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LREC 2026 First Call for Papers
by info＠elda.org 19 Jun '25

19 Jun '25

[Apologies for cross-postings] FIRST CALL FOR PAPERS LREC 2026 Organised by the ELRA Language Resources Association Palma, Mallorca, Spain 11-16 May 2026 The Fifteenth biennial Language Resources and Evaluation Conference (LREC) will be held at the Palau de Congressos de Palma in Palma, Mallorca, Spain, on 11-16 May 2026. LREC serves as the primary forum for presentations describing the development, dissemination, and use of language resources involving both traditional and recently developed approaches. The scientific program will include invited talks, oral presentations, and poster and demo presentations, as well as a keynote address by the winner of the Antonio Zampolli Prize. Submissions describing all aspects of language resource development and use are invited, including, but not limited to, the following: Language Resource Development Methods and tools for mono- and multi-lingual language resource development and annotation Knowledge discovery/representation (knowledge graphs, linked data, terminologies, lexicons, ontologies, etc.) Resource development for less-resourced/endangered languages Guidelines, standards, best practices, and models for interoperability Language Resource Use Use of language resources in systems and applications for any area of language and speech processing Use of language resources in assistive technologies, support for accessibility Efficient/low-resource methods for language and speech processing Evaluation Methodologies and protocols for evaluation and benchmarking of language technologies Measures for validation of language resources and quality assurance Usability of user interfaces and dialogue systems Bias, safety, and user satisfaction metrics Interpretability/explainability of language models and language and speech processing tools Language Resources and Large Language Models Language resource development for LLMs (monolingual, multilingual, multimodal) (Semi-)automatic generation of training data Training, fine-tuning, adaptation, alignment, and representation learning Guardrails, filters, and modules for generative AI models Policy and Organizational Considerations International and national activities, projects, initiatives, and policies Language coverage and diversity Replicability and reproducibility Organisational, economic, ethical, climate, and legal issues Separate calls will be issued for Workshops, Tutorials and Industry Track. Submission Submissions should be 4 to 8 pages in length (excluding references) and follow the LREC stylesheet, which will soon be available on the conference website. At the time of submission, authors are offered the opportunity to share related language resources with the community. All repository entries are linked to the LRE Map [https://lremap.elra.info/], which provides metadata for the resource. Accepted papers will appear in the conference proceedings, which include both oral and poster papers in the same format. Determination of the presentation format (oral vs. poster) is based solely on an assessment of the optimal method of communication (more or less interactive), given the paper content. Important dates (All deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”) Oral and poster (or poster+demo) paper submission: 17 October 2025 Notification of acceptance: 13 February 2026 Camera Ready due: 6 March 2026 Workshop and tutorial proposals submission: 17 October 2025 LREC 2026 conference: 11-16 May 2026 More information on LREC 2026: https://lrec2026.info/ Contact: info(a)lrec2026.info

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Deadline extension: First Workshop on Optimal Reliance and Accountability in Interactions with Generative Language Models
by Nikhil Krishnaswamy 18 Jun '25

18 Jun '25

The First Workshop on Optimal Reliance and Accountability in Interactions with Generative Language Models (*ORIGen*) will be held in conjunction with the Second Conference on Language Modeling (COLM) at the Palais des Congrès in Montreal, Quebec, Canada, on October 10, 2025! *The deadline for submission has been extended to June 27, 2025, Anywhere on Earth.* With the rapid integration of generative AI, exemplified by large language models (LLMs), into personal, educational, business, and even governmental workflows, such systems are increasingly being treated as “collaborators” with humans. In such scenarios, underreliance or avoidance of AI assistance may obviate the potential speed, efficiency, or scalability advantages of a human-LLM team, but simultaneously, there is a risk that subject matter non-experts may overrely on LLMs and trust their outputs uncritically, with consequences ranging from the inconvenient to the catastrophic. Therefore, establishing optimal levels of reliance within an interactive framework is a critical open challenge as language models and related AI technology rapidly advances. * What factors influence overreliance on LLMs? * How can the consequences of overreliance be predicted and guarded against? * What verifiable methods can be used to apportion accountability for the outcomes of human-LLM interactions? * What methods can be used to imbue such interactions with appropriate levels of “friction” to ensure that humans think through the decisions they make with LLMs in the loop? The ORIGen workshop provides a new venue to address these questions and more through a multidisciplinary lens. We seek to bring together broad perspectives from AI, NLP, HCI, cognitive science, psychology, and education to highlight the importance of mediating human-LLM interactions to mitigate overreliance and promote accountability in collaborative human-AI decision-making. Submissions are due *June 27, 2025*. Please see our call for papers [1] for more! [1] https://origen-workshop.github.io/submissions/ Organizers: - Nikhil Krishnaswamy, Colorado State University - James Pustejovsky, Brandeis University - Dilek Hakkani-Tür, University of Illinois Urbana Champaign - Vasanth Sarathy, Tufts University - Tejas Srinivasan, University of Southern California - Mariah Bradford, Colorado State University - Timothy Obiso, Brandeis University - Mert Inan, Northeastern University

