AGGREY project (An argumentation-based platform for e-democracy) This project brings together 4 French laboratories, including: - CRIL with VESIC Srdjan, KONIECZNY Sébastien, BENFERHAT Salem, VARZINCZAK Ivan, AL ANAISSY Caren, - LIP6 with MAUDET Nicolas, BEYNIER Aurélie, LESOT Marie-Jeanne, - LIPADE with DELOBELLE Jérôme, BONZON Elise, MAILLY Jean-Guy and - I3S with CABRIO Elena, VILLATA Serena and DAVID Victor. Summary of the project in general: E-democracy is a form of government that allows everybody to participate in the development of laws. It has numerous benefits since it strengthens the integration of citizens in the political debate. Several on-line platforms exist; most of them propose to represent a debate in the form of a graph, which allows humans to better grasp the arguments and their relations. However, once the arguments are entered in the system, little or no automatic treatment is done by such platforms. Given the development of online consultations, it is clear that in the near future we can expect thousands of arguments on some hot topics, which will make the manual analysis difficult and time-consuming. The goal of this project is to use artificial intelligence, computational argumentation theory and natural language processing in order to detect the most important arguments, estimate the acceptability degrees of arguments and predict the decision that will be taken. Given the size of the project, the tasks were defined and distributed between 5 work packages. The one corresponding to the postdoc (or research engineer) we are looking for is number 3, and depending on progress and priorities, it will also be possible to participate in number 5. Work package 3: Manipulation detection Leader: Elena Cabrio (I3S) Aim: We will rely on both heuristics and on state-of-the-art argument mining methods in order to detect an anomaly, a fallacious or a duplicate argument [Vorakitphan et al., 2021] (i.e., speech acts that violate the rules of a rational argumentative discussion for assumed persuasive gains), and manipulations (e.g., an organised group of users massively voting for the exact same arguments in a short time period, or submitting variants of the same argument). Background: The use of NLP, and more precisely of argument mining methods [Cabrio and Villata, 2018], will be relevant in supporting the smooth functioning of the debate, automatically detecting its structure (supporting and attacking argumentative components) and analysing its content (premises or claims)[Haddadan et al., 2019b]. Moreover, we will rely on previous studies of the similarity between arguments [Amgoud et al., 2018]. This includes, among other things, assistance in detecting manipulation by identifying duplicate arguments with argument similarity calculation [Reimers et al., 2019], or checking the relationships (attack or support) between arguments provided by users in the argument graph. Challenges/Subtasks: Subtask 3.1. Development of argument mining methods for finding missing elements and duplicates We plan to use argument mining methods to automatically build the argumentative graph and detect the missing elements and duplicates. Identifying argument components and relations in the debates is a necessary step to improve the model’s result in detecting and classifying fallacious and manipulative content in argumentation [Vorakitphan et al., 2021]. The use of the notion of similarity between arguments [Amgoud et al., 2018] will be further investigated in this context. Subtask 3.2. Development of methods for detecting manipulations We will develop and test different heuristics for dealing with manipulations. Those heuristics will be based on natural language processing, argument mining, graph theory, game theory, etc. Some parameters that we might take into account include also the ratio of added arguments and votes; the number of users that vote on similar arguments during the same time period; the votes on arguments attacking / supporting the same argument. Subtask 3.3. Development of graph-based methods for finding missing elements and duplicates We will develop graph-based properties for dealing with missing elements and duplicates. Consider, for instance, two arguments x and y that have the same attackers except that y is also attacked by z; suppose also that x and y attack exactly the same arguments. We might want to check whether z also attacks x. This might not be the case, so the system will not add those attacks automatically, but ask the users that put forward the arguments attacking x and y to consider this question. Bibliography: [Vorakitphan et al., 2021]: Vorakit Vorakitphan, Elena Cabrio, and Serena Villata. "Don’t discuss": Investigating semantic and argu- mentative features for supervised propagandist message detection and classification. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), Held Online, 1-3September, 2021, pages 1498–1507, 2021. URL https://aclanthology.org/2021.ranlp-1.168. [Cabrio and Villata, 2018]: Elena Cabrio and Serena Villata. Five years of argument mining: a data-driven analysis. In IJCAI, pages 5427–5433, 2018. URL https://www.ijcai.org/proceedings/2018/766. [Haddadan et al., 2019b]: Shohreh Haddadan, Elena Cabrio, and Serena Villata. Disputool - A tool for the argumentative analysis of political debates. