- Corpora - ELRA lists

Call for participation: Shared task on Predicting Disagreements in WiC Annotations
by Dominik Schlechtweg 23 Sep '24

23 Sep '24

Dear colleagues, The CoMeDi (Context and Meaning—Navigating Disagreements in NLP Annotations) workshop will host a shared task. We invite participants to solve two subtasks given a pair of words uses: Subtask 1: Ordinal Word-in-Context Detection (OGWiC) Subtask 2: Disagreement in Word-in-Context Detection (DisWiC) The task takes a different view on modeling of word meaning by (i) treating WiC as an ordinal classification task, and (ii) making disagreement the explicit detection aim (instead of removing it). The workshop will colocated with COLING 2025, where the results of the shared task will be presented. All information can be found on our website: https://comedinlp.github.io/ Everyone is cordially invited to participate. Feel free to approach us in case of any questions. Best, Dominik -- https://garrafao.github.io/ https://www.ims.uni-stuttgart.de/en/institute/team/Schlechtweg/

2 3

Job offer: research assistant (m/f/d) (E 13 TV-G-U) in computer science at GU Frankfurt
by Andy Lücking 22 Sep '24

22 Sep '24

*** Apologies for cross-postings *** At the Institute for Computer Science (Prof. Dr. Alexander Mehler), Department of Computer Science and Mathematics at Goethe University Frankfurt, a position for a research assistant (m/f/d) (E 13 TV-G-U) is available at the earliest possible date research assistant (m/f/d) (E 13 TV-G-U) for a period of three years within the ENTAILab project – research infrastructure and innovation lab. The salary scale is based on the job characteristics of the collective agreement applicable to Goethe University (TV-G-U). The project is part of the priority program (SPP) New Data Spaces for the Social Sciences, which is funded by the German Research Foundation (DFG) (see https://www.new-data-spaces.de). The aim of the project is to establish a research-oriented infrastructure for novel data in survey research. To this end, a method-oriented innovation laboratory for novel methods in survey research is to be set up, which will develop and test methods of machine learning and artificial intelligence in cooperation with the projects of the SPP. The subject of the methods to be developed is multimodal data and thus not primarily or exclusively linguistic research data. You are expected to collaborate in the project and actively participate in the workshops and events of the SPP. We are looking for a highly qualified individual with a keen interest in working in the field of cutting-edge research infrastructures and in the team-oriented development and application of innovative, research-oriented methods in the field of survey research and the social sciences. With the SPP New Data Spaces for the Social Sciences and the Text-Technology Lab, in which the position will be embedded, we offer two research-strong, internationally oriented working environments in the areas of computational humanities, multimodal computing, machine learning and artificial intelligence. This also includes financial resources for conference participation and individual career development. Requirements: · Completed academic university degree (e.g. Master's) in a relevant subject with a focus on information science · Very good knowledge of English (C1) · Proven experience in the field of databases and machine learning or artificial intelligence methods · Extensive programming knowledge in Java, Python or similar · Knowledge of container technologies such as Docker, Kubernetes or similar · An interest in social science issues is desirable. Please send your application with the usual documents (cover letter, CV, copies of certificates) electronically in a combined PDF document by 08.10.2024 to Prof. Dr. Alexander Mehler: mehler(a)em.uni-frankfurt.de.

1 0

One PhD Position and One Postdoc Position Open in Computational Social Science / Computational Linguistics, IMS Stuttgart, Germany
by Tanise Ceron 22 Sep '24