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Job Offers: Senior and Junior AI & Language Technologies Specialists – EUSKORPORA (San Sebastián, Spain)
by info 18 Jun '25

18 Jun '25

Dear colleagues, EUSKORPORA, a newly created Linguistic Data Center for Basque digital technologies based in San Sebastián (Donostia), Spain, is seeking candidates for two key roles in its Technology area: 1) Senior AI and Language Technologies Specialist 2) Junior AI and Language Technologies Specialist Both positions are part of the Center's mission to position the Basque language in the global digital space through open-source development and cutting-edge research. === SENIOR AI AND LANGUAGE TECHNOLOGIES SPECIALIST === EUSKORPORA, the Linguistic Data Center for Basque Digital Technologies, a new association based in Donostia/San Sebastián, is seeking a senior expert in AI technologies applied to natural language processing, with experience, to lead key tasks related to language technologies applied to the Basque language. The selected person will be part of an interdisciplinary team and will participate in projects involving the collection, analysis, and annotation of linguistic data, as well as the development of open-source foundational language models (ASR, TTS, MT, NLP) oriented to Basque, in a research and development context closely connected to industry. Responsibilities: - Supervise and optimize processes for linguistic corpus collection, annotation, and management - Lead the design and development of foundational language models applied to Basque (speech recognition, synthesis, translation, text processing, etc.) - Contribute to the technological architecture of the Center - Coordinate internal and external teams and mentor junior staff - Identify innovation opportunities and contribute to proposals, reports, and dissemination - Establish strategic relationships with ecosystem stakeholders Requirements: - Advanced degree (Master or PhD) in Computational Linguistics, NLP, AI, Computer Engineering, Data Science or related fields - Minimum 5 years of experience in language or speech technologies - Proven experience with ASR, TTS, MT, or NLP models - Strong programming skills in Python and familiarity with frameworks such as Hugging Face, PyTorch, TensorFlow, spaCy, Kaldi, ESPnet, Fairseq - Knowledge of MLOps, Git, and data science best practices - Familiarity with open repositories and licensing Languages: - Basque: desirable, intermediate level (B2 or higher) - Spanish: fluent - English: high level (especially technical) We offer: - Participation in strategic national and international projects - Competitive salary according to experience - Interdisciplinary environment and opportunities for professional growth === JUNIOR AI AND LANGUAGE TECHNOLOGIES SPECIALIST === EUSKORPORA, the Linguistic Data Center for Basque Digital Technologies, a new association based in Donostia/San Sebastián, is seeking young professionals at the beginning of their careers to support key tasks related to the creation of linguistic resources and language technologies for the Basque language. Selected individuals will join an interdisciplinary team and participate in projects involving the collection, annotation, and analysis of linguistic data, as well as the development of open-source foundational language models (ASR, TTS, MT, NLP) oriented to Basque, in a research and development context closely connected to industry. Responsibilities: - Support the collection, cleaning and annotation of linguistic corpora (text and audio) - Assist in the training and evaluation of language and speech models - Collaborate in the documentation and maintenance of language resources - Contribute to the integration of open-source NLP tools and libraries - Assist in reports and dissemination activities - Work in coordination with technical, linguistic and project management profiles Requirements: - Degree or Master in Computational Linguistics, Computer Engineering, Data Science, or similar - Basic knowledge of NLP, language models, or speech technologies - Python programming (basic/intermediate level) - Familiarity with linguistic annotation or text processing tools - Experience with Git and frameworks like Hugging Face or spaCy is a plus Languages: - Basque: high level (B2 or higher) - Spanish: fluent - English: high level (B2 or higher) We offer: - Dynamic and innovative environment based in San Sebastián - Continuous training in cutting-edge technologies - Real opportunities for growth within the team - Competitive salary according to training and experience For further information or to apply, please contact: info(a)euskorpora.eus Best regards, EUSKORPORA [Euskorpora]<https://www.euskorpora.eus/> Euskorpora info(a)euskorpora.eus<mailto:sarregi@euskorpora.eus> +(34) 611 02 81 72 Mezu elektroniko honetan jasotzen den informazioa hartzaileen erabilera pertsonal eta konfidentzialerako da. Okerreko mezu hau jaso baduzu, mesedez, jakinarazi eta ezabatu. [https://www.euskorpora.eus/wp-content/uploads/2025/02/eco.png] Ez inprimatu mezu hau behar-beharrezkoa ez bada.

