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Postdoc positions at the ELLIS Institute Finland
by Tiedemann, Jörg 14 Jan '26

14 Jan '26

The ELLIS Institute Finland, a newly established world-class research hub in AI and machine learning, invites applications for postdoctoral researcher positions. Deadline February 9, 2026. Call with all details: https://www.ellisinstitute.fi/postdoc-recruit-2026 Research units and PIs in the call: Institute faculty and staff<https://www.ellisinstitute.fi/people> and the wider ELLIS community in Finland<https://www.ellisinstitute.fi/ellis-community-in-finland> We are seeking postdoctoral researchers to join the ELLIS Institute Finland and its wider research community. We welcome applications across all areas of machine learning, artificial intelligence, and related fields. Your research can be theoretical, applied, or span both. We offer independent postdoctoral researcher positions within the groups of experienced supervisors, with opportunities to work on ambitious, high-impact projects. Research environment You will join a cooperative and multidisciplinary environment for AI research: * Cutting-edge computational resources, including EuroHPC LUMI, one of the world’s fastest and greenest supercomputers, and an upcoming pan-European AI-optimized supercomputer (available by 2027) * Close collaborations with other top machine learning researchers in Europe and globally * Broad range of possibilities to work with companies and startups, fostering innovation and real-world applications of AI * An inclusive and international workplace, with English as the working language We are strongly committed to offering everyone an inclusive and non-discriminating working environment and warmly welcome applicants from diverse backgrounds to join our academic community. Job details Key information about the positions: * Positions are hosted at ELLIS Institute Finland and/or one of its partner universities. * All positions are fully funded and the salaries are based on the Finnish universities’ pay scale. * Positions are typically offered for up to three years. Starting dates are flexible. All positions are negotiated on an individual basis. Requirements Key requirements for the positions: * You hold (or expect to shortly receive) a PhD in computer science, statistics, electrical engineering, mathematics or a related field. * You have previous experience in machine learning, statistics, artificial intelligence or a related field, preferably demonstrated by publication record in a top-tier venue in machine learning-driven fields*. Other merits demonstrating suitability for a researcher position can also be considered. * The positions require the ability to work both independently and as part of a team in a highly collaborative and interdisciplinary environment. Excellent command of written and spoken English is required. How to apply Applications must be submitted electronically through the Apply here! link. The call will close on February 9, 2026 at 23:59 EET (UTC+2). Required documents (in English and in PDF format): * Cover letter (1–2 pages, see Q6 below) * CV * List of publications, highlighting up to five key papers with links * Transcript of doctoral and MSc studies * Degree certificate of your latest degree – if you don’t yet have a PhD degree, a plan of completion must be submitted In the application form, you are also asked to provide contact details of 2–3 senior academics who can provide references For inquiries, please email contact(a)ellisinstitute.fi. An FAQ is on https://www.ellisinstitute.fi/postdoc-recruit-2026 ***************************************************************** Jörg Tiedemann Language Technology https://blogs.helsinki.fi/language-technology/ University of Helsinki

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Call for Papers: ACL 2026 Industry Track
by ACL Announcements 13 Jan '26

