- Corpora - ELRA lists

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 Regular papers should present substantial, original, and unpublished research, including empirical evaluation results where appropriate.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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Can LLMs Finally Win? The CRAC 2026 Shared Task on Multilingual Coreference Resolution
by Dan Zeman 11 Jan '26

11 Jan '26

* ———————————————————————————— Call for Participation: CRAC 2026 Shared Task on Multilingual Coreference Resolution ———————————————————————————— https://ufal.mff.cuni.cz/corefud/crac26 We are excited to announce the fifth edition of the Shared Task on Multilingual Coreference Resolution! As in the previous edition, where LLMs were not able to dethrone traditional approaches, the upcoming task again primarily focuses on LLMs and challenges their ability to predict coreference across a range of typologically diverse languages. The results will be presented at the CODI-CRAC 2026 workshop, co-located with the ACL 2026 conference in San Diego, USA. System description papers will be published in the proceedings of CODI-CRAC, also available in the ACL anthology. ————————————— Task description ————————————— The task is to identify mentions and cluster them according to their reference to the same entity. Participants may choose between two tracks: 1. LLM track 2. Unconstrained track ————————————— Data ————————————— The Shared Task is based on the upcoming CorefUD 1.4. collection, which comprises datasets with coreference annotation for at least 17 languages. Participants may also choose to compete on only a subset of these languages. ————————————— Timeline (tentative) ————————————— January 16, 2026 - start of the development phase * release of training and development data * evaluation tool available on GitHub * baseline system available at GitHub * development evaluation possible via CodaBench March 4, 2026 - start of the evaluation phase * test evaluation via CodaBench March 18, 2026 (AoE) - end of the evaluation phase April 10, 2026 - submission of system description papers to the CODI-CRAC 2026 workshop July 3/4, 2026 – the CODI-CRAC workshop at ACL ————————————— Participation ————————————— Please let us know by filling in the registration form: https://ufal.mff.cuni.cz/corefud/crac26#llm-registration <https://ufal.mff.cuni.cz/corefud/crac26#llm-registration> ————————————— Organizers ————————————— Michal Novák, Charles University, Czechia Martin Popel, Charles University, Czechia Zdeněk Žabokrtský, Charles University, Czechia Dan Zeman, Charles University, Czechia Anna Nedoluzhko, Charles University, Czechia Milan Straka, Charles University, Czechia Ondřej Pražák, University of West Bohemia, Czechia Miloslav Konopík, University of West Bohemia, Czechia Jakub Sido, University of West Bohemia, Czechia *

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survey on corpora user experience
by varvara.magomedova＠ung.si 11 Jan '26

11 Jan '26

Dear all, I'm collecting data on corpus interface usability to support a standardization proposal. If you use corpora for research or teaching, I'd very much appreciate 5-10 minutes of your time: https://www.1ka.si/a/65063543 The survey covers common frustrations (export limits, query interfaces, metadata gaps) and desired improvements. It is fully anonymous, doesn't even ask how far you are in your academic career. Thanks a lot! Varya Magomedova varvara.magomedova[(a)]ung.si University of Nova Gorica

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MATS AI Safety Summer Fellowship: Apply by Jan. 18
by Eric Dhan 10 Jan '26

10 Jan '26

A quick reminder that applications to the MATS Summer 2026 fellowship cohort are due by January 18. It only takes 1-2 hours to apply! MATS Summer 2026 <https://www.matsprogram.org/apply?utm_source=corpora&utm_medium=&utm_campai…> (June - August) is a 12-week fully-funded research fellowship for aspiring AI alignment, control, security, and governance researchers. Fellows work directly with mentors from Anthropic, Google DeepMind, OpenAI, UK AISI, GovAI, Redwood, METR, Apollo, Goodfire, AIFP, and other top organizations—with housing and office space provided in Berkeley or London. MATS has accelerated 450+ researchers; among alumni who graduated before 2025, 80% now work on AI safety. *Submit your application by Jan. 18!* <https://www.matsprogram.org/apply?utm_source=corpora&utm_medium=&utm_campai…> Please share this opportunity with your networks. We’d love to reach as many people as possible so that we can continue to attract top talent into AI safety. Best, Eric -- Eric Dhan Operations Generalist, MATS <https://www.matsprogram.org/> LinkedIn <https://www.linkedin.com/in/eric-dhan/>

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CFP: StanceNakba 2026 Shared Task (LREC 2026)
by Wajdi Zaghouani 10 Jan '26