22 Sep '24

(Posted: September 13, 2024; Deadline: October 6, 2024) The Theoretical Computational Linguistics group [1] at the Institute for Natural Language Processing (IMS), University of Stuttgart, Germany, has two open positions as part of the MULTIVIEW project [2]: one for a PhD candidate and one for a postdoctoral researcher. The project, led by Amelie Wührl [3] and Tanise Ceron [4], focuses on diversifying news recommendation. The successful candidates will investigate methods for diversifying perspectives in news recommendation systems based on textual and discourse features. The general goals are to create datasets and develop methods that identify and rank news based on a variety of perspectives on the same events. The candidates should have a background in computer science, computational linguistics or similar with substantial knowledge of natural language processing including neural network modeling and strong programming and software engineering skills. They require excellent communication skills and knowledge of English, and interest in interdisciplinary and team work. Prior experience with recommendation systems and large language models are considered a plus. A master’s degree level of education is required for the PhD candidate and a PhD title is required for the postdoctoral candidate. The candidates will be employed by IMS at the University of Stuttgart. The PhD position is available for three years, starting in January 2025. It is a 75% position, following the German university pay scale (TV-L 13) [5]. The candidate will be co-supervised by Sebastian Padó [6] and Tanise Ceron. The postdoctoral position is for a duration of 13 months, beginning in January 2025. It is a full-time position (100%), also according to the German university pay scale (TV-L 13) [7]. To apply, please send a full CV and letter of motivation together in a single PDF document to Tanise Ceron (tanise.ceron at ims.uni-stuttgart.de). The motivation letter should highlight the candidate’s relevant research or work experience, explain their interest in the project, and outline how they can contribute to it. Applications received by October 6 will receive full consideration. For further clarification, please contact Amelie Wührl and Tanise Ceron (amelie.wuehrl, tanise.ceron at ims.uni-stuttgart.de) About Stuttgart and the University of Stuttgart: The University of Stuttgart is a technically oriented university in Germany. It is especially known for engineering and related topics, with its computer science department being ranked highly nationally and internationally. The Institute of Natural Language Processing (Institut für Maschinelle Sprachverarbeitung, IMS), which forms part of the Faculty of Computer Science and Electrical Engineering, is one of the largest academic research institutes for natural language processing in Germany. Its activities range from computational corpus linguistics to semantic processing, machine translation, psycholinguistics, and phonetics. The city of Stuttgart is the capital of the state of Baden-Württemberg in the south-west of Germany and known for its strong economy, rich culture and its location across a variety of hills, many covered in vineyards. It is a lively place with an active bar and club scene and well-serviced public transport. By train, it is well-connected to many other interesting places, for instance Munich and Cologne (~2 hours), Paris (~3.5 hours), Berlin (~5.5 hours), Strasbourg (1 hour) or Lake Constance (2 hours). [1] https://www.ims.uni-stuttgart.de/en/institute/researchgroups/tcl/ [2] https://www.ims.uni-stuttgart.de/en/research/projects/multiview/ [3] https://www.ims.uni-stuttgart.de/institut/team/Wuehrl/ [4] https://tceron.github.io/ [5]* https://oeffentlicher-dienst.info/c/t/rechner/tv-l/allg?id=tv-l&g=E_13&s=1&… [6] https://nlpado.de/~sebastian/ [7]* https://oeffentlicher-dienst.info/c/t/rechner/tv-l/allg?id=tv-l&g=E_13&s=1&… * values are approximations which may vary depending on previous work experience.

1 0

38th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2025) :Call for Special Tracks
by Announce 22 Sep '24