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Second CfP [New Dates]: Interdisciplinary Workshop on Observations of Misunderstood, Misguided and Malicious Use of Language Models (OMMM 2025)
by Piotr Przybyła 18 Jun '25

18 Jun '25

We are pleased to invite submissions for the first Interdisciplinary Workshop on Observations of Misunderstood, Misguided and Malicious Use of Language Models (OMMM 2025). The workshop will be held with the RANLP 2025 conference in Varna, Bulgaria, on 11-13 September 2025. Overview The use of Large Language Models (LLMs) pervades scientific practices in multiple disciplines beyond the NLP/AI communities. Alongside benefits for productivity and discovery, widespread use often entails misuse due to misalignment of values, lack of knowledge, or, more rarely, malice. LLM misuse has the potential to cause real harm in a variety of settings. Through this workshop, we aim to gather researchers interested in identifying and mitigating inappropriate and harmful uses of LLMs. These include misunderstood usage (e.g., misrepresentation of LLMs in the scientific literature); misguided usage (e.g., deployment of LLMs without adequate training or privacy safeguards); and malicious usage (e.g., generation of misinformation and plagiarism). Sample topics are listed below, but we welcome submissions on any domain related to the scope of the workshop. Important Dates Submission deadline *[NEW]*: *15 July 2025*, at 23:59 Anywhere on Earth Notification of acceptance: 01 August 2025 Camera-ready papers due: 30 August 2025 Workshop dates: September 11, 12, or 13, 2025 Submission Guidelines Submissions will be accepted as short papers (4 pages) and as long papers (8 pages), plus additional pages for references. All submissions undergo a double-blind review, so they should not include any identifying information. Submissions should conform to the RANLP guidelines; for further information and templates, please see https://ranlp.org/ranlp2025/index.php/submissions/ We welcome submissions from diverse disciplines, including NLP and AI, psychology, HCI, and philosophy. We particularly encourage reports on negative results that provide interesting perspectives on relevant topics. In-person presenters will be prioritised when selecting submissions to be presented at the workshop, but the workshop will take place in a hybrid format. Accepted papers will be included in the workshop proceedings in the ACL Anthology. Papers should be submitted on the RANLP conference system at https://softconf.com/ranlp25/OMMM2025/ Keynote Speaker We are excited to have Dr. Stefania Druga as the keynote speaker for the inaugural OMMM workshop. Dr. Druga is a Research Scientist at Google DeepMind, where she designs novel multimodal AI applications. Topics of Interest We welcome paper submissions on all topics related to inappropriate and harmful uses of LLMs, including but not limited to: - Misunderstood use (and how to improve understanding): - Misrepresentation of LLMs (e.g., anthropomorphic language) - Attribution of consciousness - Interpretability - Overreliance on LLMs - Misguided use (and how to find alternatives): - Underperformance and inappropriate applications - Structural limitations and ethical considerations - Deployment without proper training or safeguards - Malicious use (and how to mitigate it): - Adversarial attacks, jailbreaking - Detection and watermarking of machine-generated content - Generation of misinformation or plagiarism - Bias mitigation and trust design For more information, please refer to the workshop website: https://ommm-workshop.github.io/2025/. For any questions, please contact the organisers at ommm-workshop(a)googlegroups.com. The organisers, Piotr Przybyła, Universitat Pompeu Fabra Matthew Shardlow, Manchester Metropolitan University Clara Colombatto, University of Waterloo Nanna Inie, IT University of Copenhagen

