- Corpora - ELRA lists

[NTCIR-18] Final Call for Participation
by CHUNG-CHI CHEN 28 Mar '24

28 Mar '24

Dear colleagues, We are glad to share the information of NTCIR-18 with you. This year, we have 9 interesting tasks, that cover the (1) Modern IR Tasks, (2) Access to Non-Digitized Archive Material, (3) Large Language Model Evaluation, and (4) NLP Tasks in Financial and Medical Domains. We will have a kickoff event within 24 hours. The task organizers will introduce their tasks. Below are more details, and please register for the kickoff event. We will send a Zoom link to you soon. Feel free to let us know if you have any questions. Best Regards, Qingyao Ai, Chung-Chi Chen, Shoko Wakamiya NTCIR-18 Program Co-Chairs *Kick-Off Event* - Date/Time: March 29th (Friday) 2024, From 16:00 To 17:30 p.m. - Onsite: Room 1902-1903, National Institute of Informatics - Online: Zoom (The link will be available for participants before the event.) - Fees: Free - Registration: https://docs.google.com/forms/d/e/1FAIpQLScumfe8q3HDe2Vul2RUhTxNacSt9KujvqM… - Zoom link will be sent to the registered email address before the event. - For more details, please refer to our site: https://research.nii.ac.jp/ntcir/ntcir-18/kickoffcfp.html *Kick-Off Event Tentative Program* - Overview of NTCIR - Overview of NTCIR-18 - Introduction of each task - How to participate in NTCIR-18 - Q & A *NTCIR-18 Tasks* *CORE TASKS* 1. AEOLLM: Automatic Evaluation of LLMs 2. FairWeb-2: The Second Fair Web Task 3. FinArg-2: Temporal Inference of Financial Arguments 4. MedNLP-Rad: Medical Natural Language Processing for Radiology 5. MedNLP-CHAT: Medical Natural Language Processing for AI Chat 6. Transfer-2: The Resource Transfer Based Dense Retrieval Task *PILOT TASKS* 1. HIDDEN-RAD: Hidden Causality Inclusion in Radiography Report Generation 2. SUSHI: Searching Unseen Sources for Historical Information 3. UFO 2.0: Understanding of Non-Financial Objects in Financial Reports

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CFP - SIGIR 2024 Workshop on eCommerce
by Surya Kallumadi 28 Mar '24