22 Sep '24

*** Call for Special Tracks *** 38th IEEE International Symposium on Computer-Based Medical Systems (IEEE CBMS 2025) June 18-20, 2025, Universidad Politécnica de Madrid (UPM), Madrid, Spain https://2025.cbms-conference.org Attracting a worldwide audience, CBMS is the premier conference for computer-based medical systems, and one of the main conferences within the fields of medical informatics and biomedical informatics. IEEE CBMS 2025 invites proposals for organization of special tracks that will be held in parallel with the general conference track. The themes of the special tracks should not overlap with the general conference topics and should focus on emerging research fields. All tracks are expected to enable stimulating discussions of state-of-the-art, emerging, visionary, and perhaps controversial topics. Their papers should report on significant unpublished work and must meet the same standards as main conference papers. All accepted papers will be included in the conference proceedings. We expect all accepted tracks to adhere to the conference paper submission and reviewing schedule, as outlined in the dates indicated below. Special Tracks chair(s) will be interacting with organisers of accepted workshops to ensure a high-quality workshop program. In the case of detecting several similar submissions, the CBMS 2025 organization can propose the fusion of those proposals. Special Track requirements The organizers of a special track must comply with a set of principles and obligations, listed below: • A specific webpage with information about the special track will be created by CBMS after the acceptance notification. The organizers must provide the following information to be added to such webpage: special track description, list of topics, call for papers, submission information (must be the same as CBMS 2025 regular track), special track organizers, special track program committee members, any other relevant information. • The organizers of the special track are responsible for the peer-review process within their track. They must add their own Program committee members/reviewers to the submission platform, ensure that receive all the reviews on time, check the quality of the reviews, and establish the acceptance/rejection decision. The final decision will be sent by CBMS 2025 PC Chairs. They also must pay special attention to potential conflicts of interest and ensure that all the general ethical rules of research are followed. • At least one of the organizers of the special track must register and attend to CBMS 2025 in Madrid. The organizer(s) who attend CBMS will also chair the specific session that will be assigned in the agenda to their track. • The organizers of the special track are responsible for the publicity of their track to try to win as many submissions as possible. Please bear in mind that a special track with less than 4 accepted papers could be canceled. In this case, the accepted papers will be moved to the regular track. Important Dates • Deadline for special track proposal: November 8, 2024 (AoE) • Special track notification acceptance: November 15, 2024 Submission Guidelines Each proposal must include: • Special track title • Rough estimate of the expected ST size as number of sessions (with 4-5 papers per session) • A brief biography of ST organizer(s) • List of Special Track program committee members • A draft of Special Track “Call for papers” (important dates must be the same of the main conference) • One or two appropriate journals or follow up publications: tracks are expected to organize a special issue, if planned. The proposal must be sent to info[at]cbms-conference[dot]org CBMS 2025 Special Track Chairs • Alba García Seco de Herrera • Gilberto Ochoa-Ruiz • Sharib Ali Other Information For more information, please contact info[at]cbms-conference[dot]org.

1 0

Survey on Arabic NLP Datasets
by Wajdi Zaghouani 22 Sep '24

22 Sep '24

Dear Colleagues, We are conducting a brief survey to assess the current state of Arabic NLP datasets and to explore the challenges involved in creating new ones. The survey consists of *7 short-answer questions* and should take less than 5* minutes* of your time. Your insights will be invaluable in helping to advance research and development in Arabic Natural Language Processing. Please consider participating by following this link: https://forms.gle/ukyGk9pEzegGtHW29 We truly appreciate your time and contribution to this important area of research. ---- Wajdi Zaghouani, Ph.D. Associate Professor, Communication Program Northwestern Qatar | Education City T +974 4454 5232 | M +974 3345 4992

1 0

Release: 𝐐𝐚𝐛𝐚𝐬 - 𝐚𝐧 𝐎𝐩𝐞𝐧-𝐒𝐨𝐮𝐫𝐜𝐞 𝐋𝐞𝐱𝐢𝐜𝐨𝐠𝐫𝐚𝐩𝐡𝐢𝐜 𝐃𝐚𝐭𝐚𝐛𝐚𝐬
by Mustafa Jarrar 20 Sep '24