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, pages 6524–6526, 2019b. doi: 10.24963/ijcai.2019/944. URL https://doi.org/10.24963/ijcai.2019/944. [Amgoud et al., 2018]: Leila Amgoud, Elise Bonzon, Jérôme Delobelle, Dragan Doder, Sébastien Konieczny, and Nicolas Maudet. Gradual semantics accounting for similarity between arguments. In International Conference on Principles of Knowledge Representation and Reasoning (KR 2018), pages 88–97. AAAI Press, 2018. URL https: //aaai.org/ocs/index.php/KR/KR18/paper/view/18077. [Reimers et al., 2019]: Nils Reimers, Benjamin Schiller, Tilman Beck, Johannes Daxenberger, Christian Stab, and Iryna Gurevych. Classification and clustering of arguments with contextualized word embeddings. In ACL, pages 567–578, 2019. URL https://aclanthology.org/P19-1054/. ========================================================================================================================================================== Work package 5: Implementation and evaluation of the platform Leaders: Jean-Guy Mailly (LIPADE) and Srdjan Vesic (CRIL) Aim: The goal of this WP is to implement the platform, evaluate it through experiments with end users, and use the obtained data to improve the design of the framework. Our experiments will also help us to better understand how humans use online platforms, which is essential for the future success of online debates. After implementing the platform, we will measure to which extent our platform leads to more informed decisions and attitudes. We plan to do this by measuring the extent of disagreement between the participants before and after the use of our system. We expect that the instructions to explicitly state one’s arguments and to link them with other justified counter-arguments make people more open to opposite views and more prone to changing their opinion. Background: The field of computational argumentation progressively went from using toy examples and theoretical only evaluation of the proposed approaches to constructing benchmarks [Cabrio and Villata, 2014] and evaluating the proposed approaches by comparing their output to that of human reasoners [Rosenfeld and Kraus, 2016, Polberg and Hunter, 2018, Cerutti et al., 2014, 2021]. Our recent results [Vesic et al., 2022] as well as our current work (unpublished experiments) found that when people see the graph representation of the corresponding debate they comply significantly more often to rationality principles. Furthermore, our experiments show that people are able to draw the correct graph (i.e. the one that corresponds to the given discussion) in the absolute majority of cases (even after no prior training except reading a three minute tutorial). The fact that those participants respect rationality principles more frequently is crucial, since it means that they are e.g., less prone to accept weak or fallacious arguments. Challenges/Subtasks: Subtask 5.1. Implementation of the platform This task aims at implementing the platform. Implementation of the platform will be done by using the agile method. This means that it will be implemented progressively and tested in order to allow for adaptive planning, evolutionary development and constant improvement. We could use an existing platform and add our functionalities. However, we find that building a dedicated platform more adequate for several reasons: many of the platforms are proprietary and would not allow us to use and publish their code, most of the functionalities we need do not exist in any platform, so using an existing platform would not help us gain a lot of time. Subtask 5.2 Measuring the quality of the platform We will conduct experiments with users in order to test if the platform can be used to reduce opinion polarisation and to enhance more rational and informed estimations of arguments’ qualities / strengths. To this end, we will examine if relevant parameters (such as the degree to which individuals agree with a given statement, the extent to which individuals diverge in their opinions, and in understanding the issue they debate about, etc.) are significantly different before and after the use of our debate platform. Our hypothesis is that seeing or producing the graph, making the arguments explicit, and engaging in a structured discussion will yield a better understanding of the questions and a better chance to reach an agreement with other parties. Ethical permission will be asked before conducting the experiments. Subtask 5.3. Improving the platform We will take into account the results of the experiments, user feed-back, bugs reports etc. in order to develop the final version of the platform. Bibliography: [Cabrio and Villata, 2014]: Elena Cabrio and Serena Villata. Node: A benchmark of natural language arguments. In Simon Parsons, Nir Oren, Chris Reed, and Federico Cerutti, editors, Computational Models of Argument - Proceedings of COMMA 2014, Atholl Palace Hotel, Scottish Highlands, UK, September 9-12, 2014, volume 266 of Frontiers in Artificial Intelligence and Applications, pages 449–450. IOS Press, 2014. doi: 10.3233/978-1-61499-436-7-449. URL https://doi.org/10.3233/978-1-61499-436-7-449. [Rosenfeld and Kraus, 2016]: Ariel Rosenfeld and Sarit Kraus. Providing arguments in discussions on the basis of the prediction of human argumentative behavior. ACM Trans. Interact. Intell. Syst., 6(4):30:1–30:33, 2016. doi: 10.1145/2983925. URL https://doi.org/10.1145/2983925. [Polberg and Hunter, 2018]: Sylwia Polberg and Anthony Hunter. Empirical evaluation of abstract argumentation: Supporting the need for bipolar and probabilistic approaches. Int. J. Approx. Reason., 93:487–543, 2018. doi: 10.1016/j.ijar.2017. 11.009. URL https://doi.org/10.1016/j.ijar.2017.11.009. [Cerutti et al., 2014]: Federico Cerutti, Nava Tintarev, and Nir Oren. Formal arguments, preferences, and natural language interfaces to humans: an empirical evaluation. In Torsten Schaub, Gerhard Friedrich, and Barry O’Sullivan, edi- tors, ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, volume 263, pages 207–212. IOS Press, 2014. doi: 10.3233/978-1-61499-419-0-207. URL https://doi.org/10.3233/978-1-61499-419-0-207. [Cerutti et al., 2021]: Federico Cerutti, Marcos Cramer, Mathieu Guillaume, Emmanuel Hadoux, Anthony Hunter, and Sylwia Polberg. Empirical cognitive studies about formal argumentation. In Guillermo R. Simari Dov Gabbay, Massimiliano Giacomin and Matthias Thimm, editors, Handbook of Formal Argumentation, volume 2. College Publications, 2021. [Vesic et al., 2022]: Srdjan Vesic, Bruno Yun, and Predrag Teovanovic. Graphical representation enhances human compliance with principles for graded argumentation semantics. In AAMAS ’22: 21st International Conference on Autonomous Agents and Multiagent Systems, Virtual Event, 2022. URL https://hal-univ-artois. archives-ouvertes.fr/hal-03615534.