13 Jan '26

Call for Papers: ACL 2026 Industry Track ACL 2026 Industry Track in San Diego, CA, United States Conference: July 2 - 7, 2026 Paper submission deadline: February 14, 2026 BACKGROUNDPERMALINK Language technologies are an integral and critical part of our daily lives. Many of these applications have their roots in academic and industrial research laboratories where researchers invented a plethora of algorithms, benchmarked them against shared datasets and perfected their performance to provide plausible solutions to real-world applications. While a controlled laboratory setting is vital for a deeper scientific understanding of the problems underlying language technologies and the impact of algorithmic design choices on their performance, transitioning the technology to real-world industrial strength applications raises a different, yet challenging, set of technical issues. We acknowledge the challenges when adapting language technologies for building novel and robust real-world applications as the journey from theoretical research to practical deployment can be difficult. Challenges can include technical aspects of system deployment and optimizing for efficiency, making informed design choices or methodological considerations of incorporating human feedback, evaluation and oversight. To provide a forum to address these multifaceted issues, we are seeking submissions that not only dive into research but also demonstrate the application of systems in real-world scenarios, irrespective of whether they involve proprietary data. TOPICSPERMALINK We invite submissions describing innovations and implementations in all areas of speech and natural language processing (NLP) technologies and systems that are relevant to real-word applications. The primary focus of this track is on papers that advance the understanding of, and demonstrate the effective handling of, practical issues related to the deployment of language processing or language generation technologies, including those of large language models, in non-trivial real-world systems, meaning: applications deployed for real-world use, i.e., outside controlled environments such as laboratories, classrooms or experimental crowd-sourced setups, also including applications that use NLP and/or speech technology, even if not state of the art in terms of research. There is no requirement that the system be made by a for-profit company, but the users of the system are most likely outside the NLP research community. This track provides an opportunity to highlight the key insights and new research challenges that arise from real world implementations. Relevant areas include: A. System design, efficiency, maintainability and scalability of real-world applications, with topics in alphabetical order including, but not limited to: * Benchmarks and methods for improving the latency and efficiency of systems * Continuous maintenance and improvement of deployed systems * Efficient methods for training and inference * Enabling infrastructure for large-scale deployment * Handling unexpected user behaviour * Human-in-the-Loop approaches to application development * Implementation at speed, scale and low-cost * Negative results related to real-world applications * System combination B. Novel applications and use cases, with topics in alphabetical order including, but not limited to: * Best practices and lessons learned * Case studies, from design to deployment * Description of an application or system * Design of application-relevant datasets * Development of methods under system constraints (model or data size) * Novel, previously unsolved NLP problems and novel NLP applications C. Methods for deployed systems, with topics in alphabetical order including, but not limited to: * Ethics, bias, fairness, harmlessness and trustworthiness in deployed systems * Interpretability * Interactive systems * Offline and online system evaluation methodologies * Online learning * Robustness In addition, opinion/vision papers related to real-world applications are also welcome. Submissions must clearly identify one of the following three areas they fall into: * _Deployed_: Must describe a system that solves a non-trivial real-world problem. The focus may include describing the problem related to actual use cases, its significance (against opportunity size, value proposition, and ideal end state), design/formulation of methods, tradeoff design decision for solutions, deployment challenges, and lessons learned. * _Emerging_: Must describe the development of a system that solves a non-trivial real-world problem (it need not be deployed or even close, but there needs to be evidence that this development is intended for real-world deployment). Papers that describe enabling infrastructure for large-scale deployment of NLP techniques also fall in this category. * _Discovery_: Must include results obtained from NLP applications in real-world scenarios that result in actionable insights. These discoveries should reveal promising directions in their application areas, leading to further system or societal enhancements. For example, an actionable discovery from an analysis of call center transcripts may reveal that certain language choices negatively impact customer experience, leading to better training of service representatives and improved customer experience. IMPORTANT DATESPERMALINK Paper submission deadline February 14, 2026 Author response deadline March 29, 2026 Notification of acceptance April 12, 2026 Camera-ready deadline April 19, 2026 Main conference July 2-7, 2026 All deadlines are 11.59 pm UTC -12h (anywhere on earth). Following the ACL and ARR Policies for Review and Citation, updated in early 2024, there is no anonymity period requirement, e.g., one may upload the paper to arXiv at any time. Please note that the ACL 2026 Industry Track does not use ARR! EVALUATION AND DECISION CRITERIAPERMALINK Submissions will be reviewed in a double-blind manner and assessed based on their novelty, technical quality, potential impact, and clarity. Submissions to the industry track should emphasize real-world implementations of NLP systems, the development of such systems, or provide insights based on real-world datasets with obvious industry impact. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and reproducible (though the data may be proprietary); in that regard, due to the type of work we expect to be submitted to the Industry Track, we ask authors to pay specific attention to their evaluation methodologies (human vs. automated). SUBMISSION REQUIREMENTSPERMALINK Authors are invited to submit original, full-length (6 pages) industry track papers that are not previously published, accepted to be published, or under consideration for publication in any other forum. Manuscripts should be submitted digitally, in PDF format and formatted using the ACL 2026 formatting requirements. Please do not modify these style files, nor should you use templates designed for other conferences. Submissions that do not conform to the required styles, including paper size, margin width, and font size restrictions, will be desk-rejected. Length and appendices: Industry Track papers cannot exceed 6 pages in length (excluding ethical considerations and references). After the bibliography, papers can have an optional appendix with, e.g., examples or sample inputs/outputs, pre-processing decisions, model parameters, feature templates, pseudocode, information about user studies, additional errors analysis or other details that are necessary for the replication of the work described in the paper. Note, however, that paper submissions must be fully self-contained, i.e., supplementary materials, as provided in the