20 Sep '24

يسرنا الاعلان عن معجم قبس الحاسوبي We are very happy to release 𝐐𝐚𝐛𝐚𝐬 - 𝐎𝐩𝐞𝐧-𝐒𝐨𝐮𝐫𝐜𝐞 𝐋𝐞𝐱𝐢𝐜𝐨𝐠𝐫𝐚𝐩𝐡𝐢𝐜 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 Qabas = 60k Lemmas + manually linked with 12 corpora (2.3 tokens) + 110 lexicons (~ 300k lemmas) Birzeit University’s SinaLab for Computational Linguistics and Artificial Intelligence <https://sina.birzeit.edu/> has officially launched Qabas <https://sina.birzeit.edu/qabas>, an open-source lexicographic database for Arabic, designed specifically for Natural Language Processing (NLP) applications. Qabas stands out by linking its lexical entries (lemmas) with lemmas from 110 different lexicons and numerous morphologically annotated corpora (around 2 million tokens), creating an extensive lexicographic graph. This project has been under development for over fourteen years. Lexicons have evolved from being primarily hard-copy resources for human use to having substantial significance in NLP applications. Although Arabic is a highly resourced language in terms of traditional lexicons, not enough attention is given to developing AI-oriented lexicographic databases. Additionally, none of the Arabic lexicons are available open-source, due to copyright restrictions imposed by their owners. As for Qabas, it is an open-source Arabic lexicon designed for NLP applications, and its novelty lies in its synthesis of many lexical resources. Each lexical entry (i.e., lemma) in Qabas is linked with equivalent lemmas in 110 other lexicons, and with 12 morphologically-annotated corpora (about 2M tokens); The philosophy of Qabas is to construct a large lexicographic data graph by linking existing Arabic lexicons and annotated corpora. Qabas stands as the largest Arabic lexicon, encompassing about 58K lemmas (45K nominal lemmas, 12.5K verbal lemmas, and 500 function word lemmas). Prof. Mustafa Jarrar, the project’s manager and main author, emphasized the importance of making Qabas freely available as an open-source resource, allowing everyone to access and use it for both commercial and non-commercial purposes. Prof. Jarrar hopes that researchers, companies, and software developers will leverage the lexicon’s data to develop innovative content and applications that benefit humanity. Prof. Talal Shahwan, President of Birzeit University, stated that despite the challenging conditions in Palestine, the university remains committed to excellence and to its mission towards knowledge. He emphasized that this achievement was made possible by the dedication of the university’s faculty and researchers. Qabas is publicly available online at: https://sina.birzeit.edu/qabas To download Qabas and find out more, see: https://sina.birzeit.edu/qabas/about Article: https://www.jarrar.info/publications/JH24.pdf We’d love your feedback: Facebook: https://www.facebook.com/watch?v=880418097306662 LinkedIn: https://www.facebook.com/watch?v=880418097306662 Best --Mustafa __________________________ Mustafa Jarrar, PhD Professor of Artificial Intelligence Chair, PhD Program in Computer Science Birzeit University, Palestine Page: http://www.jarrar.info <http://www.jarrar.info/> SinaLab: https://sina.birzeit.edu <https://sina.birzeit.edu/>