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[2nd call] PhD position on Explainable NLU at the University of Copenhagen
by Isabelle Augenstein 09 Jan '24

09 Jan '24

The Natural Language Processing Section at the Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD position in Explainable Natural Language Understanding with a start date of 1 September 2024. The application deadline is 1 February 2024. Applications for the position can be submitted via UCPH's job portal<https://candidate.hr-manager.net/ApplicationInit.aspx/?cid=1307&departmentI…>. The Natural Language Processing Section<https://di.ku.dk/english/research/nlp/> provides a strong, international and diverse environment for research within core as well as emerging topics in natural language processing, natural language understanding, computational linguistics and multi-modal language processing. It is housed within the main Science Campus, which is centrally located in Copenhagen. The successful candidate will join Isabelle Augenstein’s Natural Language Understanding research group<http://www.copenlu.com/>. The Natural Language Processing research environment at the University of Copenhagen is internationally leading, as e.g. evidenced by it being ranked 2nd in Europe according to CSRankings. The position is offered in the context of an ERC Starting Grant held by Isabelle Augenstein on ‘Explainable and Robust Automatic Fact Checking (ExplainYourself)’. ERC Starting Grant is a highly competitive funding program by the European Research Council to support the most talented early-career scientists in Europe with funding for a period of 5 years for blue-skies research to build up or expand their research groups. The project team will consist of the principle investigator, three PhD students and two postdocs, collaborators from CopeNLU as well as external collaborators. The role of the PhD student to be recruited in this call will be to research methods for generating faithful free-text explanations of NLU models in collaboration with the larger project team. More information about the project can also be found here<http://www.copenlu.com/talk/2022_11_erc/>. Informal enquiries about the positions can be made to Professor Isabelle Augenstein, Department of Computer Science, University of Copenhagen, e-mail: augenstein(a)di.ku.dk<mailto:augenstein@di.ku.dk?subject=PhD%20position%20on%20Explainable%20Natural%20Language%20Understanding>. Isabelle Augenstein, Dr. Scient., Ph.D. Professor and Head of the NLP Section, Department of Computer Science (DIKU) Co-Lead, Pioneer Centre for Artificial Intelligence University of Copenhagen Østervold Observatory Øster Voldgade 3 1350 Copenhagen augenstein(a)di.ku.dk<mailto:augenstein@di.ku.dk> http://isabelleaugenstein.github.io/

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[2nd call] PhD position on Explainable NLU at the University of Copenhagen
by Isabelle Augenstein 09 Jan '24