appendix, are completely optional, and reviewers are not even asked to review them. Note that it will not be possible to submit additional separate files as supplementary materials. Authors are asked not to abuse the option of an unlimited appendix and only to include material that supports the primary messages and content of the paper; to avoid any misunderstandings regarding the nature of the appendix, for the final papers, especially those with an appendix of excessive length, the ACL 2026 Industry Track chairs reserve the right to include a statement that it was not mandatory for reviewers to review the material presented in the appendix. Double-blind review: Industry Track submissions must neither include the authors' names nor their affiliations. Self-references that reveal the authors' identities must be avoided. For example, instead of "We previously showed (Smith, 1991) …" or even "We previously showed (Anonymous, 1991) …", please use "Smith (1991) previously showed …". Authors should also be careful not to reveal their affiliation indirectly, for example through screenshots or trade names. Submissions should avoid links to non-anonymized repositories: code should be submitted as a link to an anonymized repository (e.g., Anonymous GitHub or Anonym Share). Please avoid links to storage services like Dropbox (which may track the reviewers downloading the resources). Papers that do not conform to these requirements will be desk-rejected. Citation and comparison: Authors are expected to cite all refereed publications relevant to their submission but may be excused for not knowing about all unpublished work (especially work that has been recently posted and/or is not widely cited). In cases where a preprint has been superseded by a refereed publication, the refereed publication should be cited in addition to or instead of the preprint version. Papers (whether refereed or not) appearing less than 3 months before the submission deadline are considered contemporaneous to a submission, and authors are therefore not obliged to make detailed comparisons that require additional experimentation and/or in-depth analysis. For more information, see the ACL Policies for Review and Citation. Writing assistance: The ACL 2026 Industry Track adheres to the ACL policy on using writing assistants (including AI-based writing assistants and other AI tools) available here. Submission system: Papers have to be submitted through the ACL 2026 Industry Track online submission system. The submission link will be provided soon. Final version: Accepted papers will be given one additional page of content (up to 7 pages; ethical considerations, acknowledgements and references do not count against this limit) so that reviewers' comments can be taken into account. Previous presentations of the work (e.g., preprints on arXiv.org) should be indicated in a footnote that should be excluded from the review submission, but included in the final version of papers appearing in the ACL 2026 proceedings. The final version should remove anonymization in text, citation, and figures. For example, the final version may include the name of the authors' institutions, trademarks, and screenshots of identifiable products. Please notice that once the paper has been submitted, no changes to the list of authors are allowed. Presentation requirement for accepted papers: Industry Track papers will be presented orally or as posters, to be determined by the program committee. All accepted papers must be presented at the conference (either via online or onsite presence). At least one author of each accepted paper must register for ACL 2026 by the early registration deadline. The ACL 2026 Industry Track will run in parallel with the Research Track. Presentation Mode: Accepted papers will be presented orally or as posters as determined by the program committee. The decisions as to which papers will be presented orally and which as poster presentations will be based on the nature rather than the quality of the work. There will be no distinction in the proceedings between papers presented orally or as posters Authorship: The author list for submissions should include all (and only) individuals who made substantial contributions to the work presented. Each author listed on a submission to the ACL 2026 Industry Track will be notified of submissions and the final decision. No changes to the order or composition of authorship may be made to submissions to the ACL 2026 Industry Track after the paper submission deadline MULTIPLE SUBMISSION POLICYPERMALINK ACL 2026 will not consider any paper that is under review in a journal or another conference at the time of submission, and submitted papers must not be submitted elsewhere during the ACL 2026 review period. This policy covers all refereed and archival conferences and workshops (e.g., NeurIPS, ACL workshops), as well as ARR. In addition, we will not consider any paper that overlaps significantly in content or results with papers that have been (or will be) published elsewhere. Authors submitting more than one paper to ACL 2026 must ensure that their submissions do not overlap significantly (>25%) with each other in content or results. Submissions of identical or closely related work to multiple ACL 2026 tracks (e.g., to the research track and industry track) will be treated as duplicate submissions. Such submissions violate our multiple submission policy and will be rejected without review. The authors should also include the papers that their paper overlaps with or extends in the references section as follows: _Anonymous Authors_, "_Title of the paper_", _Under submission at ACL 2026 (TRACK NAME)_. ETHICS POLICYPERMALINK Authors are required to honor the ethical code set out in the ACL Code of Ethics. The consideration of the ethical impact of our research, use of data, and potential applications of our work has always been an important consideration, and as artificial intelligence is becoming more mainstream, these issues are increasingly pertinent. We ask that all authors read the code, and ensure that their work is conformant to this code. Where a paper may raise ethical issues, we ask that you include in the paper an explicit discussion of these issues, which will be taken into account in the review process. We reserve the right to reject papers on ethical grounds, where the authors are judged to have operated counter to the code of ethics, or have inadequately addressed legitimate ethical concerns with their work. Authors will be allowed extra space after the sixth page for an optional broader impact statement or other discussion of ethics. The ACL review form will include a section addressing these issues and papers flagged for ethical concerns by reviewers or ACs will be further reviewed by an ethics committee. Note that an ethical considerations section is not required, but papers working with sensitive data or on sensitive tasks that do not discuss these issues will not be accepted. Conversely, the mere inclusion of an ethical considerations section does not guarantee acceptance. In addition to acceptance or rejection, papers may receive a conditional acceptance recommendation. Camera-ready versions of papers designated as conditional accept will be re-reviewed by the ethics committee to determine whether the concerns have been adequately addressed. Please read the ethics FAQ for more guidance on some problems to look out for and key concerns to consider relative to the code of ethics. CONTACT INFORMATIONPERMALINK Industry Track Co-Chairs: * Yunyao Li (Adobe) * Georg Rehm (DFKI GmbH) * Mei Tu (Samsung) Email: acl-2026-industry-track(a)googlegroups.com General Chair: Philipp Koehn (Johns Hopkins University)