10 Jan '26

We are pleased to invite you to participate in StanceNakba 2026, a shared task co-located with LREC 2026 as part of Nakba-NLP 2026: The 2nd International Workshop on Nakba Narratives as Language Resources. The shared task focuses on Actor- and Topic-Aware Stance Detection in polarized social media discourse related to the Palestinian–Israeli conflict. Task Overview * Subtask A (English): Actor-Level Stance Detection Labels: Pro-Palestine | Pro-Israel | Neutral * Subtask B (Arabic): Cross-Topic Stance Detection Labels: Favor | Against | Neither Topics: normalization with Israel and refugee presence in Jordan Dataset & Evaluation * 2,606 manually annotated social media posts * English and Arabic datasets * Primary evaluation metric: Macro-F1 Important Dates * Training data release: January 10, 2026 * System submission deadline: February 17, 2026 * Workshop: May 11–16, 2026 (TBC) Participation in the shared task is free of charge. Please note that at least one member of each participating team must be registered for the conference. Further details, data access, and submission instructions are available on the shared task website: https://marsadlab.github.io/stancenakba/index.html If you have any questions, feel free to contact us at stancenakba(a)gmail.com<mailto:stancenakba@gmail.com>. We warmly encourage you to join us in advancing stance detection research and improving our understanding of polarized online discourse. Kind regards, The StanceNakba 2026 Organizing Team

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CfA: Conference "How does artificial intelligence challenge our traditional understanding of legal reasoning?" August 27-28, 2026, University of St.Gallen
by reto.gubelmann＠uzh.ch 09 Jan '26

09 Jan '26

Dear Colleagues, I would like to draw your attention to a conference that I’m co-organizing. Please find the call for Abstracts below. For further inquiries, please contact the Organizing Committee at: conference-ile(a)unisg.ch. All best, Reto Gubelmann University of Zurich ********************************* CALL FOR ABSTRACTS How does artificial intelligence challenge our traditional understanding of legal reasoning? August 27-28, 2026, University of St. Gallen This international conference invites scholars, practitioners, and Natural Language Processing (NLP) researchers to explore how contemporary Language AI Systems—especially large language models (LLMs) and Deep Learning Methods—reshape fundamental assumptions and methods about legal method, interpretation, and decision-making. Legal practice often presents itself as value-laden, interpretive, and methodologically disciplined. Yet current Language AI predominantly operate through statistical pattern recognition and representation rather than propositional argument. This tension raises pressing questions: Does Language AI merely automate inessential aspects of legal work, or does it reveal that legal reasoning itself has long contained implicit statistical or probabilistic elements? Do machine-generated legal outputs expose hidden (ir)regularities in judicial and administrative practice? And how should legal theory respond when computational systems appear to “mimic” legal judgment without engaging, for all we know, in human-like, propositional reasoning? We especially welcome contributions addressing, but not limited to, the following themes: • Statistical Aspects in Legal Reasoning: What role do probabilistic or statistical considerations already play—implicitly or explicitly—in legal interpretation and decision-making? • AI and the Transformation of Legal Method: Does the rise of generative Language AI undermine traditional conceptions of doctrinal reasoning, hermeneutics, or precedent? • Values, Normativity, and Language: How do values enter legal language, and can AI systems meaningfully represent or operationalize normative commitments? • AI as Mirror or Distortion of Legal Practice: Does AI reveal the latent patterns of legal discourse, contributing to a more objective practice, or does it impose new biases and structures that distort legal meaning? • Epistemic, Democratic, and Ethical Implications: What does the integration of (currently largely private and often closed-sourced) AI into legal institutions (public administration or courts) imply for legitimacy, transparency, and the rule of law? We invite submissions from law, philosophy, NLP, (computational) linguistics, computer science, statistics and related fields. Both theoretical and empirical contributions are welcome. Confirmed Keynote Speakers • Prof. Dr. Christoph Engel, Max Planck Institute, Bonn • Dr. Joel Niklaus, Machine Learning Engineer, Hugging Face Submission Guidelines: Abstract • Scope: 300–500 words • Submission deadline: February 28, 2026, to conference-ile(a)unisg.ch • Form: Anonymized PDF. Please indicate your name, affiliation and contact information in the body of your email • Notification of acceptance: April 2, 2026 Paper and presentation • Paper scope: 3,000 words • Submission deadline: August 14, 2025 • Presentations of 15 minutes, followed by 30 minutes discussion, online presentations are possible Scientific and Organizing Committee • Désirée Klingler, University of St. Gallen • Peter Hongler, University of St. Gallen • Reto Gubelmann, University of Zurich

