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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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Pre-reviewed (ARR) DEADLINE EXTENSION: HEALING Workshop on Health-Related Discourse and Language (EACL 2026)
by murathan.kurfali＠ri.se 08 Jan '26

08 Jan '26

The First International Workshop on Linguistic Analysis for Health (HeaLing’26) We are excited to announce the First Workshop on Linguistic Analysis for Health (HeaLing), co-located with EACL 2026, to be held in Rabat, Morocco, on March 24–29, 2026. 📌 Important Links Workshop Website: https://healing-workshop.github.io Contact: healing-workshop(a)googlegroups.com CFP & Submissions (OpenReview): https://openreview.net/group?id=eacl.org/EACL/2026/Workshop/HeaLing 🗓️ Key Dates (AoE) Tentative Timeline Event Date Direct submission deadline December 19, 2025 (**passed**) Pre-reviewed (ARR) submission deadline January **10**, 2026 Notification of acceptance January 23, 2026 Camera-ready paper due February 3, 2026 Workshop date March 28 (afternoon session) 🧠 Workshop Scope Language-oriented approaches—such as discourse and conversation analysis, narrative medicine, and linguistic ethnography—have long been central to qualitative investigations of how medical knowledge is produced, communicated, and experienced. Today, advances in natural language processing (NLP) and artificial intelligence (AI) offer new possibilities for extending and scaling linguistic approaches across large health-related datasets. The HeaLing workshop invites contributions that integrate qualitative and computational methods to examine how language informs and transforms medicine as a social and scientific practice. A central focus of the workshop is the practical value of interpretive insights derived from language analysis. We welcome researchers from medical humanities, social and historical studies of medicine, and computational language sciences. The workshop will be held as a half-day event at EACL 2026. 🧩 Topics of Interest (include but are not limited to) - Computational + qualitative discourse analysis of clinical, scientific, policy, and other health-related texts (media, guidelines, patient narratives, clinical notes). - Metaphor and framing in illness narratives, public health messaging, and clinical communication. - Narrative medicine, story-centered clinical interventions, and evaluation of their effects. - Historical and contemporary discourse studies of medical epistemologies (how concepts, categories, and expertise are constructed). - Language, power, and inequality: how linguistic framing shapes access, stigma, and policy for marginalized populations. - Methods for responsible use of NLP/LLMs in medical language research (bias, explainability, mixed-methods validation). - Digital humanities approaches: building and interrogating historical corpora, archives, and born-digital records. - Translational impact: case studies showing how interpretive linguistic insights led to concrete changes in practice, education, or policy. 📝 Submission Format and Reviewing Procedure We accept original and unpublished research contributions (including surveys, position, and theory papers) following the ACL format. The ACL Paper Styles are available here: https://github.com/acl-org/acl-style-files (both LaTeX and Word). Long papers: up to 8 pages (+ references) Short papers: up to 4 pages (+ references) Camera-ready versions will be given one additional page to address reviewers’ comments. Papers must be submitted anonymously. We accept submissions either through our own submission page or via the ACL Rolling Review (ARR). All submissions will undergo double-blind peer review by at least three reviewers, with final acceptance decisions made by the workshop organizers. Accepted papers will be published in the workshop proceedings and presented orally or as posters. 👥 Organizing Committee Ylva Söderfeldt, Uppsala University, Sweden Vera Danilova, Uppsala University, Sweden Julia Reed, University of Vienna, Austria Murathan Kurfalı, RISE Research Institutes of Sweden, Sweden Gavin Farrell, University of Padua, Italy

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Second Call for Nominations – The Keith van Rijsbergen (KvR) Award 2026
by Yifei Yuan 08 Jan '26