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2nd CfP: NLP4Ecology 2026 @ LREC 2026
by fr.grasso＠unito.it 13 Jan '26

13 Jan '26

We invite submissions to the 2nd Workshop on Ecology, Environment, and Natural Language Processing. We are particularly interested in contributions that push the boundaries of linguistics and NLP research in the context of ecological and environmental crisis and that foster interdisciplinary collaboration. The topics of interest include, but are not limited to: - Sentiment, Argument, and Stance Analysis of Environmental Topics: Evaluating public opinions, emotions, and stances on ecological issues across social media, news outlets, and other media, including environmental activism communication and AI–environment debates (e.g., Longo and Longo, 2025; Ibrohim et al., 2023; Barz et al., 2025; Grasso et al., 2024). - Automated Linguistic and Discourse/Frame Analysis, and Topic Modeling: Studying grammatical, lexical, and discourse patterns in ecological communication from an ecolinguistic perspective, including topic modeling and framing analyses of media, political discourse, corporate reports, and NGO communication (e.g., Widanti, 2022; Dehler-Holland et al., 2021; Bosco et al., 2025; Grasso et al., 2025b). - Detection of Anthropocentric and Speciesist Biases: Identifying and mitigating anthropocentric and speciesist biases in language data and NLP applications, including bias in large language models (e.g., Leach et al., 2021; Takeshita et al., 2022; Grasso et al., 2025a). - Text Classification, Entity Recognition, and Environmental Monitoring: Categorizing texts into environmental subdomains such as biodiversity, climate change, and conservation, and identifying or tracking mentions of species, habitats, pollutants, and ecological phenomena, including applications of LLMs to ecological and biodiversity corpora (e.g., Volkanovska, 2025; Schimanski et al., 2023; Abdelmageed et al., 2022; Grasso & Locci, 2024). - Fact-checking and Greenwashing Detection: Analyzing corporate sustainability reports and institutional communication to detect misleading claims, greenwashing practices, and inaccuracies in environmental discourse (e.g., Glazkova and Zakharova, 2025; Cojoianu et al., 2020; Moodaley & Telukdarie, 2023). - Ecofeminism, Environmental Justice, and Language: Exploring the intersections of gender, justice, power, and ecological narratives, and how NLP methods can support the analysis of environmental justice–oriented discourse. Further topics include: - Ecolinguistic applications of NLP. -Large Language Models (LLMs) application in Climate Change and Environmental domain. -Analysis of harmful environmental narratives and misinformation on social media. -Corpora creation and annotation for ecological discourse -Geo-tagging and Sentiment Mapping of Environmental Discussions -Fairness, ethics, and accountability in environmental NLP. -Environmental communication in low-resource languages. -Multimodal analysis for ecological and environmental challenges. -Lexical and semantic analysis of sustainability discourse. -Linked Data and Knowledge Graphs on ecological topics. -Language diversity and inclusion in environmental narratives. -Cognitive models and ecological storytelling. -NLP for understanding indigenous knowledge in environmental contexts. -Machine learning techniques for analyzing environmental communication. -NLP for environmental legislation and policy discourse. -NLP for environmental education and awareness campaigns. -Speech technologies to support ecological field research. -Educational chatbots and conversational agents for raising environmental awareness. We invite submissions in the following categories: - Regular Papers (from a minimum of 4 up to 8 pages) - Non-archival contributions (up to 4 pages). Regular papers must report original, previously unpublished work and follow the LREC 2026 Author Kit. Accepted regular papers will be included in the workshop proceedings. Non-archival contributions include research communications (i.e. work already published at other venues), work in progress, manifestos, and similar contributions. Non-archival contributions can be presented at the workshop but will not be included in the proceedings. Please visit https://nlp4ecology2026.di.unito.it/ for more infos. Contact e-mails: nlp4ecology.workshop(a)gmail.com ; fr.grasso(a)unito.it

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PhD position (4-year FPI contract) at the UNED NLP & IR group
by JORGE AMANDO CARRILLO DE ALBORNOZ CUADRADO 12 Jan '26

12 Jan '26

****We apologize for the multiple copies of this e-mail**** Dear all, We would like to share the following PhD opportunity, which may be of interest to prospective doctoral candidates or colleagues who could help disseminate the call. A PhD position (4-year FPI contract) is available at the UNED NLP & IR group, within the framework of the ANNOTATE research project, carried out in collaboration with the University of Barcelona and the Universitat Politècnica de València. The PhD research will focus on Human-Centric Artificial Intelligence, with particular emphasis on the analysis and detection of sexism in digital and multimedia environments, combining multimodal data and explainable, socially responsible AI approaches. The doctoral work will contribute to the development of a Sexism Observatory, an interactive platform for large-scale detection, analysis, and visualization of sexist content. The position is aimed at candidates with a background in Artificial Intelligence and Natural Language Processing, strong Python programming skills, and a good command of English. The application deadline is February 8th, 2026. Full details about the position and the application process are available in the linked document: http://nlp.uned.es/~jcalbornoz/jobs/Full_time_Phd_UNED_FPI.pdf Best regards, Jorge Carrillo-de-Albornoz P.S. Please feel free to share or redistribute this call with anyone who might be interested. AVISO LEGAL. Este mensaje puede contener información reservada y confidencial. Si usted no es el destinatario no está autorizado a copiar, reproducir o distribuir este mensaje ni su contenido. Si ha recibido este mensaje por error, le rogamos que lo notifique al remitente. Le informamos de que sus datos personales, que puedan constar en este mensaje, serán tratados en calidad de responsable de tratamiento por la UNIVERSIDAD NACIONAL DE EDUCACIÓN A DISTANCIA (UNED) c/ Bravo Murillo, 38, 28015-MADRID-, con la finalidad de mantener el contacto con usted. La base jurídica que legitima este tratamiento, será su consentimiento, el interés legítimo o la necesidad para gestionar una relación contractual o similar. En cualquier momento podrá ejercer sus derechos de acceso, rectificación, supresión, oposición, limitación al tratamiento o portabilidad de los datos, ante la UNED, Oficina de Protección de datos<https://www.uned.es/dpj>, o a través de la Sede electrónica<https://uned.sede.gob.es/> de la Universidad. Para más información visite nuestra Política de Privacidad<https://descargas.uned.es/publico/pdf/Politica_privacidad_UNED.pdf>.