1 0

Call for Doctoral Consortium Papers : FIRE 2024
by Bhargav Dave 19 Sep '24

19 Sep '24

Apologies for the multiple postings. ------------------------------------- *Call for Doctoral Consortium Papers* *FIRE 2024: 16th meeting of the Forum for Information Retrieval Evaluation* 12th - 15th December 2024 DA-IICT, Gandhinagar, India Submission Deadline: 2nd October 2024 (Extended) Website: fire.irsi.org.in Submission Link : https://cmt3.research.microsoft.com/FIRE2024 ------------------------------ *The goals of the symposium are to: * - provide the participants with an independent and constructive assessment of their current research and possible future research scopes; - develop a supportive community of scholars and a spirit of collaborative research; - provide a platform for the doctoral participants to share and discuss their ideas with distinguished researchers from their domain; and support the participants further with an individual mentorship session with a distinguished researcher. *Who should participate? * Students should consider participating in the Doctoral Consortium if they are at least twelve months away from completing their dissertation at the time of the event, but after having settled on a research area or thesis topic. In the area of research which largely covers AI / ML, and information science-related, we do not have any fixed set of research areas for the DC. However, it would be desirable to have information retrieval as a paradigm in your research that can be in any domain like software engineering, machine translation and image processing, etc. *Submission* Submissions can be based on early ideas or results (communicated elsewhere) for further feedback, or well-rounded study, results, and analysis, on approach to convert PhD work into a product, and the like. The paper should be 4 pages long (including references) and may contain the following aspects: - the problem to be solved in the research; a justification of why the problem is important; a summary of the previous research and related work has not yet solved that problem, - the expected contributions of the research, - how the student aims to evaluate and analyze the results; acceptable evidence of the results to the community, - an outline and characterization of the results achieved so far, and - the planned timeline for completion. Students, whose submissions are accepted, will be invited to present a poster at the consortium. They will also need to give a short talk at the consortium. Paper submission link: https://cmt3.research.microsoft.com/FIRE2024 *Format* The submitted papers must follow follow LNCS (Springer conference) template available on https://www.overleaf.com/latex/templates/springer-lecture-notes-in-computer…. The only accepted format of submissions is PDF. Papers which do not conform to the requirements may get rejected without review. Please note that it is the responsibility of the authors to ensure that the PDF submission has been uploaded successfully (we suggest that you try downloading your paper again yourself, to check). Authors are invited to submit in any of the following tracks: Paper Length: 4 page single column The author names and affiliations of the PhD Student or supervisors should be included in the paper during submission. The first author of the paper should be the PhD Student. *Review Process* Submissions will be reviewed by members of the Doctoral Symposium Committee. Participants will be selected on the basis of their anticipated contribution to the Doctoral Consortium goals as well as the potential benefit to the participants. Among the criteria that will be considered in reviewing submissions are: - the potential quality of the anticipated contributions - the stage of the research; - the diversity of backgrounds, research topics, and approaches. An additional review would be done to assess if the participants are eligible for the PhD clinic, where potential research work can be reviewed and discussed individually by a distinguished researcher. *Consortium and PhD Clinic* Authors of submissions selected for participation will have the opportunity to present their work during the Doctoral Consortium and to have a camera-ready version of their papers published in a companion volume to the FIRE 2024 Conference Proceedings. The presentation is expected to be delivered in person, unless this is impossible due to travel limitations (related to, e.g., health or visa). Selected participants will be also be eligible for the PhD clinic wherein they will be assigned to a distinguished researcher who will conduct an individual mentoring session with the participants. This session can be constructively used by the participants to discuss their ideas, get more insights and feedback and also directions forfuture work. *Important dates* *25th July 2024* DC Paper submission link <https://cmt3.research.microsoft.com/FIRE2024> will be available * 20th September 2024 2nd October 2024 * Paper submission deadline *30th October 2024 * Paper acceptance notification *10th November 2024 * Camera ready copy submission deadline *12th-15th December 2023* In-person conference Note: All submission deadlines are 11:59 PM AoE Time Zone (Anywhere on Earth). *Presentation Requirements* If accepted, at least one author will have to register for the conference and present their work in-person. *Doctoral Consortium Co-ordinator * - Soumen Paul ( IIT Kharagpur, India) - Srijoni Majumdar, University of Leeds, UK For queries related to conference please email us at [ clia(a)isical.ac.in ] For latest updates subscribe the FIRE mailing List [ https://groups.google.com/forum/#!forum/fire-list ]

1 0

Call for Participations: Regulations Challenge at FinNLP-FNP-LLMFinLegal Workshop @ COLING 2025
by jimin.huang＠thefin.ai 19 Sep '24