09 Jan '24

The Natural Language Processing Section at the Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD position in Explainable Natural Language Understanding with a start date of 1 September 2024. The application deadline is 1 February 2024. Applications for the position can be submitted via UCPH's job portal<https://candidate.hr-manager.net/ApplicationInit.aspx/?cid=1307&departmentI…>. The Natural Language Processing Section<https://di.ku.dk/english/research/nlp/> provides a strong, international and diverse environment for research within core as well as emerging topics in natural language processing, natural language understanding, computational linguistics and multi-modal language processing. It is housed within the main Science Campus, which is centrally located in Copenhagen. The successful candidate will join Isabelle Augenstein’s Natural Language Understanding research group<http://www.copenlu.com/>. The Natural Language Processing research environment at the University of Copenhagen is internationally leading, as e.g. evidenced by it being ranked 2nd in Europe according to CSRankings. The position is offered in the context of an ERC Starting Grant held by Isabelle Augenstein on ‘Explainable and Robust Automatic Fact Checking (ExplainYourself)’. ERC Starting Grant is a highly competitive funding program by the European Research Council to support the most talented early-career scientists in Europe with funding for a period of 5 years for blue-skies research to build up or expand their research groups. The project team will consist of the principle investigator, three PhD students and two postdocs, collaborators from CopeNLU as well as external collaborators. The role of the PhD student to be recruited in this call will be to research methods for generating faithful free-text explanations of NLU models in collaboration with the larger project team. More information about the project can also be found here<http://www.copenlu.com/talk/2023_11_erc/>. Informal enquiries about the positions can be made to Professor Isabelle Augenstein, Department of Computer Science, University of Copenhagen, e-mail: augenstein(a)di.ku.dk<mailto:augenstein@di.ku.dk?subject=PhD%20position%20on%20Explainable%20Natural%20Language%20Understanding>. Isabelle Augenstein, Dr. Scient., Ph.D. Professor and Head of the NLP Section, Department of Computer Science (DIKU) Co-Lead, Pioneer Centre for Artificial Intelligence University of Copenhagen Østervold Observatory Øster Voldgade 3 1350 Copenhagen augenstein(a)di.ku.dk<mailto:augenstein@di.ku.dk> http://isabelleaugenstein.github.io/

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Postdoc position in Cambridge (deadline 25/1)
by A. Vlachos 09 Jan '24

09 Jan '24

Dear all, We are looking for a Research Assistant/Associate to work on the project FEVER-IT: Fact Extraction and VERification with Images and Text funded by the Alan Turing Institute and DSO labs, Singapore. The successful candidate will be based in the Natural Language and Information Processing group (http://www.cl.cam.ac.uk/research/nl/) at the Department of Computer Science and Technology. The project will focus on constructing a dataset and developing approaches enabling the verification of claims which require both text and images as evidence. Particular focus will be paid to accompanying the verdicts with suitable justifications. Candidates will have completed a Ph.D. (or be close to completing it) in a relevant field such as NLP, Information Retrieval, Artificial Intelligence or Machine Learning and be able to demonstrate a strong track record of independent research and high-quality publications. Essential skills include excellent programming (Python), NLP techniques (multimodal NLP in particular), Machine Learning, and proven communication skills. Candidates must provide the names and contact details of two referees who are familiar with their work in the relevant field whom we can contact for a reference before the interviews, which are expected to take place in January 2024. We are looking to start the project in February 2024, or as soon as possible after that. Enquiries concerning this position should be directed to Prof. Andreas Vlachos (av308(a)cam.ac.uk), and applicants are encouraged to contact him regarding the position. Apply using this link: https://www.jobs.cam.ac.uk/job/44672/ Thanks, Andreas

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Call for Participation: Learner Corpus Symposium (Feb 3, Kobe, Japan)
by Shin ISHIKAWA 09 Jan '24

09 Jan '24

Dear Colleagues We are happy to announce that Learner Corpus Studies in Asia and the World (LCSAW) 6th will be held in Kobe, Japan, on February 3, 2024. We have 24 presentations. Participation at the event is free of charge, but prior registration is needed. Program https://language.sakura.ne.jp/icnale/lcsaw/lcsaw6_program.pdf Venue Centennial Hall of Kobe University https://x.gd/N1ji1 Transportation https://language.sakura.ne.jp/icnale/lcsaw/2019/lcsaw_travel_guide/pdf Registration https://forms.office.com/r/nU132uW5tc NB: FCFS policy will be applied. Shin LCSAW Organizing Committee ICNALE Development Team Dr. Shin ISHIKAWA (he/his) Kobe University iskwshin(a)gmail.com