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Call for Papers: LxGr2026
by Costas Gabrielatos 12 Jan '26

12 Jan '26

11th Symposium on Corpus Approaches to Lexicogrammar (LxGr2026) CALL FOR PAPERS Deadline for abstract submission: 1 March 2026 The symposium will take place online on Thursday 2 and Friday 3 July 2026 Invited Speakers Stefan Gries<https://www.stgries.info/> (University of California, Santa Barbara, USA) Martin Hilpert<http://members.unine.ch/martin.hilpert> (University of Neuchâtel, Switzerland) LxGr primarily welcomes papers reporting on corpus-based research on any aspect of the interaction of lexis and grammar -- particularly studies that interrogate the system lexicogrammatically to get lexicogrammatical answers. However, position papers discussing theoretical or methodological issues, as well as descriptions or demonstrations of tools or resources are also welcome, as long as they are relevant to both lexicogrammar and corpus linguistics. If you would like to present, send an abstract of 500 words (excluding references) to lxgr(a)edgehill.ac.uk<mailto:lxgr@edgehill.ac.uk>. * Abstracts for research papers should specify the research focus (research questions or hypotheses), the corpus, the methodology (techniques, metrics), the theoretical orientation, and the main findings. * Abstracts for position papers should specify the theoretical orientation and the potential contribution to both lexicogrammar and corpus linguistics. * Abstracts for tools or resources should provide a clear description of the main functions, and specify the potential contribution to both lexicogrammar and corpus linguistics. Full papers will be allocated 35 minutes (including 10 minutes for discussion). Work-in-progress reports will be allocated 20 minutes (including 5 minutes for discussion). There will be no parallel sessions. Participation is free. For details, visit the LxGr website: https://sites.edgehill.ac.uk/lxgr If you have any questions, please contact lxgr(a)edgehill.ac.uk<mailto:lxgr@edgehill.ac.uk>. ________________________________ Edge Hill University<http://ehu.ac.uk/home/emailfooter> Modern University of the Year, The Times and Sunday Times Good University Guide 2022<http://ehu.ac.uk/tef/emailfooter> University of the Year, Educate North 2021/21 ________________________________ This message is private and confidential. If you have received this message in error, please notify the sender and remove it from your system. Any views or opinions presented are solely those of the author and do not necessarily represent those of Edge Hill or associated companies. Edge Hill University may monitor email traffic data and also the content of email for the purposes of security and business communications during staff absence.<http://ehu.ac.uk/itspolicies/emailfooter>

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Lancaster Open research group - starts 21 January
by Brezina, Vaclav 12 Jan '26

12 Jan '26

Dear all, The Open Advanced Methods in Corpus Linguistics research group, offered by CASS - the ESRC Centre for Corpus Approaches to Social Science at Lancaster University, will resume this term. The group is open to anyone with an interest in corpus linguistics or quantitative approaches to language, and sessions will be held in a hybrid format (in person and online). This term, we will focus on one of the most fundamental concepts in corpus linguistics, frequency, a concept that underpins the field as a whole. When: Wednesdays, fortnightly, 12:00-12:50 pm (UK time) Starting: Wednesday 21 January Running topic: Measuring and reporting frequency in corpus linguistics Free registration: https://forms.office.com/e/YT5md2fjkac All are very welcome. Best wishes, Vaclav Readings: Brezina, V., & Gablasova, D. (2024). A frequency dictionary of British English: core vocabulary and exercises for learners. Routledge. Divjak, D. (2019). Frequency in language: Memory, attention and learning. Cambridge University Press. Gries, S.T. (2024). Frequency, Dispersion, Association, and Keyness: Revising and tupleizing corpus-linguistic measures. Amsterdam: John Benjamins. Platt, W. C. (2025). Review of Gries (2024): Frequency, Dispersion, Association, and Keyness: Revising and tupleizing corpus-linguistic measures. Tissari, H. (2023). Divjak, Dagmar: Frequency in language: memory, attention and learning. Cambridge: Cambridge University Press, 2019.[Book review]. Linguist list, 34.