19 Sep '24

Dear all, The Regulations Challenge aims to push the boundaries of LLMs in understanding, interpreting, and applying regulatory knowledge in the finance industry. In this challenge, participants will participate in 9 tasks to explore key issues, including, but not limited to, regulatory complexity, ethical considerations, domain-specific terminology, industry standards, and interpretability. We welcome students, researchers, and practitioners who are passionate about finance and LLMs. We encourage participants to develop solutions that advance the capabilities of LLMs in addressing the challenges of financial regulations and industry standards. These tasks assess the LLM's ability to handle different types of questions within the regulatory domain which follow: - Abbreviation Recognition Task: Goal: Match an abbreviation with its expanded form. Input Template: "Expand the following acronym into its full form: {acronym}. Answer:" - Definition Recognition Task: Goal: Correctly define a regulatory term or phrase. Input Template: "Define the following term: {regulatory term or phrase}. Answer:" - Named Entity Recognition (NER) Task: Goal: Ensure the output correctly identifies entities and places them into groups that the user specifies. Input Template: "Given the following text, only list the following for each: specific Organizations, Legislations, Dates, Monetary Values, and Statistics: {input text}." - Question Answering Task: Goal: Ensure the output matches the correct answer to a detailed question about regulatory practices or laws. Input Template: "Provide a concise answer to the following question: {detailed question}? Answer:" - Link Retrieval Task: Goal: Ensure the link output matches the actual law. Input Template: "Provide a link for ____ law, Write in the format of ("{Law}: {Link}" or "{Law}: Not able to find a link for the law")" - Certificate Question Task: Goal: Select the correct answer choice to a question that may be based on additional context. Input Template: "(This context is used for the question that follows: {context}). Please answer the following question with only the letter and associated description of the correct answer choice: {question and answer choices}. Answer:" - XBRL Analytics Task: Goal: Ensure the output strictly matches the correct answer to a detailed question about financial data extraction and application tasks via XBRL filings. These standardized digital documents contain detailed financial information. Input Template: "Provide the exact answer to the following question: {detailed question}? Answer:" - Common Domain Model (CDM) Task: Goal: Deliver precise responses to questions about the Fintech Open Source Foundation's (FINOS) Common Domain Model (CDM). Input Template: "Provide a concise answer to the following question related to Financial Industry Operating Network's (FINO) Common Domain Model (CDM): {detailed question}? Answer:" - Model Openness Framework (MOF) Licenses Task: Goal: Deliver precise responses to questions concerning the requirement of license under the Model Openness Framework. Input Template: "Provide a concise answer to the following question about MOF's licensing requirements: {detailed question}? Answer:" The final score is determined by the weighted average of metrics for 9 tasks. We assign the weight of 10% to Task 1-5 each, 20% to Task 6, and 10% to Task 7-8 each. Important Dates Training Set Release: September 15, 2024 Training Data Details: Summary of Question Dataset Validation Set Release: October 30, 2024 Systems Submission: November 7, 2024 Release of Results: November 12, 2024 Paper Submission Deadline: November 25, 2024 Notification of Acceptance: December 5, 2024 Camera-ready Paper Deadline: December 13, 2024 Workshop Date: January 19-20, 2025 Task Organizers Keyi Wang, Columbia University, Northwestern University Lihang (Charlie) Shen, Columbia University Haoqiang Kang, Columbia University Xingjian Zhao, Rensselaer Polytechnic Institute Namir Xia, Rensselaer Polytechnic Institute Christopher Poon, Rensselaer Polytechnic Institute Jaisal Patel, Rensselaer Polytechnic Institute Andy Zhu, Rensselaer Polytechnic Institute Shengyuan Lin, Rensselaer Polytechnic Institute Daniel Kim, Rensselaer Polytechnic Institute Jaswanth Duddu, Rensselaer Polytechnic Institute Matthew Tavares, Rensselaer Polytechnic Institute Shanshan Yang, Stevens Institute of Technology Sai Gonigeni, Stevens Institute of Technology Kayli Gregory, Stevens Institute of Technology Katie Ng, Stevens Institute of Technology Andrew Thomas, Stevens Institute of Technology Dong Li, FinAI Supervisors Yanglet Xiao-Yang Liu, Rensselaer Polytechnic Institute, Columbia University Steve Yang, School of Business at Stevens Institute of Technology Kairong Xiao, Roger F. Murray Associate Professor of Business at Columbia Business School Matt White, Executive Director, PyTorch Foundation. GM of AI, Linux Foundation Cailean Osborne, University of Oxford Wes Turner, Rensselaer Center for Open Source (RCOS), Rensselaer Polytechnic Institute Neha Keshan, Rensselaer Polytechnic Institute Luca Borella, PM of AI Strategic Initiative, FINOS Ambassador, Linux Foundation Karl Moll, Technical Project Advocate, FINOS, Linux Foundation For more details, please visit https://coling2025regulations.thefin.ai/ or contact colingregchallenge2025(a)gmail.com Best regards, Jimin Huang The Fin AI (https://thefin.ai)