08 Jan '26

The KvR Award honours outstanding researchers who have advanced the theoretical foundations of Information Retrieval — those whose work has shaped new models, paradigms, or metrics that deepen our understanding of IR. The award was first presented at ECIR 2024 to Prof. Maarten de Rijke (University of Amsterdam). The second KvR Award will be awarded at ECIR 2026 in Delft! 🔹 Eligibility: active IR researchers with ≥10 years since PhD 🔹 Deadline for nominations: 15 January 2026 🔹 Submit nominations via the form provided below Read more about the award, nomination process, and find the form to submit your nominations here: https://lnkd.in/emecdsXm, https://ecir2026.eu/calls/keith-van-rijsbergen-award

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2nd CFP: Third Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC 2026
by Paul Thompson 08 Jan '26

08 Jan '26

Third Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC 2026 https://bionlp.nlm.nih.gov/cl4health2026/ LREC 2026 Palma, Mallorca (Spain) SCOPE CL4Health fills the gap among the different biomedical language processing workshops by providing a general venue for a broad spectrum of patient-oriented language processing research. The third workshop on patient-oriented language processing follows the successful CL4Health workshops (co-located with LREC-COLING 2024 and NAACL 2025), which clearly demonstrated the need for a computational linguistics venue focused on language related to public health. CL4Health is concerned with the resources, computational approaches, and behavioral and socio-economic aspects of the public interactions with digital resources in search of health-related information that satisfies their information needs and guides their actions. The workshop invites papers concerning all areas of language processing focused on patients' health and health-related issues concerning the public. The issues include, but are not limited to, accessibility and trustworthiness of health information provided to the public; explainable and evidence-supported answers to consumer-health questions; accurate summarization of patients' health records at their health literacy level; understanding patients' non-informational needs through their language, and accurate and accessible interpretations of biomedical research. The topics of interest for the workshop include, but are not limited to the following: * Health-related information needs and online behaviors of the public; * Quality assurance and ethics considerations in language technologies and approaches applied to text and other modalities for public consumption; * Summarization of data from electronic health records for patients; * Detection of misinformation in consumer health-related resources and mitigation of potential harms; * Consumer health question answering (Community Question Answering)(CQA); * Biomedical text simplification/adaptation; * Dialogue systems to support patients' interactions with clinicians, healthcare systems, and online resources; * Linguistic resources, data, and tools for language technologies focusing on consumer health; * Infrastructures and pre-trained language models for consumer health; IMPORTANT DATES (Tentative) February 18, 2026 -Workshop Paper Due Date️ March 13, 2026 - Notification of acceptance March 20, 2026 - Camera-ready papers due April 10, 2026 - Pre-recorded video due (hard deadline) May 12, 2026 - Workshop SHARED TASKS Detecting Dosing Errors from Clinical Trials (CT-DEB'26). Clinical Trials Dosing Errors Benchmark 2026 is a challenge to predict medication errors in clinical trials using Machine Learning. The Clinical Trials Dosing Errors Benchmark 2026 (CT-DEB'26) is dedicated to automated detection of the risks of medication dosing errors within clinical trial protocols. Leveraging a curated dataset of over 29K trial records derived from the ClinicalTrials.gov<http://clinicaltrials.gov/> registry, participants are challenged to predict the risk probabilities of protocols likely to manifest dosing errors. The dataset consists of various fields with numerical, categorical, as well as textual data types. Once the shared task is concluded and the leaderboard is published, the participants are invited to submit a paper to the CL4Health workshop. Website: https://www.codabench.org/competitions/11891/ Automatic Case Report Form (CRF) Filling from Clinical Notes. Case Report Forms (CRFs) are standardized instruments in medical research used to collect patient data in a consistent and reliable way. They consist of a predefined list of items to be filled with patient information. Each item aims to collect a portion of information relevant for a specific clinical goal (e.g., allergies, chronicity of disease, tests