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International Conference on Software and Systems Reuse, Product Lines, and Configuration (VARIABILITY 2026): First Call for Project Showcases
by Announce 12 Jan '26

12 Jan '26

*** First Call for Project Showcases *** International Conference on Software and Systems Reuse, Product Lines, and Configuration (VARIABILITY 2026) 29 September - 2 October 2026, 5* St. Raphael Resort and Marina Limassol, Cyprus https://conf.researchr.org/home/variability-2026 The VARIABILITY conference series brings together the communities previously served by ICSR, SPLC, and VaMoS, forming a unified venue for research on variability, configuration, customization, and related disciplines in software and systems engineering. As part of this mission, VARIABILITY 2026 invites submissions to its Project Showcase Track, a forum dedicated to presenting ongoing or recently completed research projects. The track offers a stage for research teams to share their vision, goals, early outcomes, intermediate results, final achievements, and lessons learned from funded projects of all scales, including collaborative research centers, EU projects, and nationally or regionally funded initiatives. The goal is to encourage interaction, foster collaboration opportunities, and help disseminate project insights to the broader community. Objectives and Scope We welcome submissions on research projects that address reuse, product lines, and variable/configurable software systems. A list of research topics that are relevant for this track is available from the call for the papers for the VARIABILITY 2026 Research Track, at: https://conf.researchr.org/track/variability-2026/variability-2026-papers#C… Submissions are expected to describe ongoing or recently completed research projects within this scope. This track is not intended for publishing mature research results. Instead, it focuses on project summaries and overviews, highlighting goals, structure, challenges, insights, and project level impact. Examples of suitable submissions include: • Ongoing projects focusing on goals, challenges, methodology, or early findings • Recently completed projects summarizing outcomes, evidence, and impact • Large scale, collaborative, or multi partner efforts, where visibility and networking are beneficial • Smaller or emerging projects that would benefit from early feedback and exposure PhD thesis projects are not in scope for this track. We warmly encourage PhD candidates to submit their work to the VARIABILITY 2026 Doctoral Symposium. Submission Format • Length: 7 to 10 pages, excluding references • Format: LNCS (Springer), single blind submissions Each submission will receive feedback from three reviewers. All submissions must adhere to the LNCS (Springer) format. Please refer to the official LNCS template at https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu… . Submissions must be in PDF format and submitted via EasyChair: https://easychair.org/conferences/?conf=variability2026 (Select “Projects Showcase Track”). Presentation and Publication Accepted papers will appear in the VARIABILITY 2026 Companion Proceedings published by Springer in the LNCS series. Accepted submissions will receive a presentation slot. At least one author of each accepted paper must: • Register for the full conference, and • Present the contribution at the event Evaluation Criteria Submissions will be evaluated on: • Relevance to the conference scope • Clarity of project goals, context, and contributions • Potential for impact, collaboration, reuse, or technology transfer • Value for discussion and interaction at the conference The focus is on clarity, relevance, and value to the community rather than scientific novelty. Important Dates (AoE) • Submission of Papers: 1 June 2026 • Notification of Acceptance: 21 June 2026 • Camera-Ready Submission: 15 July 2026 • Author Registration: 15 July 2026 Organisation General Chairs • George A. Papadopoulos, University of Cyprus, Cyprus • Gilles Perrouin, FNRS & University of Namur, Belgium Research Track Chairs • Thorsten Berger, Ruhr University Bochum, Germany • Ina Schaefer, KIT, Germany Industry Track Chairs • Shaukat Ali, Simula Research Lab and Oslo Metropolitan University, Norway • Martin Becker, Fraunhofer IESE, Germany Journal First Track Chairs • Mathieu Acher, University Rennes, Inria, CNRS, IRISA, France • Xhevahire Tërnava, LTCI, Télécom Paris, Institut Polytechnique de Paris, France Doctoral Symposium Track Chairs • Rick Rabiser, LIT CPS, Johannes Kepler University Linz, Austria • Iris Reinhartz-Berger, University of Haifa, Israel Demos and Tools Track Chairs • Sandra Greiner, University of Southern Denmark, Denmark • Leopoldo Teixeira, Federal University of Pernambuco Projects Showcase Chairs • Daniel Struber, Chalmers, University of Gothenburg, Radbound University, Sweden • Dalila Tamzalit, Nantes Université, France Hall of Fame Chairs • Martin Becker, Fraunhofer IESE, Germany • Goetz Botterweck, Lero - The Irish Software Research Centre and University of Limerick, Ireland • Natsuko Noda, Shibaura Institute of Technology, Japan Workshops Chairs • Lidia Fuentes, Universidad de Malaga, Spain • Malte Lochau, University of Siegen, Germany Tutorials Chairs • Loek Cleophas, Eindhoven University of Technology and Stellenbosch University, The Netherlands • Mahsa Varshosaz, IT University of Copenhagen, Denmark Proceedings Chair • Sophie Fortz, King's College London, UK Publicity Chairs • Wesley Assunção, North Carolina State University, USA • Kentaro Yoshimura, Hitachi Ltd, Japan Local Organiser and Finance Chair • George A. Papadopoulos, University of Cyprus, Cyprus