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CfP: Terminology Translation Task @WMT25
by Kirill Semenov 18 Jun '25

18 Jun '25

[Apologies for cross-posting] Terminology Translation Task at WMT2025 - Call for Participation We are excited to announce the third Shared Task on Terminology Translation<https://www2.statmt.org/wmt25/terminology.html>, which would be run within the 10th Conference on Machine Translation (WMT2025) in Suzhou, China. TL;DR: - We test the sentence-level and document-level translation of the texts in finance and IT domains, given the explicit terminology. - The language pairs are: English -> {Spanish, German, Russian, Chinese}, Chinese -> English. - We evaluate the overall quality of translation, terminology success rate and consistency. Additionally, we compare the performance of systems given no terms provided, proper terminology and random terms. - The task starts on 20th June 2025 AOE, the submission deadline is 20th July 2025 AOE. - Please pre-register via Google Forms here: https://forms.gle/ZSn2pNJkQJAzHFnA6 . OVERVIEW The advances in neural MT and LLM-assisted translation of the last decade show nearly human quality in general domain translation at least for the high-resource languages. However, when it comes to specialized domains like science, finance, or legal texts, where the correct and consistent use of special terms is crucial, the task is far from being solved. The Terminology Shared Task aims to assess the extent to which machine translation models can utilize additional information regarding the translation of terminologies. Compared to two previous editions, 2021 and 2023, the new test data have more various test cases, are more consistent in domains for each translation direction, and are broader in language coverage. TASK DESCRIPTION Track №1: Sentence/Paragraph-Level Translation You will be provided with sequence of input sentences long, and small terminology dictionaries that will correspond only to the terms present in the given sentence. Language Pairs: * en-de (English → German) * en-ru (English → Russian) * en-es (English → Spanish) Domain: information technology Track №2: Document-Level Translation The setup is similar to Track №1, with two exceptions: the length of the input texts now equals the document, and the dictionaries correspond to the whole set of input texts (i.e. they are corpus-level). This makes the task close to the real-life setup (where the dictionaries exist independently from the texts), while it may complicate the implementation (since for the solutions that require storing the whole dictionary it will take more memory). Additionally, for the whole document setup, the problem of the consistent usage of terms is becoming more important. Language Pairs: en-zh-Hant (English → Traditional Chinese) zh-Hant-en (Traditional Chinese → English) Domain: finance EVALUATION Terminology Modes: You are expected to compare your system’s performance under three modes: 1. No terminology: the system is only provided with input sentences/documents. 2. Proper terminology: the system is provided with input texts (same as 1.) and dictionaries of the format {source_term: target_term}. 3. Random terminology: the system is provided with input texts and translation dictionaries of the same format as in 2. The difference is that the dictionary items are not special terms but words randomly drawn from input texts. This mode is of special interest since we want to measure to what extent the proper term translations help to improve the system performance (2.), as opposed to an arbitrary broader input that does not contain the domain-specific terminology. Metrics: 1. Overall Translation Quality: we will evaluate the general aspects of machine translation outputs such as fluency, adequacy and grammaticality. We will do that with the general MT automatic metrics such as BLEU or COMET. In addition to that, we will pay special attention to the grammaticality of the translated terms. 2. Terminology Success Rate: This metric assesses the ability of the system to accurately translate technical terms given the specialized vocabulary. This will be carried out by comparing the occurrences of the correct term translations (i.e. the ones present in the dictionary) to the output terms. The goal is to have a higher success rate that will show adherence to dictionary translations. 3. Terminology Consistency: for domains such as science or legal texts, the consistent use of an introduced term throughout the text is crucial. In other words, we want a system to not only pick up a correct term in a target language but to use it consistently once it is chosen. This will be evaluated by comparing all translations of a given source term in a text and measuring the percentage of deviations from the most consistent translation. This metric is more important for the Document-Level track, but it will be used for both tracks. IMPORTANT DATES All dates are end of Anywhere on Earth (AoE). Data snippets released: 7th May 2025 Dev data released: 22nd May 2025 Test data release, task starts: 20th June 2025 (postponed) Submission deadline: 20th July 2025 (postponed) Paper submission to WMT25: in-line with WMT25 Camera-ready submission to WMT25: in-line with WMT25 Conference in Suzhou, China: 05-09 November 2025 SUBMISSION GUIDELINES 0. Please notify us about your participation prior to submission. This is optional, but will be very helpful for us for better understanding of our workload after submission. Please do it through this Google Form: https://forms.gle/ZSn2pNJkQJAzHFnA6 1. Check your submission files with the validation script. It will be published at test date publication. 2. Write a description of your system (optional). 3. Submit your system via Google Forms. The Google form with all necessary submission details will be published at the test set date. All details on submission as well as FAQ can be found at the webpage of the shared task. ORGANIZERS * Kirill Semenov (University of Zurich), main contact: FirstNаmе [dоt] LаstNаmе {аt} uzh /dоt/ ch * Nathaniel Berger (Heidelberg University) * Pinzhen Chen (University of Edinburgh & Aveni.ai) * Xu Huang (Nanjing University) * Arturo Oncevay (JP Morgan) * Dawei Zhu (Amazon) * Vilém Zouhar (ETH Zurich) WEBSITE: https://www2.statmt.org/wmt25/terminology.html In case of query, please send an email to Kirill Semenov (see email above).