28 Mar '24

Call For Papers - SIGIR eCom'24 - https://sigir-ecom.github.io/ The SIGIR Workshop on eCommerce will serve as a platform for publication and discussion of Information Retrieval, NLP and Vision research relative to their applications in the domain of eCommerce. This workshop will bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to product search and recommendation in eCommerce. The deadline for paper submission is April 25, 2024 (11:59 P.M. AoE) The special theme of this year's workshop is eCommerce Search in the Age of Generative AI and LLMs. The workshop will also include a data challenge. This year we will collaborate with TREC on a product search data challenge ( https://trec-product-search.github.io/index.html). The overarching goal is to study how end-to-end retrieval systems can be built and evaluated given a large set of products. The data challenge provides a corpus of products and a set of user intents (queries): the goal is to find the product that suits the user’s needs. SIGIR eCom is a full day workshop taking place on Thursday, July 18, 2024 in conjunction with SIGIR 2024. SIGIR eCom'24 will be an in-person workshop. ________________ Important Dates: Paper submission deadline - April 25, 2024 (11:59 P.M. AoE) Notification of acceptance - May 23, 2024 Camera Ready Version of Papers Due - June 24, 2024 SIGIR eCom Full day Workshop - July 18, 2024 We invite quality research contributions, position and opinion papers addressing relevant challenges in the domain of eCommerce. We invite submission of both papers and posters. All submitted papers and posters will be single-blind and will be peer reviewed by an international program committee of researchers of high repute. Accepted submissions will be presented at the workshop. Topics: Topics of interest include, but are not limited to: - eCommerce search in the age of Generative AI and LLMs (2024 special theme) - Ranking and Whole Page Relevance - Optimization for IR and business metrics - Diversity in product search and recommendations - Relevance models for multi-faceted entities - Relevance vs. revenue - Deterministic sorts (e.g. price low to high) - Temporal dynamics and seasonality - Query and Document Understanding - Query intent, query suggestions, and auto-completion - Strategies for resolving low or zero recall queries - Converting across modalities (e.g., text, structured data, images) - Categorization and facets - Reviews and sentiment analysis - Recommendation and Personalization - Personalization & contextualization, including the use of personal facets such as age, gender, location - Privacy, bias and ethics in eCommerce IR - Blending recommendations and search results - Representations and Data - Semantic representation of products, queries, and customers - Construction and use of knowledge graphs for eCommerce - IR Fundamentals for eCommerce - Unified and universal search and recommendations - Cross-lingual search and machine translation - Indexing and search in rapidly changing environments (e.g., auction sites) - Experimentation techniques including AB testing and multi-armed bandits - Visual Search in ecommerce - Large-scale Visual Search Challenges and Solutions - Multimodal Search and combining visual and textual information - Combining Vision and language models - Explainable AI for Visual Search - Other challenges - Trust, transparency, and fairness in eCommerce - UX for eCommerce - The role of search in trust and security for marketplaces - Question answering and chatbots for eCommerce Data/Resource Track: In order to promote academic research in the eCommerce domain, we plan to accept a small number of high quality dataset contributions. These submissions should be accompanied by a clear and detailed description of the dataset, some potential questions and applications that arise from it. Preliminary empirical investigations conveying any insight about the data will increase the quality of the submission. Submission Instructions: All papers will be peer reviewed (single-blind) by the program committee and judged by their relevance to the workshop, especially to the main themes identified above, and their potential to generate discussion. Submissions must describe work that is not previously published, not accepted for publication elsewhere, and not currently under review elsewhere. All submissions must be in English. The workshop follows a single-blind reviewing process, i.e. author names must be on the papers. We do not accept anonymized submissions. At least one of the authors of each accepted paper must register for the workshop and present the paper. All submissions must be in PDF formatted according to the latest CEUR single column format; the short (8-page) and long (15-page) limits are extended to account for this. For instructions and LaTeX/Overleaf/docx templates, see: https://ceur-ws.org/HOWTOSUBMIT.html#CEURART Read up to and including the “License footnote in paper PDFs” section. Please Use Emphasizing Capitalized Style for Paper Titles. Submit your paper PDF through the SIGIR eCom’24 Easychair: https://easychair.org/conferences/?conf=sigirecom24 Long paper limit: 15 pages. References are not counted in the page limit. Short paper limit: 8 pages. References are not counted in the page limit. The deadline for paper submission is April 25, 2024 (11:59 P.M. AoE) https://sigir-ecom.github.io/

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Meta KDD Cup 2024: Comprehensive RAG Challenge
by Kai Sun 28 Mar '24