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[CFP] ClimateCheck 2026: Shared Task on Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims
by max.upravitelev＠tu-berlin.de 12 Jan '26

12 Jan '26

The rise of climate discourse on social media offers new channels for public engagement but also amplifies mis- and disinformation. As online platforms increasingly shape public understanding of science, tools that ground claims in trustworthy, peer-reviewed evidence are necessary. The new 2026 iteration of ClimateCheck builds on the results and insights from the 2025 iteration (run at SDP 2025/ACL 2025), extending it by adding training data, a new task on classifying disinformation narratives in climate discourse, and a focus on sustainable solutions. The ClimateCheck shared task is a part of the the 3rd International Workshop on Natural Scientific Language Processing (NSLP 2026), which will take place on May 12 2026 and is co-located with LREC 2026 in Palma de Mallorca (Spain). ***Available Tasks*** Task 1: Abstract retrieval and claim verification: given a claim and a corpus of publications, retrieve the top 5 most relevant abstracts and classify each claim-abstract pair as supports, refutes, or not enough information. Evaluation: Recall@K (K=2, 5) and B-Pref (for retrieval) + Weighted F1 (for verification) based on gold data; additional unannotated documents will be evaluated automatically. In addition, we will ask participants to use CodeCarbon to assess emissions and energy consumption at test inference. Task 2: Disinformation narrative classification: given a claim, predict which climate disinformation narrative exists according to a predefined taxonomy. Evaluation: Macro-, micro-, and weighted-F1 scores based on annotated documents. ***Important Dates*** - Release of datasets: December 15, 2025 (task 1); December 19, 2025 (task 2) -) Both datasets are now available for training! - Testing phase begins: January 15, 2026 (Codabench link TBA) - Deadline for system submissions: February 16, 2026 - Deadline for paper submissions: February 20, 2026 - Notification of acceptance: March 13, 2026 - Camera-ready papers due: March 30, 2026 - Workshop: May 12, 2026 We encourage and invite participation from junior researchers and students from diverse backgrounds. Participants are also highly encouraged to submit a paper describing their systems to the NSLP 2026 workshop. ***Call for Participation*** The call for participation with more information can be found here: https://nfdi4ds.github.io/nslp2026/

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2nd CfP: Universal Dependencies Workshop @ LREC 2026
by cagri coltekin 11 Jan '26

11 Jan '26

*** apologies for cross-posting *** CALL FOR PAPERS Ninth Workshop on Universal Dependencies (UDW 2026) 16 May 2026, Palma de Mallorca, Spain (co-located with LREC 2026) https://universaldependencies.org/udw26/ Overview Universal Dependencies (UD) is a framework for cross-linguistically consistent treebank annotation that has so far been applied to over 180 languages. The framework aims to capture similarities as well as idiosyncrasies among typologically different languages (e.g., morphologically rich languages, pro-drop languages, and languages featuring clitic doubling). The goal in developing UD was not only to support comparative evaluation and cross-lingual learning but also to facilitate multilingual natural language processing, enable comparative linguistic studies, and provide resources for language model understanding and evaluation. The Universal Dependencies Workshop series was started to create a forum for discussion of the theory and practice of UD, its use in research and development, and its future goals and challenges. Some of the previous workshops have been co-located with COLING, EMNLP, and SyntaxFest. We invite papers on all topics relevant to UD, including but not limited to: * Theoretical foundations and universal guidelines * Linguistic analysis of specific languages and/or constructions * Language typology and linguistic universals * Treebank annotation, conversion, and validation * Word segmentation, morphological tagging and syntactic parsing * Use of UD data for evaluating or understanding language models * Linguistic studies based on the UD data Priority will be given to papers that adopt a cross-lingual perspective. Invited Speakers * Marie-Catherine de Marneffe, UC Louvain * Stephen Mayhew, Duolingo Important Dates Paper submission deadline: February 16, 2026 Notification of acceptance: March 16, 2026 Camera-ready version due: March 30, 2026 Workshop date: May 16, 2026 Submission Formats We invite submissions in two formats: * Regular (long) papers up to 8 pages of content (excluding references and appendices). Regular papers should present substantial, original, and unpublished research, including empirical evaluation results where appropriate. * Short papers up to 4 pages of content (excluding references and appendices). Short papers may offer smaller, focused contributions, such as work in progress, negative results, surveys, or opinion pieces. We also welcome non-archival papers, defined as work that has already been published or accepted for publication at another computational linguistics venue. These papers may be presented at the workshop but will not appear in the LREC 2026 Workshop Proceedings. Accepted papers will be given one additional page to address reviewer comments. Paper Submission, Review Process and Selection Criteria Submissions will be handled via the START Conference Manager. * Submission link: https://softconf.com/lrec2026/UDW2026/ Papers should describe original work; they should emphasise completed work rather than intended work, and should indicate clearly the state of completion of the reported results. Submissions will be judged on correctness, originality, technical strength, significance and relevance to the conference, and interest to the attendees. All submissions should follow the two-column LREC style guidelines. We strongly recommend the use of the LaTeX style files, OpenDocument, or Microsoft Word templates created for LREC: https://lrec2026.info/authors-kit/. Unlike LREC main conference submissions, UDW submissions are allowed to include appendices, and the UDW makes a distinction between short (up to four pages) and long papers (up to eight pages). All papers must be anonymous, i.e., not reveal author(s) on the title page or through self-references. So, e.g., “We previously showed (Smith, 2020) …”, should be avoided. Instead, use citations such as “Smith (2020) previously showed …”. All papers will undergo a double-blind peer review process, with final acceptance decisions made by the workshop chairs. Submissions that violate the requirements above will be rejected without review. LRE-Map and Sharing Language Resources When submitting a paper from the START page, authors will be asked to provide essential information about resources (in a broad sense, i.e. also technologies, standards, evaluation kits, etc.) that have been used for the work described in the paper or are a new result of your research. Moreover, ELRA encourages all LREC authors to share the described LRs (data, tools, services, etc.) to enable their reuse and replicability of experiments (including evaluation ones). Presentation Format Accepted papers will be presented as oral or poster presentations. The mode of presentation will be determined by the workshop chairs and does not reflect the quality of the submission. UDW 2026 will primarily be an in-person event, but online participation will also be possible for the participants who cannot travel to the conference. Accepted papers will be published in the LREC 2026 Workshop Proceedings. Website: https://universaldependencies.org/udw26/ Contact: udw26(a)googlegroups.com Organizing Committee * Çağrı Çöltekin, Tübingen University * Kaja Dobrovoljc, University of Ljubljana & Jozef Stefan Institute * Joakim Nivre, Uppsala University