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Call for papers: The First Workshop on Natural Language Processing and Language Models for Digital Humanities (LM4DH 2025) @ RANLP_2025
by Nanomi Arachchige, Isuri (Postgraduate Researcher) 18 Jun '25

18 Jun '25

Call for papers: The First Workshop on Natural Language Processing and Language Models for Digital Humanities (LM4DH_2025) @ RANLP_2025 Date: 11th- to 13th September 2025 (TBC) Venue : Varna, Bulgaria Website: https://www.clarin.eu/event/2025/clarin-workshop-ranlp-2025 Submissions Portal: https://softconf.com/ranlp25/LM4DH2025/ Digital Humanities has emerged as an interdisciplinary field of research, serving as an intersection of computer science with many other fields such as linguistics, social sciences, history, psychology, etc. With the development of Large Language Models (LLMs), state-of-the-art Natural Language Processing (NLP) tasks such as entity recognition, sentiment analysis, and text summarisation have been significantly enhanced, offering powerful tools to analyse and interpret complex historical and cultural data. These developments offer transformative capabilities for analysing and interpreting complex historical and cultural datasets, including oral histories, archival documents, and literary texts. These advancements provide powerful tools for analysing and interpreting intricate historical, cultural, and social data, enabling researchers to identify patterns, extract meaningful relationships, and generate interpretations at unprecedented scale and precision. This workshop aims to provide a common platform for researchers, practitioners, and students from diverse disciplines to collaboratively explore and apply AI-driven techniques in the Digital Humanities. Through interdisciplinary discussion, the event aims to generate creative approaches, exchange best practices, and create a community committed to furthering AI-based research on human culture and history. The focus of the workshop is on applying natural language processing techniques to digital humanities research. The topics can be anything of digital humanities interest with a natural language processing or LLM-based application. We expect contributions related (but not limited) to the following topics: * Text analysis and processing related to the humanities using computational methods * Usage of the interpretability of large language models' output for DH-related tasks * Dataset creation and curation for NLP (e.g. digitisation, datafication, and data preservation * Automatic error detection, correction, and normalisation of textual data * Generation and analysis of literary works such as poetry and novels * Analysis and detection of text genres * Emotion analysis for the humanities and literature * Modelling of information and knowledge in the Humanities, Social Sciences, and Cultural Heritage * Low-resource and historical language processing * Search for scientific and/or scholarly literature * Profiling and authorship attribution Submission & Publication All papers must represent original and unpublished work that is not currently under review. Papers will be evaluated according to their significance, originality, technical content, style, clarity, and relevance to the workshop. Submissions must follow the RANLP 2025 submission guidelines<https://ranlp.org/ranlp2025/index.php/submissions/>, using ACL-style templates (LaTeX or MS Word). Paper must be submitted using SoftConf at https://softconf.com/ranlp25/LM4DH2025/ All papers will be double-blind peer reviewed. Authors of the accepted papers will present their work in either the oral or poster session. All accepted papers will appear in the workshop proceedings that will be published in ACL Anthology. Important Dates * Paper submission deadline: 20th July 2025 * Notification of acceptance: 2nd August 2025 * Camera-ready paper: 20th August 2025 * Workshop date: 11th September 2025 Organising Committee * Isuri Anuradha, Lancaster University, UK * Francesca Frontini, CNR-ILC, Italy & CLARIN ERIC * Paul Rayson, Lancaster University, UK * Ruslan Mitkov, Lancaster University, UK * Deshan Sumanathilake, Swansea University, UK This workshop has been organised with the generous support and coordination of CLARIN-EU. Gmail: dhranlp2(a)gmail.com<mailto:%20dhranlp2@gmail.com>