28 Mar '24

Hello Colleagues, Imagine using an AI assistant to get the latest updates on your favorite sports team, but instead of receiving latest scores, you get last year’s results. Or when asking about a niche movie you really like, but couldn't get meaningful answers. These are classic examples of “hallucination” where LLMs provide outdated or incorrect information. The Meta Comprehensive RAG (CRAG) Benchmark Challenge aims to address these challenges. Participate to improve how Large Language Models (LLMs) can keep-up with the ever-evolving reality and provide accurate responses by leveraging Retrieval Augmented Generation (RAG). Why RAG Matters Despite the advancements of LLMs, the issue of hallucination persists as a significant challenge; that is, LLMs may generate answers that lack factual accuracy or grounding. Retrieval-Augmented Generation (RAG) has recently emerged as a promising solution to alleviate LLM’s deficiency in lack of knowledge and attracted a lot of attention from both academia research and industry. Introducing the Meta Comprehensive RAG (CRAG) Benchmark Challenge CRAG is a factual question answering benchmark that covers 5 domains and 8 question types, and provides a practical set-up to evaluate RAG systems. Different from existing benchmarks, CRAG is designed to include questions with a wide variety of domains and types. In particular, it includes questions with answers that change from over seconds to over years; it considers entity popularity and covers not only head, but also torso and tail facts; it contains simple-fact questions as well as 7 types of complex questions such as comparison, aggregation and set questions to test the reasoning and synthesis capabilities of RAG solutions. Why This Challenge Is a Game-Changer Addressing "hallucination" and outdated information is critical to enhancing the reliability of LLM-powered question-answering systems. RAG proposes a solution by integrating the external data into its responses. The CRAG Benchmark is a comprehensive test to evaluate these advanced systems' effectiveness across various domains and question types, challenging them with scenarios that require immediate data and those that explore less popular "tail" facts. What's unique about this challenge? * Tasks Designed to Improve QA Systems: The three tasks focus on web-based retrieval summarization, knowledge graph and web augmentation, and an end-to-end RAG challenge, each built on top of the previous one. * Rich Dataset Across Diverse Domains: The CRAG dataset covers domains from finance to music, to address questions that mirror real-world variability and complexity. * Prizes For Winners: Compete for a chance to win a part of the $31,500 prize pool, with the top performing teams in each task winning up to $4,000. Challenge Timeline * Website Online and Registration Begin: 20th March, 2024 23:55 UTC * Phase 1 Start Date: 1st April, 2024 23:55 UTC * Phase 1 End Date: 20th May, 2024 23:55 UTC * Phase 2 Start Date: 22nd May, 2023 23:55 UTC * Registration and Team Freeze Deadline: 31st May, 2024 23:55 UTC * Phase 2 End Date: 20th Jun, 2023 23:55 UTC * Winner Notification: 15th July, 2024 * Winner Announcement: 26th August, 2024 (KDD Cup Winners) 👉 Engage Now: Begin this journey by delving into the challenge details at https://www.aicrowd.com/challenges/meta-comprehensive-rag-benchmark-kdd-cup…. Join a community of innovative thinkers, share ideas, and engage in this exciting challenge. Connect with us on our Community Forum and Discord Server for support and collaboration. We're eager to see the innovations you'll bring to life. Refer to: https://www.aicrowd.com/challenges/meta-comprehensive-rag-benchmark-kdd-cup… for the competition rules. All the best, Team AIcrowd *NO PURCHASE NECESSARY TO ENTER/WIN. Open to individuals who are 18 + age of majority and meet the full eligibility requirements in the full Rules. Open 3/20/2024 10:00:01 AM thru 6/15/2024 23:59:59 PM PT. Void where prohibited. Subject to full Rules at https://www.aicrowd.com/challenges/meta-comprehensive-rag-benchmark-kdd-cup…. See Rules for prize details and values. Sponsor: Meta Platforms, Inc. 1 Hacker Way, Menlo Park, California 94025 (for US entrants) or Meta Ireland Limited, 4 Grand Canal Square, Dublin 2, Ireland (for all other entrants).

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Invitation: Guest Speaker @ ACFTI Cybersecurity stream
by Andrew Zayine 27 Mar '24

27 Mar '24

The Association of Cyber Forensics and Threat Investigators (ACFTI) is an ambitious, non-profit technical organization focusing on the academics and practitioners of cybersecurity, digital forensics, incident response, and threat investigations and their influence on society. Our main aim is to inspire the next generation of underrepresented groups to flourish by creating a learning community of students, professors, and industry professionals. It connects future cybersecurity practitioners on campus with leading professionals On behalf of the Association of Cyber Forensics and Threat Investigators (ACFTI), I am pleased to invite you to the new DFIR stream lecture/seminar series. The presentation is a maximum of 1 hour in length, with an audience of about 60+, made up of researchers, practitioners, and cybersecurity students from underrepresented groups. Our goal is to shine a spotlight on the broad array of new advances in cybersecurity science and operations currently adopted in the industry. This session will be conducted online. It will be fantastic to have any hands-on topics related to cyber forensics and/or Cybercrime Your discussion on this topic will be a great addition to our event. Expressions of interest to present from anyone doing research or applying cybersecurity techniques to practical or theoretical applications related to the interactions between cyber forensics and threat investigations can be sent as a summary of your work (c.300 words) to https://dfir.stream/call-for-guest-speakers Thank you in advance for your consideration, and we are very much looking forward to hearing from you. To get more news about our events, please join our low-traffic announcement group @ https://groups.google.com/g/acfti Best regards, Andrew Zayin Ph.D., CISSP, CISM, CRISC, CDPSE, PMP ACFTI Secretariat ________________________________________________________ Association of Cyber Forensics and Threat Investigators https://www.acfti.org Twitter: @acfti

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Second Call for Participation - HOPE@IberLEF 2024: Approaching Hope Speech Detection in Social Media from Two Perspectives, for Equality, Diversity and Inclusion and as Expectations
by Sabur B 27 Mar '24