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CFP: UMR parsing shared task + DMR 2026 workshop
by Dan Zeman 11 Jan '26

11 Jan '26

Call for Participation: Shared Task in Parsing into UMR Please consider participating in shared task in multilingual parsing into Uniform Meaning Representation. Details and registration link here: https://ufal.mff.cuni.cz/umr-parsing The shared task is part of the DMR 2026 workshop, see the call for papers below: Call for Papers: DMR 2026 DMR 2026 invites the submissions of long and short papers about original works on the design, processing, and use of meaning representations. While deep learning methods have led to many breakthroughs in practical natural language applications, there is still a sense among many NLP researchers that we have a long way to go before we can develop systems that can actually “understand” human language and explain the decisions they make. Indeed, “understanding” natural language entails many different human-like capabilities, and they include but are not limited to the ability to track entities in a text, understand the relations between these entities, track events and their participants described in a text, understand how events unfold in time, and distinguish events that have actually happened from events that are planned or intended, are uncertain, or did not happen at all. We believe a critical step in achieving natural language understanding is to design meaning representations for text that have the necessary meaning “ingredients” that help us achieve these capabilities. Such meaning representations can also potentially be used to evaluate the compositional generalization capacity of deep learning models. There has been a growing body of research devoted to the design, annotation, and parsing of meaning representations in recent years. In particular, formal meaning representation frameworks such as Minimal Recursion Semantics (MRS) and Discourse Representation Theory are developed with the goal of supporting logical inference in reasoning-based AI systems and are therefore easily translatable into first-order logic, while other meaning representation frameworks such as Abstract Meaning Representation (AMR), Uniform Meaning Representation (UMR), Tecto-grammatical Representation (TR) in Prague Dependency Treebanks and the Universal Conceptual Cognitive Annotation (UCCA), put more emphasis on the representation of core predicate-argument structure. The automatic parsing of natural language text into these meaning representations and the generation of natural language text from these meaning representations are also very active areas of research, and a wide range of technical approaches and learning methods have been applied to these problems. DMR intends to bring together researchers who are producers and consumers of meaning representations and, through their interaction, gain a deeper understanding of the key elements of meaning representations that are the most valuable to the NLP community. The workshop will provide an opportunity for meaning representation researchers to present new frameworks and to critically examine existing frameworks with the goal of using their findings to inform the design of next-generation meaning representations. One particular goal is to understand the relationship between distributed meaning representations trained on large data sets using network models and the symbolic meaning representations that are carefully designed and annotated by NLP researchers, with an aim of gaining a deeper understanding of areas where each type of meaning representation is the most effective. The workshop solicits papers that address one or more of the following topics: * Development and annotation of meaning representations; * Challenges and techniques in leveraging meaning representations for downstream applications, including neuro-symbolic approaches; * The relationship between symbolic meaning representations and distributed semantic representations; * Issues in applying meaning representations to multilingual settings and lower-resourced languages; * Challenges and techniques in automatic parsing of meaning representations; * Challenges and techniques in automatically generating text from meaning representations; * Meaning representation evaluation metrics; * Cross-framework comparison of meaning representations and their formal properties; * Any other topics that address the design, processing, and use of meaning representations. Contact For any questions regarding the workshop, please contact us atdmr.workshop.2026(a)gmail.com.

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