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ArabicNLP 2024 - Second Call for Shared Task Proposals
by Salam Khalifa 09 Jan '24

09 Jan '24

*** Apologies for Cross-Posting *** The Second Arabic Natural Language Processing Conference (ArabicNLP 2024) Co-located with ACL 2024 in Bangkok, Thailand, August 16, 2024. (Hybrid Mode). We invite proposals for shared tasks related to Arabic NLP to be part of the ArabicNLP 2024 conference. <https://arabicnlp2024.sigarab.org/> The proposals should provide an overview of the proposed task, motivation, data/resource collection and creation, task description, pilot run details (if available), a tentative timeline that matches the submission dates below, and task organizers (name, email, affiliation). Proposals in PDF format can be up to 4 pages. Shared Task Proposal Submission URL: https://shorturl.at/eCJOS Selection Process The proposals will be reviewed by the organizing committee and selected based on multiple factors such as the novelty of the task, the expected interest from the community, how convincing the data collection plans are, the soundness of the evaluation method, and the expected impact of the task. Task Organization Upon acceptance, the task organizers are expected to verify that the task organization and data delivery to participants are happening in a timely manner, provide the participants with all needed resources related to the task, create a mailing list, and maintain communication and support to participants, create and manage CodaLab or similar competition website, manage submissions to CodaLab, write a task description paper, manage participants submissions of system description papers, and review and maintain the quality of submitted system description papers. Important Dates for Shared Task Proposals - January 23, 2024: Submission of shared tasks proposals due date - February 6, 2024: Notification of acceptance of shared tasks - Proposals should target the following dates when planning their calls - April 29, 2024: Shared task papers due date - June 4, 2024: Notification of acceptance - June 24, 2024: Camera-ready papers due - August 16, 2024: ArabicNLP conference All deadlines are 11:59 pm UTC -12h <https://www.timeanddate.com/time/zone/timezone/utc-12> (“Anywhere on Earth”). For any questions, please contact the Shared Task Chair: arabicnlp-shared-task-chair(a)sigarab.org The ArabicNLP 2024 Organizing Committee -- Salam Khalifa

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PhD vacancy in Formal Methods for Natural Language Processing at Leiden University, The Netherlands
by Wijnholds, G.J. (Gijs) 09 Jan '24

09 Jan '24

** Apologies for cross-posting ** Applications are invited for a fully funded PhD candidature in at Leiden Institute of Advanced Computer Science (LIACS), The Netherlands, on the use of Formal Methods to enhance the efficiency, transparency and the understanding of Transformer-based language models. While large language models (LLMs) have proven successful in many areas of Natural Language Processing, they suffer from high data and resource usage, and display limited generalization capacity in tasks that humans excel at. In this PhD project you will have the opportunity to investigate how formal methods can help in developing more efficient and more transparent models for Natural Language Understanding. Specifically, you will investigate the use of implicit or explicit structural bias in Transformer-based language models to reduce training data and model parameters; additionally, you will look at novel techniques for evaluating models for their generalization capabilities on Natural Language Understanding tasks such as Natural Language Inference, possibly in a multilingual and multimodal setting. The specific project content is to be decided between the applicants’ interest and the expertise of the supervisor, dr. Gijs Wijnholds. Topics include (but are not limited to): - Using logical methods to define task-relevant constraints on LLM finetuning; - Incorporating structured representations in regularized training of smaller language models; - Assessing the generalization capacity of Transformer-based models in the context of formal language theory, model probing, Natural Language Inference; - Evaluation of Natural Language Understanding models in the presence of ambiguity and/or annotator disagreement; - Understanding multilingual Natural Language Inference in Vision-Language Models; For the official vacancy text, please see https://www.universiteitleiden.nl/en/vacancies/2023/qw4/23-81914335phd-cand… The application deadline is January 13, 2024. The ideal starting date is in March 2024, but can be negotiated depending on circumstances. For further information feel free to reach out to dr. Gijs Wijnholds (g.j.wijnholds(a)liacs.leidenuniv.nl<mailto:g.j.wijnholds@liacs.leidenuniv.nl>). dr. Gijs Wijnholds Assistant Professor in Natural Language Processing Text Mining and Retrieval Group<https://tmr.liacs.nl/> Leiden Institute of Advanced Computer Science https://gijswijnholds.github.io

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