27 Mar '24

****We apologize for multiple postings of this e-mail**** IberLEF 2024 Task - HOPE: Approaching Hope Speech Detection in Social Media from Two Perspectives, for Equality, Diversity and Inclusion and as Expectations Held as part of the evaluation forum IberLEF 2024 <https://sites.google.com/view/iberlef-2024/home?authuser=0> in the 40th edition of the International Conference of the Spanish Society for Natural Language Processing (SEPLN 2024 <http://sepln2024.infor.uva.es/en/front-page-english/>) Valladolid, Spain, 24-27 September 2024 Codalab link: https://codalab.lisn.upsaclay.fr/competitions/17714 Dear All, Hope, a crucial aspect of human psychology, profoundly shapes emotions, behavior, and mood, influencing how individuals perceive and navigate challenges (Bruininks and Malle, 2005; Snyder, 1994, 2000). High levels of hope correlate with positive outcomes such as academic success and lower depression rates, while low hope is associated with diminished well-being (Snyder, 2002; Snyder et al., 1997; Diener, 2009). Despite its significance, hope has been underexplored in Natural Language Processing (NLP) until recent years. Efforts have been made to integrate NLP techniques into the analysis of hope through shared tasks, like those organized in ACL 2022, RANLP 2023, and IberLEF 2023 (Chakravarthi et al., 2022; Kumaresan et al., 2023; Jiménez-Zafra et al., 2023). The upcoming IberLEF 2024 edition aims to delve deeper into hope from two angles: hope for equality, diversity, and inclusion, and hope as expectations. This edition promises to expand understanding by examining hope across different domains and languages, thus addressing crucial questions in hope speech detection research. Two tasks are outlined in this description, each focusing on different aspects of hope. - Task 1: It centers on "Hope for Equality, Diversity, and Inclusion," emphasizing the importance of hope speech in mitigating hostility and supporting individuals facing challenges like illness, stress, or loneliness, particularly within vulnerable groups such as the LGBT community and racial minorities. This task consists of giving a Spanish tweet, identifying whether it contains hope speech or not. The possible categories for each text are: - hs: hope speech. - nhs: non hope speech. - Task 2: It delves into "Hope as Expectations," highlighting hope's role as an anticipatory mindset shaping human emotions and behaviors, especially in the context of social media where expressions are abundant. This task aims to analyze hope speech's presence in English and Spanish texts, focusing on binary hope speech detection and multiclass hope speech detection. The subtask are presented as follows, - Subtask 2a- Binary Hope speech detection: A given text in English/Spanish will be classified as: - Hope - Not Hope - Subtask 2b- Multiclass Hope speech detection: A given text in English/Spanish will be classified as: - Generalized Hope - Realistic Hope - Unrealistic Hope - Not Hope In both tasks, there will be a real-time leaderboard and the participants will be allowed to make a maximum of 10 submissions through CodaLab, from which each team will have to select the best one for ranking. The dataset details and registration are available at: https://codalab.lisn.upsaclay.fr/competitions/17714 Best regards, The HOPE 2024 organizing committee Important dates - Release of training + development corpora: Feb 16, 2024. - Release of test corpora and start of evaluation campaign: April 1, 2024. - End of evaluation campaign (deadline for runs submission): Apr 16, 2024. - Publication of official results: Apr 18, 2024. - Paper submission: May 14, 2024. - Review notification: Jun 11, 2024. - Camera-ready submission: Jun 28, 2024. - IberLEF Workshop (SEPLN 2024): Sep 27, 2024. - Publication of proceedings: Sep ??, 2024. Organizing Committee - Daniel García-Baena, SINAI, Universidad de Jaén, Spain. - Fazlourrahman Balouchzahi, CIC IPN, Mexico. - Salud María Jiménez-Zafra, SINAI, Universidad de Jaén, Spain. - Sabur Butt, Institute for the Future of Education (IFE) at Tecnológico de Monterrey, Mexico. - Miguel Ángel García-Cumbreras, SINAI, Universidad de Jaén, Spain. - Atnafu Lambebo Tonja, Centro de Investigación en Computación, Instituto Politécnico Nacional (IPN), Mexico. - José Antonio García-Díaz, UMUTeam, Universidad de Murcia, Spain. - Selen Bozkurt, Department of Biomedical Informatics, School of Medicine, Emory University. - Bharathi Raja Chakravarthi, University of Galway, Ireland. - Hector G. Ceballos, Institute for the Future of Education (IFE) at Tecnologico de Monterrey, Mexico. - Rafael Valencia-García, UMUTeam, Universidad de Murcia, Spain. - Grigori Sidorov, CIC IPN, Mexico. - L. Alfonso Ureña-López, SINAI, Universidad de Jaén, Spain. - Alexander Gelbukh, CIC IPN, Mexico. *Sabur Butt, Ph.D. *(He/Him) Institute for the Future of Education (IFE) *Tecnológico de Monterrey, Mexico* Address: Av. Eugenio Garza Sada 2501 Sur Tecnológico, 64849 Monterrey, N.L. LinkedIn <https://www.linkedin.com/in/saburb> - GitHub <https://github.com/saburbutt> - Scholar <https://scholar.google.com/citations?user=re7md-0AAAAJ&hl=en> - Website <https://saburbutt.github.io/>