results). Automating CRF filling from clinical notes would accelerate clinical research, reduce manual burden on healthcare professionals, and create structured representations that can be directly leveraged to produce accessible, patient- and practitioners-friendly summaries. Even though the healthcare community has been utilizing CRFs as a basic tool in the day-to-day clinical practice, publicly available CRF datasets are scarce, limiting the development of robust NLP systems for this task. We present this Shared Task on CRF-filling aiming to enhance research on systems that can be applied in real clinical settings. Website: https://sites.google.com/fbk.eu/crf/ ArchEHR-QA 2026: Grounded Question Answering from Electronic Health Records. The ArchEHR-QA (“Archer”) shared task focuses on answering patients’ health-related questions using their own electronic health records (EHRs). While prior work has explored general health question answering, far less attention has been paid to leveraging patient-specific records and to grounding model outputs in explicit clinical evidence, i.e., linking answers to specific supporting content in the clinical notes. The shared task dataset consists of patient-authored questions, corresponding clinician-interpreted counterparts, clinical note excerpts with sentence-level relevance annotations, and reference clinician-authored answers grounded in the notes. ArchEHR-QA targets the problem of producing answers to patient questions that are supported by and explicitly linked to the underlying clinical notes. This second iteration builds on the 2025 challenge (which was co-located with the ACL 2025 BioNLP Workshop) by expanding the dataset and introducing four complementary subtasks spanning question interpretation, clinical evidence identification, answer generation, and answer–evidence alignment. Teams may participate in any subset of subtasks and will be invited to submit system description papers detailing their approaches and results. Website: https://archehr-qa.github.io/ FoodBench-QA 2026: Grounded Food & Nutrition Question Answering. FoodBench-QA 2026 is a shared task challenging systems to answer food and nutrition questions using evidence from nutrient databases and food ontologies.The dataset includes realistic dietary queries, ingredient and their quantities lists, and recipe descriptions, requiring models to perform nutrient estimation, FSA traffic-light prediction, and food entity recognition/linking across three food semantic models. Participants must generate accurate, evidence-based answers across these subtasks (or at least one of it). After the shared task concludes and the leaderboard is released, participants will be invited to submit their work to the Shared Tasks track of the CL4Health workshop at LREC 2026. Website: https://www.codabench.org/competitions/12112/ SUBMISSIONS Two types of submissions are invited: - Full papers: should not exceed eight (8) pages of text, plus unlimited references. These are intended to be reports of original research. - Short papers: may consist of up to four (4) pages of content, plus unlimited references. Appropriate short paper topics include preliminary results, application notes, descriptions of work in progress, etc. Electronic Submission: Submissions must be electronic and in PDF format, using the Softconf START conference management system. Submissions need to be anonymous. Papers should follow LREC 2026 formatting. LREC provides style files for LaTeX and Microsoft Word at https://lrec2026.info/authors-kit/. Submission site: https://softconf.com/lrec2026/CL4Health/ Dual submission policy: papers may NOT be submitted to the workshop if they are or will be concurrently submitted to another meeting or publication. 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). MEETING The workshop will be hybrid. Virtual attendees must be registered for the workshop to access the online environment. Accepted papers will be presented as posters or oral presentations based on the reviewers’ recommendations. ORGANIZERS - Deepak Gupta, US National Library of Medicine - Paul Thompson, National Centre for Text Mining and University of Manchester, UK - Dina Demner-Fushman, US National Library of Medicine - Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK -- Paul Thompson Research Fellow Department of Computer Science National Centre for Text Mining Manchester Institute of Biotechnology University of Manchester 131 Princess Street Manchester M1 7DN UK http://personalpages.manchester.ac.uk/staff/Paul.Thompson/

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DEADLINE EXTENSION: Learner Corpus Research Conference 2026 (LCR 2026, Prague) – 3rd CfP
by tomas.graf＠ff.cuni.cz 08 Jan '26