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Webinar by: Thamar Solorio (Mohamed bin Zayed University of Artificial Intelligence (MBZUAI))
by HiTZ zentroa 09 Jan '26

09 Jan '26

**** We apologize for the multiple copies of this email. In case you are already registered to the next webinar, you do not need to register again. **** Dear colleague, We are happy to announce the next webinar in the Language Technology webinar series organized by The HiTZ Chair of Artificial Intelligence and Language Technology (https://hitz.eus/katedra). We are organizing one seminar every month. Next webinar: Speaker: Thamar Solorio (Mohamed bin Zayed University of Artificial Intelligence (MBZUAI)) Title: A Research Agenda for Low Resource NLP Date: Thursday, January 15, 2026 - 15:00 Summary: Low resource NLP is nowadays an umbrella keyword that covers a wide set of research directions. In this talk I will argue that it is important to carefully present the low resource scenario and distinguish when the languages are truly lacking resources, as opposed to simulating lack of labeled data. I propose to follow a more systematic way to represent work in this space and to question how we approach technology development for these languages. I will also present recent work in my group that contributes to improve language representation by exploring efficient approaches to diverse languages. Bio: Thamar Solorio is a professor of NLP at MBZUAI where she also serves as Vice Provost for Faculty Excellence and Advancement. Her research interests include NLP for low-resource settings and multilingual data, including code-switching and information extraction. More recently, she has been exploring language and vision problems, focusing on developing inclusive NLP. She served two terms as an elected board member of the North American Chapter of the Association of Computational Linguistics (NAACL) and was PC co-chair for NAACL 2019, and recently stepped down from being co-Editor in Chief of the ACL Rolling Review Initiative (ARR). She was the general chair of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP). Registration: https://www.hitz.eus/webinar_izenematea Upcoming webinars: Henning Wachsmuth (February 5) José Andrés González-López (March 5) Ranjay Krishna (April 16) You can view the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info Best wishes, The HiTZ Chair of Artificial Intelligence and Language Technology P.S: HiTZ will not grant any type of certificate for attendance at these webinars.

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Call for Papers: The 1st Workshop on Computational Affective Science
by Roman Klinger 08 Jan '26