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GEM'24 shared task: Final call for participation
by Simon Mille 27 Mar '24

27 Mar '24

Dear colleagues, The deadline for the GEM shared task submissions on multilingual data-to-text generation and summarization is now less than 10 days away! Note that you can pre-register your systems until the submission date (April 5th). More information on the GEM website <https://gem-benchmark.com/shared_task>. Regards, simon, on behalf of the GEM human evaluation team *ADAPT Research Centre / Ionaid Taighde ADAPT* *School of Computing, Dublin City University, Glasnevin Campus / Scoil na Ríomhaireachta, Campas Ghlas Naíon, Ollscoil Chathair Bhaile Átha Cliath*

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KONVENS 2024: Second Call for Papers
by Benjamin Roth 27 Mar '24

27 Mar '24

KONVENS 2024: Second Call for Papers We warmly welcome the submission of papers for KONVENS 2024, scheduled from September 9 to 13, 2024, at the University of Vienna, Austria. In addition to its technical program, KONVENS will facilitate dynamic interactions among academic researchers and industry peers, offering workshops, tutorials, shared tasks, and networking events. Confirmed keynote: Jana Diesner (TU München) See https://konvens-2024.univie.ac.at/ for more information! PAPER SUBMISSION INFORMATION We invite submissions of original and unpublished works in the fields of research, development, applications, and evaluation, encompassing all aspects of natural language processing, from fundamental inquiries to the practical implementation of natural language resources, components, and systems. We particularly encourage submissions of NLP approaches dedicated to the German language, including survey papers that provide insights into the current state of the art in German language and speech processing. We welcome contributions from both academic and industry professionals. We welcome the following types of paper submissions: * Long papers (8 pages plus references and appendix), describing original research with substantial new results. * Short papers (4 pages plus references and appendix), including small focused contributions, work in progress, as well as descriptions of projects, systems and resources. * Long and short papers can be submitted for archival publication, published in the ACL Anthology, and there is the option of non-archival submission. In the case of non-archival submission, only the abstract of the paper (max. 200 words) will be published on our website and the paper will not be part of the conference proceedings. Accepted papers will be presented orally or as posters as determined by the program chairs. The decisions will be based on the nature rather than the quality of the work. The conference language is English. Only contributions written in English will be accepted. Each submission must include a mandatory discussion of Ethical Considerations as well as a section on Limitations (both sections do not count towards the page limit). Papers without these sections will be desk-rejected. The review process will be double-blind. Submissions must be anonymized accordingly. The conference proceedings will be published via the ACL Anthology (archival submissions only). Papers must be formatted in accordance with the ACL style sheet: https://github.com/acl-org/acl-style-files. We strongly encourage authors to use LaTeX in preparing their document. Papers must be submitted electronically via OpenReview: https://openreview.net/group?id=KONVENS/2024/Conference IMPORTANT DATES * April 30th, 2024: Paper submission due (all submission types) * June 30th, 2024: Notification of acceptance * July 15th, 2024: Camera-ready papers due * September, 9th-13th, 2024: KONVENS CONFERENCE STIPEND GSCL is offering stipends for students in the field of computational linguistics (including PhD students) covering conference fees and (partially) travel costs for attending KONVENS 2024. For more information, see: https://gscl.org/activities/conference-stipend/ Mit freundlichen Grüßen / Best regards the KONVENS-2024 organization team konvens-2024(a)googlegroups.com https://konvens-2024.univie.ac.at/ -- Univ.-Prof. Dr. Benjamin Roth Digitale Textwissenschaften Universität Wien Kolingasse 14 Raum 5.17 1090 Wien email: benjamin.roth(a)univie.ac.at tel: +43 14277 79513 virtual coffee (Tuesday 2pm CEST): https://www.benjaminroth.net/virtual_coffee video call: https://univienna.zoom.us/j/93796507934?pwd=VFg5dW9JbStPUml6WFVtOWJXV3phQT09 web: https://dm.cs.univie.ac.at/team/person/112089/