08 Jan '26

Learner Corpus Research Conference 2026 – LCR 2026 The 8th Learner Corpus Research Conference to be held in Prague 16–19 September, 2026 First Call for Papers opens on 16 November 2025 Organizers: Tomáš Gráf, Barbora Bulantová, Kryštof Buchal, Alexandr Rosen, Radek Skarnitzl, Lanfen Huang, Kristián Centek, Daniela Marková Conference site: https://lcr2026.ff.cuni.cz Key dates: Submission deadline (extended): 31 January 2026 Notification of acceptance: 8–10 April 2026 Conference dates: 17–19 September 2026 Pre-conference workshops and PhD programme: 16 September 2026 The Learner Corpus Research Conference 2026 (LCR 2026) will be held in the beautiful and historically rich city of Prague on 16–19 September 2026. Organized biennially under the auspices of the Learner Corpus Association, the upcoming conference is hosted by the Department of Linguistics at the Faculty of Arts, Charles University. The event is co-organized by two of its constituent units: the Department of English Language and ELT Methodology and the Czech National Corpus. The conference, titled Forging the Future of Learner Corpus Research, reflects a dual awareness: of the field’s substantial legacy and of the pressing need to embrace emerging technological and methodological innovations. It also highlights the importance of identifying new directions and developing fresh perspectives in learner corpus studies. The conference theme resonates with the extensive experience and pioneering contributions of the Czech National Corpus, which has been shaping standards in corpus linguistics for over three decades. Moreover, the Faculty of Arts and its linguistics departments are deeply rooted in the tradition of the Prague Linguistic Circle, and they previously hosted the 38th ICAME conference in 2017. We warmly encourage all participants to contribute actively to discussions and to share their insights. We aim to foster a collegial and collaborative environment conducive to the advancement of learner corpus research. We look forward to welcoming you to Prague for a stimulating and inspiring gathering of researchers in the field. Call description We welcome all contributions related to learner corpus research and strongly encourage authors to explore new directions, challenge existing paradigms, or apply innovative approaches to learner corpus data. Areas of interest include, but are not limited to: Language for Academic and Specific Purposes Language Teaching, Assessment, and Testing Learner Corpus-Based SLA Studies Corpora as Pedagogical Resources Multimodal Learner Corpora Software Tools for Learner Corpus Analysis Corpus-Based Translation Studies English as a Medium of Instruction (EMI) English as a Lingua Franca (ELF) Data Mining and Exploratory Methods Statistical and Quantitative Approaches Discourse Analysis and Pragmatics NLP Applications in Learner Corpus Research Complexity, Accuracy, and Fluency (CAF) Measures Presentation formats We invite submissions for the following formats: Full paper (20 minutes + 10 minutes discussion) Work in progress (WIP) report (10 minutes + 5 minutes discussion) Corpus/Software demonstration Poster presentation Insight session (Insight sessions are intended primarily for PhD students and/or early-career researchers. The format allows for a 10-minute presentation followed by a 10-minute expert feedback follow-up. ) The WIP reports and posters are intended to present research still at a preliminary stage and on which researchers would like to get feedback. The language of the conference is English. Abstract submission We invite submissions of abstracts in the range of 500 words (excluding references) for presentations in one of the categories listed above. Please indicate the category of your submission (Full paper / WiP Report / Corpus / software demonstration / Poster presentation) at the beginning of your abstract. Abstracts should include: A clearly articulated research question and an explanation of its relevance to learner corpus research A brief overview of the research approach, data, and methods used A summary of the main results and their interpretation. Please do not include author names or institutional affiliations in the submitted abstract. Submissions must be made via OpenReview (registration necessary). https://openreview.net/group?id=learnercorpusassociation.org/LCR/2026/Confer... The working language of the conference is English. For co-authored submissions, one author should register and upload the abstract, but each co-author must register individually for the conference.