08 Jan '26

Call for Papers: The 1st Workshop on Computational Affective Science First Call for Papers: The 1st Workshop on Computational Affective Science (CAS 2026), co-located with the Language Resources and Evaluation Conference (LREC) 2026 in Palma de Mallorca, Spain, May 16. Website: https://casworkshop.github.io/ <https://casworkshop.github.io/> Contact: cas-workshop(a)googlegroups.com We invite submissions to the first Workshop on Computational Affective Science (CAS 2026), co-located with LREC 2026, on research related to the understanding of affect and emotions through language and computation. CAS will accept archival long and short paper submissions, featuring substantial, original, and unpublished research. We also encourage submissions of extended abstracts from researchers in the broader Affective Science community, with up to two pages of content featuring the research background/hypotheses and a description of methods/results. Extended abstracts are non-archival, offering the option for publication and presentation at other conference venues. Motivation Affect refers to the fundamental neural processes that generate and regulate emotions, moods, and feeling states. Affect and emotions are central to how we organize meaning, to our behavior, to our health and well-being, and to our very survival. Despite this, and even though most of us are intimately familiar with emotions in everyday life, there is much we do not know about how emotions work and how they impact our lives. Affective Science is a broad interdisciplinary field that explores these and related questions about affect and emotions. Since language is a powerful mechanism of emotion expression, there is a growing use of language data and advanced natural language processing (NLP) algorithms to shed light on fundamental questions about emotions. The Workshop on Computational Affective Science (CAS) aims to be a dedicated venue for work focused specifically on the link between NLP and affective science. Interdisciplinary Scope The workshop takes an interdisciplinary approach to affective science and aims at bringing together NLP researchers, scientists, and theorists from many research areas, including psychology, sociology,, neuroscience, and philosophy. Although work in sentiment analysis is decades old, this work often proceeds separately and in different fields from research and theory in affective science. Meanwhile, affective scientists in psychology, sociology, neuroscience and philosophy increasingly seek to use linguistic tools to shed light on the nature of emotions, moods, and feeling states. CAS is therefore co-organized by an interdisciplinary group of researchers (spanning NLP and Affective Science) to foment collaboration at this exciting frontier of research. Submissions We invite long and short archival paper submissions, as well as non-archival extended abstracts on a broad range of topics at the intersection of affective science and natural language processing, including but not limited to: 1. The Nature of Affect and Computational Modeling of Emotions Computational experiments that add to our understanding of affect and emotions, including findings relevant to: * theories and nature of emotion * the biology or neuroscience of emotions * appraisal models * dimensional models (valence / arousal / dominance) * models of constructed emotion * cognitive-affective architectures * emotion dynamics (emergence, intensification, decay, transitions) * emotion granularity * emotion regulation * affective embodiment * evolutionary and developmental affect * emotion–cognition interactions These areas are relevant not just to human affect, but may also apply to data animals and artificial agents. 2. Affective Data and Resources Work on compiling and annotating affect-related information in text, speech, facial and bodily expression, and physiological signals (ECG, EEG, GSR, multimodal biosensing), with a focus on text data (monolingual or multilingual) and multimodal data suitable for an NLP venue. Data from underserved languages is especially encouraged. 3. Emotion Recognition, Prediction, and Inference At the instance level: * emotion classification (discrete emotions, dimensional ratings) * emotion intensity estimation * emotion cause detection * context-aware affect inference (culture, situation, social setting) * structured emotion analysis At the aggregate level: * creating emotion arcs * determining broad trends in emotions over time or across locations * tracking emotional responses toward entities of interest (e.g., climate change) * document-level and cross-document emotion analysis * labeling social networks 4. Applications Including but not limited to: * Affect and health, psychopathology, and mental disorders * Affect and behavior/social science (e.g., interpersonal affect, empathy, group-level affect, affect contagion, computational emotion regulation) * Affect and education * Affect and literature/narratives/digital humanities * Affect and commerce 5. Explainability and Interpretability in Computational Affective Models Work aimed at improving the transparency and interpretability of affective systems. This includes understanding how models represent and infer emotions and identifying key cues driving predictions. 6. Ethics, Fairness, Theory Integration, Philosophical Implications * Bias and generalizability of affective systems across demographics * Privacy and ethics in affective data collection * Examining whether automatic NLP systems rely on current and valid theories of affect and emotion * The implications of machines modeling or simulating affect * Societal considerations surrounding affective artificial agents ------------------------------------------------------------------------ Important Dates (tentative): ·Submission deadline:16 Feb 2026 ·Notification of acceptance: 16 March 2026 ·Camera Ready Paper due: 23 March 2026 ·Workshop date: 16 May 2026 Submission Details: We invite submissions for archival long and short papers, as well as non-archival extended abstracts. Archival long and short papers should feature novel and unpublished work relating to the topics detailed above. We also invite submissions of extended abstractsfrom researchers in the broader Affective Science community, with up to two pages of content featuring the research background/hypotheses and a description of methods/results. Extended abstracts are non-archival, offering the option for publication and presentation at other conference venues. Archival Track: ·Long Paper: Consists of up to 8 pages of content, with additional pages for references, limitations, ethical considerations, and appendices. ·Short Paper: Consists of up to 4 pages of content, with additional pages for references, limitations, ethical considerations, and appendices. (When preparing camera ready papers, you will be allowed one extra page to address comments by the reviewers.) Non-Archival Track: ·Extended Abstract: Up to 2 pages. Submission Format: All submissions must use the LREC 2026 template and follow the guidelines found at:https://lrec2026.info/authors-kit/ <https://lrec2026.info/authors-kit/>(Note: extended abstracts can be limited to being 1-2 pages in length). Mandatory Ethics Section:We ask all authors to include a section on Ethical Considerations in their submission, touching on the ethical concerns and broader societal impacts of the work. This discussion section will not count towards the page limit. Submission Site: All submissions must be made through the SoftConf portal. The link to the system will be shared shortly. Additional Details: Website: https://casworkshop.github.io/ <https://casworkshop.github.io/> Attendance: The workshop will follow the attendance policy of the main conference (https://lrec2026.info/registration-policy/ ). Organizers: * Christopher Bagdon, University of Bamberg, Germany * Krishnapriya Vishnubhotla, National Research Council Canada * Kristen A. Lindquist, The Ohio State University, USA * Lyle Ungar, University of Pennsylvania, USA * Roman Klinger, University of Bamberg, Germany * Saif M. Mohammad, National Research Council Canada Contact us at cas-workshop(a)googlegroups.com with any questions.