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FIRE 2025- Call for Participation in Tracks - 12 Tracks -17th meeting of the Forum for Information Retrieval Evaluation -Dec. Varanasi
by Thomas Mandl 17 Jun '25

17 Jun '25

*Call for Participation in Tracks * *FIRE 2025: 17th meeting of the Forum for Information Retrieval Evaluation* Indian Institute of Technology (BHU) Varanasi 17th - 20th December Website: fire.irsi.org.in <http://fire.irsi.org.in/> *Call for Participation in Tracks* FIRE 2025 offers the following exciting tracks this year: * Cross-Lingual Mathematical Information Retrieval (CLMIR) <https://clmir2025.github.io/> * Code-Mixed Information Retrieval from Social Media Data (CMIR) <https://cmir-iitbhu.github.io/cmir/index.html> * Hate Speech and Offensive Content Identification in Memes in Bengali, Hindi, Gujarati and Bodo (HASOC-meme) <https://hasocfire.github.io/hasoc/2025/> * Information Retrieval in Software Engineering (IRSE) <https://sites.google.com/view/irse-2025/home> * Misinformation Detection and Prompt Recovery (PROMID) <https://promid.github.io/index.html> * Multilingual Story Illustration: Bridging Cultures through AI Artistry (MUSIA) <https://cse-iitbhu.github.io/MUSIA/index.html> * Offensive Language Identification in Dravidian Languages (DravidianCodeMix) <https://dravidian-codemix.github.io/2025/dataset.html> * Opinion Extraction and Question Answering from CryptoCurrency-Related Tweets and Reddit posts (CryptOQA) <https://sites.google.com/view/cryptoqa-2025/> * Research Highlight Generation from Scientific Papers (SciHigh) <https://sites.google.com/jadavpuruniversity.in/scihigh2025/home> * Spoken-Query Cross-Lingual Information Retrieval for the Indic Languages (SqCLIR) <https://sites.google.com/view/sqclir-2025> * Varanasi Tourism in Question Answer System (VATIKA) <https://sites.google.com/view/vatika-2025/> * Word-Level Identification of Languages in Dravidian Languages (WILD) <https://www.codabench.org/competitions/7902/> Research groups are invited to participate in the experiments. Please register directly with the organizers. FIRE 2025 is the 17th edition of the annual meeting of Forum for Information Retrieval Evaluation (fire.irsi.org.in). Since its inception in 2008, FIRE had a strong focus on shared tasks similar to those offered at Evaluation forums like TREC, CLEF, and NTCIR. The shared tasks focus on solving specific problems in the area information access and, more importantly help in generating evaluation datasets for the research community. Visit fire.irsi.org.in <http://fire.irsi.org.in>

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CfP DHOW: Workshop Diffusion of Harmful Content on Online Web Workshop - @ ACMMM 2025
by Thomas Mandl 17 Jun '25