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CfP: 4th Workshop on Computational Linguistics for Political and Social Sciences (CPSS 2024)
by Indira Sen 27 Mar '24

27 Mar '24

[Apologies for cross-posting] Dear Corpora list members, We welcome submissions for the *4th edition of the CPSS workshop, co-located with KONVENS'24, in Vienna, Austria on 13th September 2024.* Keeping with the theme of text-as-data and NLP techniques for studying political and social phenomena, you can submit both archival papers (short or long) or non-archival abstracts. Closely related themes include (but are not limited to): - Modeling political communication with NLP (e.g. topic classification, position measurement) - Mining policy debates from heterogeneous textual sources - Modeling complex social constructs (e.g. populism, polarization, identity) with NLP methods - Political and social bias in language models - ... and more! *Important Dates* - Submission deadline: 14 June 2024 - Notification of acceptance: 2 August 2024 - Camera ready deadline: 12 August 2024 - Workshop: 13 September 2024 Papers can be submitted through Easychair via https://easychair.org/conferences/?conf=cpss2024 More details: https://sites.google.com/view/cpss2024konvens/home-page Best, CPSS'24 organizers (Christopher Klamm, Gabriella Lapesa, Simone Paolo Ponzetto, Ines Rehbein, Indira Sen)

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[2nd call] PhD and postdoc positions on Natural Language Understanding at Pioneer Centre for AI
by Isabelle Augenstein 27 Mar '24

27 Mar '24

A PhD and two postdoc positions on natural language understanding are now available at the Pioneer Centre for AI<https://www.aicentre.dk/>. You can read more about the positions here<https://www.aicentre.dk/jobs>. PhD Fellowship on Factual Text Generation While recent large language models demonstrate surprising fluency and predictive capabilities in their generated text, they have been demonstrated to generate factual inaccuracies even when they have encoded truthful information. This limits their utility and safety in real world scenarios where guarantees of factuality are needed. To address this, the project will explore methods for improving the factuality of text generation with respect to both objective real-world facts and provided source documents. We are looking for candidates with a background in computer science, machine learning, natural language processing, computational social science, or similar. The candidate should have an interest in automatic text generation and fact checking. They should also have an interest in interdisciplinary research endeavors, including at the Pioneer Center for AI. Early research experience, especially with empirical research methods, or relevant industry experience, will be a bonus. The principal supervisor is Professor Isabelle Augenstein<mailto:augenstein@di.ku.dk> and the co-supervisor is Dustin Wright<mailto:dw@di.ku.dk>. Application deadline: 1 April 2024. Apply here<https://candidate.hr-manager.net/ApplicationInit.aspx/?cid=1307&departmentI…>. Postdoctoral Fellowship on NLP for Computational Social Science The Pioneer Centre for AI and Department of Computer Science at the University of Copenhagen invite applications for a 2-year postdoctoral full-time research position in the domain of Natural Language Processing. NLP is becoming an increasingly powerful tool for social scientists. Yet, the intersection between the two disciplines is still poorly explored, with research in the two disciplines often being conducted as separate streams. The goal of this project is to research methods which can more directly be useful for downstream social science applications. One such application is to analyse common narratives in news, which requires methods including (interpretable) topic modelling, framing detection, social media analysis, etc. The successful candidate will be affiliated with a larger initiative on narrative analysis, spanning different content modalities, with the autonomy to define their project in this larger context. The research will be conducted in collaboration with researchers at the Pioneer Centre for Artificial Intelligence’s Speech and Language Collaboratory, CopeNLU<https://www.copenlu.com/> and the Belongie Lab<https://www.belongielab.org/>. Inquiries about the position can be made to Professor Isabelle Augenstein<mailto:augenstein@di.ku.dk>. Application deadline: 7 April 2024. Apply here<https://jobportal.ku.dk/videnskabelige-stillinger/?show=161353>. Postdoctoral Fellowship on Multi-Modal Fact Checking The Pioneer Centre for AI and Department of Computer Science at the University of Copenhagen invite applications for a 2-year postdoctoral full-time research position in the domain of Natural Language Processing. Online content can include multiple different modalities, ranging from text to images or tables. Increasingly, detecting false information requires the understanding of a combination of these modalities and the relationship between them. This project will focus on developing general-purpose multi-modal methods for automatic fact checking in various domains, such as scientific publications, news or social media. Inquiries about the position can be made to Professor Isabelle Augenstein<mailto:augenstein@di.ku.dk> or Assistant Professor Desmond Elliot<mailto:de@di.ku.dk>. Application deadline: 7 April 2024. Apply here<https://jobportal.ku.dk/videnskabelige-stillinger/?show=161352>. Isabelle Augenstein, Dr. Scient., Ph.D. Professor and Head of the NLP Section, Department of Computer Science (DIKU) Co-Lead, Pioneer Centre for Artificial Intelligence University of Copenhagen Østervold Observatory Øster Voldgade 3 1350 Copenhagen augenstein(a)di.ku.dk<mailto:augenstein@di.ku.dk> http://isabelleaugenstein.github.io/