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CFP for the DHOW-MiLLA: Joint Workshop on Diffusion of Harmful Content on Online Web and Countering Misinformation in the Age of LLMs and Agents
by Thomas Mandl 07 Jan '26

07 Jan '26

CFP for the DHOW-MiLLA: Joint Workshop on Diffusion of Harmful Content on Online Web and Countering Misinformation in the Age of LLMs and Agents Submission deadline: January 10, 2026 AOE Workshop website: https://dhow-workshop.github.io/2026/ <https://dhow-workshop.github.io/2026> Co-located with WWW 2026 <https://www2026.thewebconf.org/> Dubai, UAE, April 13-14, 2026 Workshop Description With the advancement of digital technologies and gadgets, online content is easily accessible. At the same time, harmful content also spreads. There are different harmful content available on different platforms in multiple languages. The topic of harmful content is broad and covers multiple research directions. But from the user’s perspective, they are affected by them all. Often, it is studied individually, like misinformation and hate speech. Research has been done on one platform, monolingual, on a particular issue. It leads to harmful content spreaders switching platforms and languages to reach the user base. Harmful is not limited to social media but also news media. Spreader shares harmful content in posts, news articles, comments, and hyperlinks. So, there is a need to study harmful content by combining cross-platform, language, multimodal data and topics. We will bring the research on harmful content under one umbrella so that research on different topics (hate speech, misinformation, disinformation, self-harm, offensive content, etc.) can bring some novel methods and recommendations for users, leveraging text analysis with image, audio, and video recognition to detect harmful content in diverse formats. The workshop will cover the ongoing issue of war or elections in 2025. We believe this workshop will provide a unique opportunity for researchers and practitioners to exchange ideas, share the latest developments, and collaborate on addressing the challenges associated with harmful content spread across the Web. We expect that the workshop will generate insights and discussions that will help advance the field of societal artificial intelligence (AI) for the development of a safer internet. In addition to attracting high-quality research contributions to the workshop, one of the aims of the workshop is to mobilise the researchers working on the related areas to form a community. Submissions Topics * Studying different types of harmful content * Improving Factual Reliability in LLMs * Computational fact-checking & Misinformation * Detection Role of Generative AI in Mitigating Harmful Content Harassment, Bullying, and Hate Speech Detection Explainable AI for Harmful Content Analysis * Agentic AI Systems and Misinformation * Detection methods for LLM/VLM-generated text, audio, and imagery * Deepfake and Synthetic Media * Ethical & Societal Implications of AI in Content Moderation * Both Qualitative and Quantitative studies on harmful content * Psychological effects of harmful content like mental health * Approaches for data collection or data annotation using multimodal large models on harmful content * User study on the effects of harmful content on human beings * Human-AI Collaboration and Defenses Submissions - Submission Instructions: https://dhow-workshop.github.io/2026/#call <https://dhow-workshop.github.io/2026/#call> - Submission Link: https://openreview.net/group?id=ACM.org/TheWebConf/2026/Workshop/DHOW-MiLLA <https://openreview.net/group?id=ACM.org/TheWebConf/2026/Workshop/DHOW-MiLLA> Important Dates Submission deadline: extended to January 7, 2026 Notification of acceptance: January 26, 2026 Camera-ready papers due: February 2, 2026 Workshop date: April 13-14, 2026 Workshop organizers * Thomas Mandl, University of Hildesheim, Germany * Haiming Liu, University of Southampton, UK * Gautam Kishore Shahi, University of Duisburg-Essen, Germany * Amit Kumar Jaiswal, Indian Institute of Technology (BHU) Varanasi, India * Durgesh Nandini, University of Bayreuth, Germany * Luis-Daniel Ibáñez, University of Southampton, UK * Junichi Suga, Fujitsu Research, Japan * Dai Yamamoto, Fujitsu Research, Japan * Rahul Mishra, Fujitsu Research, India * Rajakrishnan P Rajkumar, IIIT Hyderabad, India * Sagar Uprety, University College London, UK * Bornali Phukon, University of Illinois Urbana Champaign, USA * Sujit Kumar, Nanyang Technological University, Singapore

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