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1st Call for Papers: SIGUL 2026 Joint Workshop with ELE, EURALI, and DCLRL Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages
by Atul K. Ojha 08 Jan '26

08 Jan '26

Apologies for cross-posting. --------------------------------------------------------------------------- *SIGUL 2026 Joint Workshop with ELE, EURALI, and DCLRL* *Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages* *https://sites.google.com/view/sigul2026/home-page <https://sites.google.com/view/sigul2026/home-page>* ------------------------------------ We are pleased to announce the upcoming SIGUL 2026 Joint Workshop with ELE, EURALI, and DCLRL on Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages <https://sites.google.com/view/sigul2026/home-page>, co-located with *LREC 2026 *in Palma, Mallorca, Spain. This workshop brings together researchers working on less-resourced, endangered, minority, low-density, and underrepresented languages to share novel techniques, resources, strategies, and evaluation methods. We emphasize the entire pipeline: data creation, modeling, adaptation/transfer, system development, evaluation, deployment, and ethical/community engagement. We invite contributions on, but not limited to, the following topics: - Data collection, annotation, and curation for under-resourced languages (crowdsourcing, participatory methods, gamification, unsupervised or weakly supervised methods) - Learning with limited supervision (zero- or few-shot, PEFT, RAG with linguistic resources) - Multilingual alignment, representation learning, and language embeddings, including rare languages - Speech, multimodal, and cross-modal technologies for under-resourced languages (speech recognition, synthesis, speech-to-text, speech translation, multimodal resources) - Basic text processing (normalization, orthography, transliteration, tokenization/segmentation, morphological and syntactic processing) in and for low-resource settings. - Low-resource machine translation (pivoting, alignment, synthetic data) - Evaluation frameworks, benchmarks, and metrics designed or adapted for underrepresented languages - Adaptation, domain adaptation, and robustness to domain shift in low-resource contexts - Responsible approaches, ethical issues, community engagement, data sovereignty, and language revitalization - Deployment, tools, and practical systems for underserved languages (e.g., mobile apps, dictionary or translation apps, linguistic tools) - Case studies of success and negative results (with lessons learned) - Interoperability, standardization, and metadata practices for datasets in low-resource scenarios Special Themes Language modeling for intra-language variation, dialects, accents, and regional variants of less-resourced languages Many less-resourced languages display rich internal diversity, including dialects, accents, and regional or social varieties. This special theme focuses on developing language models and speech technologies that capture and respect intra-language variation rather than reduce it to a single “standard.” We welcome work on dialect identification and adaptation, accent-robust speech systems, normalization vs. diversity-preserving modeling, and cross-dialect transfer in low-data scenarios. Approaches combining linguistic insights, community participation, and ethical awareness are especially encouraged. The aim is to build technologies that reflect and sustain the true linguistic richness of under-resourced languages. Ultra-Low-Resource Language Adaptation This special theme focuses on methods that enable effective language and speech technology development under extreme data scarcity. We invite research on transfer learning, cross-lingual adaptation, multilingual pretraining, and self-supervised or few-shot approaches tailored to ultra-low-resource settings. Work on evaluation, data augmentation (including synthetic data), and leveraging typological or linguistic knowledge is also welcome. The goal is to advance techniques that extend modern language technologies to the most underrepresented languages, ensuring inclusivity in the digital age. Community-Led Project Showcase To help ground research in community needs, we invite brief (5–10 min) presentations by language community members, NGOs, or practitioners describing real-world challenges or resource needs. Position papers or research posters are appropriate formats for this category. Important Dates Paper Submission Deadline: February 20 (Friday), 2026 Notification of Acceptance: March 22 (Sunday), 2026 Submission of Camera-Ready: March 30 (Monday), 2026 Workshop Date: 11-12 May 2026 All deadlines are anywhere-on-earth (AoE). Call for Papers We welcome original research papers and ongoing work relevant to the topics of the workshop. Each submission can be one of the following categories: - research papers; - position papers for reflective considerations of methodological, best practice, and institutional issues (e.g., ethics, data ownership, speakers’ community involvement, de-colonizing approaches); - posters, for work-in-progress projects in the early stage of development or description of new resources; - demo papers and early-career/student papers (to be submitted as extended abstracts and presented as posters). The research and position papers should range from four (4) to eight (8) pages, while demo papers are limited to four (4) pages. References don't count towards page limits. Accepted papers will appear in the workshop proceedings, which include both oral and poster papers in the same format. Determination of the presentation format (oral vs. poster) is based solely on an assessment of the optimal method of communication (more or less interactive), given the paper content. Submissions must be anonymous and follow LREC formatting guidelines <https://lrec2026.info/authors-kit/>. For inquiries, send an email to claudia.soria(a)cnr.it. Identify, Describe and Share your LRs! 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). Thanks, Atul

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