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[CfP] DLnLD: Deep Learning and Linked Data — LREC-COLING Workshop — Last CfP
by Gilles Sérasset 26 Mar '24

26 Mar '24

DLnLD: Deep Learning and Linked Data — Last Call for Paper Workshop colocated with LREC-COLING 2024, Date: May 21, 2024 Submissions due: 9th March 2024 Venue: Torino, Italy and online For up to date info, check: https://dl-n-ld.github.io/ <https://dl-n-ld.github.io/> Call for Papers ---------------------------------------------------------------------------------------- What does Linguistic Linked Data brings to Deep Learning and vice versa ? Let’s bring together these two complementary approaches in NLP. ---------------------------------------------------------------------------------------- Motivations for the Workshop Since the appearance of transformers (Vaswani et al., 2017), Deep Learning (DL) and neural approaches have brought a huge contribution to Natural Language Processing (NLP) either with highly specialized models for specific application or via Large Language Models (LLMs) (Devlin et al., 2019; Brown et al., 2020; Touvron et al., 2023) that are efficient few-shot learners for many NLP tasks. Such models usually build on huge web-scale data (raw multilingual corpora and annotated specialized, task related, corpora) that are now widely available on the Web. This approach has clearly shown many successes, but still suffers from several weaknesses, such as the cost/impact of training on raw data, biases, hallucinations, explainability, among others (Nah et al., 2023). The Linguistic Linked Open Data (LLOD) (Chiarcos et al., 2013) community aims at creating/distributing explicitly structured data (modelled as RDF graphs) and interlinking such data across languages. This collection of datasets, gathered inside the LLOD Cloud (Chiarcos et al., 2020), contains a huge amount of multilingual ontological (e.g. DBpedia (Lehmann et al., 2015)); lexical (e.g., DBnary (Sérasset, 2015), Wordnet (McCrae et al., 2014), Wikidata (Vrandečić and Krötzsch, 2014)); or linguistic (e.g., Universal Dependencies Treebank (Nivre et al., 2020; Chiarcos et al., 2021), DBpedia Abstract Corpus (Brümmer et al., 2016)) information, structured using common metadata (e.g., OntoLex (McCrae et al., 2017), NIF (Hellmann et al., 2013), etc.) and standardised data categories (e.g., lexinfo (Cimiano et al., 2011), OliA (Chiarcos and Sukhareva, 2015)). Both communities bring striking contributions that seem to be highly complementary. However, if knowledge (ontological) graphs are now routinely used in DL, there is still very few research studying the value of Linguistic/Lexical knowledge in the context of DL. We think that, today, there is a real opportunity to bring both communities together to take the best of both worlds. Indeed, with more and more work on Graph Neural Networks (Wu et al., 2023) and Embeddings on RDF graphs (Ristoski et al., 2019), there is more and more opportunity to apply DL techniques to build, interlink or enhance Linguistic Linked Open Datasets, to borrow data from the LLOD Cloud for enhancing Neural Models on NLP tasks, or to take the best of both worlds for specific NLP use cases. Submission Topics This workshop aims at gathering researchers that work on the interaction between DL and LLOD in order to discuss what each approach has to bring to the other. For this, we welcome contributions on original work involving some of the following (non exhaustive) topics: • Deep Learning for Linguistic Linked Data, among which (but not exclusively): • Modelling, Resources & Interlinking, • Relation Extraction • Corpus annotation • Ontology localization • Knowledge/Linguistic