1 0

Financial Misinformation Detection Challenge: Training Datasets Release and Call for Participations
by jimin.huang＠thefin.ai 19 Sep '24

19 Sep '24

Dear All, We're excited to announce that we've just released all training datasets for Financial Misinformation Detection Challenge at FinNLP-FNP-LLMFinLegal Workshop @ COLING 2025, giving participants the resources needed to start building powerful models. This is your chance to explore, innovate, and contribute to the world of financial large language models. This task tests the ability of LLM to verify financial misinformation while generating plausible explanations. Participants need to develop or adapt LLMs to identify financial claims (True'/'False'/'Not Enough Information') and give explanations for their decision according to the related information, following the designed prompt template of the query. For more details: Contest Website: https://coling2025fmd.thefin.ai/ Team Registration: https://forms.gle/vh9MSQa31HwrS7Xm9 Shared Task Organizers: Zhiwei Liu - University of Manchester, UK Keyi Wang - Columbia University, Northwestern University, USA Zhuo Bao - Internet Domain Name System Beijing Engineering Research Center Co, China Xin Zhang - University of Manchester, UK Jiping Dong - University of Chinese Academy of Sciences, China Boyang Gu - Imperial College London, UK Kailai Yang - University of Manchester, UK Dong Li - FinAI, Singapore Sophia Ananiadou - University of Manchester, UK; Archimedes RC, Greece Important Dates: Schedule: from Aug 15 to Dec 13, 2024 Solution submission deadline: Nov 7, 2024 Paper submission deadline: Nov 25, 2024 Notifications of Acceptance: Dec 5, 2024 Camera-ready Paper Deadline: Dec 13, 2024 We look forward to your participation and your brilliant contributions to this event. Best regards, Jimin Huang The Fin AI (https://thefin.ai)

1 0

SemEval 2025: Multilingual News Narrative Analysis Task
by ion＠aueb.gr 19 Sep '24

19 Sep '24

First call for participation in the SemEval 2025 shared task: Multilingual Characterization and Extraction of Narratives from Online News. This task challenges participants to analyze news articles and automatically identify narratives, classify them, and determine the roles played by relevant entities. The task is multilingual, covering five languages: Bulgarian, English, Hindi, Portuguese, and Russian. Participants can choose to participate in one or more of the following subtasks: - Subtask 1: Entity Framing – Classify the roles of named entities within news articles. - Subtask 2: Narrative Classification – Classify each article based on all the (sub)narratives given a specific domain. - Subtask 3: Narrative Extraction – Generate short textual explanations for dominant narratives in the articles. The task covers news articles from two domains, namely, Ukraine-Russia War and Climate Change. Important Dates: - 31 January 2025: Test submission deadline - 28 February 2025: System paper submission deadline - 31 March 2025: Notification to authors - 21 April 2025: Camera-ready papers due - Summer 2025: SemEval workshop For more details, visit https://propaganda.math.unipd.it/semeval2025task10/ or contact us at semeval2025narratives-task-participants(a)googlegroups.com. We look forward to your participation and to advancing the state of multilingual news narrative analysis together! -- Ion Androutsopoulos (http://www.aueb.gr/users/ion/) Professor of AI, Head of Department, Information Processing Lab Director, NLP Group Co-director Department of Informatics, Athens University of Economics and Business and Adjunct Researcher, "Archimedes" Research Unit, Research Center "Athena"

1 0

2026

2025

2024

2023

2022

Corpora