Graphs creation or expansion • Linguistic Linked Data for Deep Learning, among which (but not exclusively): • Linguistic/Knowledge Graphs as training data • Fine tuning LLMs using Linguistic Linked (meta)Data • Graph Neural Networks • Knowledge/Linguistic Graphs embeddings • LLOD for model explainability/sourcing • Neural models for under-resourced languages • Joint Deep Learning and Linguistic Data applications • Use cases combining Language Models and Structured Linguistic Data • LLOD and DL for Digital Humanities • Question-Answering on graph data All application domains (Digital Humanities, FinTech, Education, Linguistics, Cybersecurity…) as well as approaches (NLG, NLU, Data Extraction…) are welcome, provided that the work is based on the use of BOTH Deep Learning techniques and Linguistic Linked (meta)Data. Important Dates All deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”) • Submissions due: 9th March 2024 (Hard deadline: there will be no deadline extension) • Notification of acceptance: 2nd April 2024 • Camera-ready due: 12th April 2024 Authors kit All papers must follow the LREC-COLING 2024 two-column format, using the supplied official style files. The templates can be downloaded from the Style Files and Formatting page provided on the website. Please do not modify these style files, nor should you use templates designed for other conferences. Submissions that do not conform to the required styles, including paper size, margin width, and font size restrictions, will be rejected without review. LREC-COLING 2024 Author’s Kit Page: https://lrec-coling-2024.org/authors-kit/ <https://lrec-coling-2024.org/authors-kit/> Paper submission Submission is electronic at https://softconf.com/lrec-coling2024/dlnld2024/ <https://softconf.com/lrec-coling2024/dlnld2024/> Workshop Chairs • Gilles Sérasset, Université Grenoble Alpes, France • Hugo Gonçalo Oliveira, University of Coimbra, Portugal • Giedre Valunaite Oleskeviciene, Mykolas Romeris University, Lithuania Program Committee • Mehwish Alam, Télécom Paris, Institut Polytechnique de Paris, France • Russa Biswas, Hasso Plattner Institute, Potsdam, Germany • Milana Bolatbek, Al-Farabi Kazakh National University, Kazakhstan • Michael Cochez, Vrije Universiteit Amsterdam, Netherlands • Milan Dojchinovski, Czech Technical University in Prague, Czech Republic • Basil Ell, University of Oslo, Norway • Robert Fuchs, University of Hamburg, Germany • Radovan Garabík, L’. Štúr Institute of Linguistics, Slovak Academy of Sciences, Slovakia • Daniela Gifu, Romanian Academy, Iasi branch & Alexandru Ioan Cuza University of Iasi, Romania • Katerina Gkirtzou, Athena Research Center, Maroussi, Greece • Jorge Gracia del Río, University of Zaragoza, Spain • Dagmar Gromann, University of Vienna, Austria • Dangis Gudelis, Mykolas Romeris University, Lithuania • Ilan Kernerman, Lexicala by K Dictionaries, Israel • Chaya Liebeskind, Jerusalem College of Technology, Israel • Marco C. Passarotti, Università Cattolica del Sacro Cuore, Milan, Italy • Heiko Paulheim, University of Mannheim, Germany • Alexandre Rademaker, IBM Research Brazil and EMAp/FGV, Brazil • Georg Rehm, DFKI GmbH, Berlin, Germany • Harald Sack, Karlsruhe Institute of Technology, Karlsruhe, Germany • Didier Schwab, Université Grenoble Alpes, France • Ranka Stanković, University of Belgrade, Serbia • Andon Tchechmedjiev, IMT Mines Alès, France • Dimitar Trajanov, Ss. Cyril and Methodius University – Skopje, Macedonia • Ciprian-Octavian Truică, POLITEHNICA Bucharest, Romania • Nicolas Turenne, Guangdong University of Foreign Studies, China • Slavko Žitnik, University of Ljubljana, Slovenia

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