17 Jun '25

The 2st Workshop on DHOW: Diffusion of Harmful Content on Online Web Workshop The workshop will be conducted in a *hybrid* format to ensure maximum participation, accommodating attendees both *online* and in person. Submission deadline: *July 11 2025 AOE* *Workshop site*: https://dhow-workshop.github.io/2025/ *Co-located with ACMMM 2025* https://acmmm2025.org/ <https://lrec-coling-2024.org/> Dublin, Ireland, 27-31 October 2024 *Important Dates* Submission deadline: extended to *July 11, 2025* Notification of acceptance: August 01, 2025 Camera-ready papers due: August 11, 2025 Workshop date: October 27/28, 2025 *Workshop Description* With the advancement of digital technologies and gadgets, online content is easily accessible. At the same time, harmful content also gets spread. 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 aspect, 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 the 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 latest developments, and collaborate on addressing the challenges associated with harmful contents 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 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 •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 •Multimodal and Multilingual Harmful Content Detection such as fake news, spam, and troll detection. •Deepfake and Synthetic Media •Ethical & Societal Implications of AI in Content Moderation •Both Qualitative and Quantitative study 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 *Submissions* - Submission Instructions: https://dhow-workshop.github.io/2025/#call <https://dhow-workshop.github.io/2025/#call> - Submission Link: https://openreview.net/group?id=acmmm.org/ACMMM/2025/Workshop/DHOW <https://openreview.net/group?id=acmmm.org/ACMMM/2025/Workshop/DHOW> ***Workshop organizers* •Thomas Mandl (University of Hildesheim, Germany) •Haiming Liu (University of Southampton, United Kingdom) •Gautam Kishore Shahi(University of Duisburg-Essen, Germany) •Amit Kumar Jaiswal (University of Surrey, United Kingdom ) •Durgesh Nandini (University of Bayreuth, Germany) DHOW 2025

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Call for papers : Ethical LLMs @ RANLP2025
by Dola Mullage, Damith (Postgraduate Researcher) 17 Jun '25

17 Jun '25

Ethical LLMs 2025: The first Workshop on Ethical Concerns in Training, Evaluating and Deploying Large Language Models<https://sites.google.com/view/ethical-llms-2025> @ RANLP2025<https://ranlp.org/ranlp2025/> Call for papers: Scope Large Language Models (LLMs) represent a transformative leap in Artificial Intelligence (AI), delivering remarkable language-processing capabilities that are reshaping how we interact with technology in our daily lives. With their ability to perform tasks such as summarisation, translation, classification, and text generation, LLMs have demonstrated unparalleled versatility and power. Drawing from vast and diverse knowledge bases, these models hold the potential to revolutionise a wide range of fields, including education, media, law, psychology, and beyond. From assisting educators in creating personalised learning experiences to enabling legal professionals to draft documents or supporting mental health practitioners with preliminary assessments, the applications of LLMs are both expansive and profound. However, alongside their impressive strengths, LLMs also face significant limitations that raise critical ethical questions. Unlike humans, these models lack essential qualities such as emotional intelligence, contextual empathy, and nuanced ethical reasoning. While they can generate coherent and contextually relevant responses, they do not possess the ability to fully understand the emotional or moral implications of their outputs. This gap becomes particularly concerning when LLMs are deployed in sensitive domains where human values, cultural nuances, and ethical considerations are paramount. For example, biases embedded in training data can lead to unfair or discriminatory outcomes, while the absence of ethical reasoning may result in outputs that inadvertently harm individuals or communities. These limitations highlight the urgent need for robust research in Natural Language Processing (NLP) to address the ethical dimensions of LLMs. Advancements in NLP research are crucial for developing methods to detect and mitigate biases, enhance transparency in model decision-making, and incorporate ethical frameworks that align with human values. By prioritising ethics in NLP research, we can better understand the societal implications of LLMs and ensure their development and deployment are guided by principles of fairness, accountability, and respect for human dignity. This workshop will dive into these pressing issues, fostering a collaborative effort to shape the future of LLMs as tools that not only excel in technical performance but also uphold the highest ethical standards. Submission Guidelines We follow the RANLP 2025 standards for submission format and guidelines. EthicalLLMs 2025 invites the submission of long papers, up to eight pages in length, and short papers, up to six pages in length. These page limits only apply to the main body of the paper. At the end of the paper (after the conclusions but before the references) papers need to include a mandatory section discussing the limitations of the work and, optionally, a section discussing ethical considerations. Papers can include unlimited pages of references and an unlimited appendix. To prepare your submission, please make sure to use the RANLP 2025 style files available here: * Latex<https://ranlp.org/ranlp2025/wp-content/uploads/2025/05/ranlp2025-LaTeX.zip> * Word<https://ranlp.org/ranlp2025/wp-content/uploads/2025/05/ranlp2025-word.docx> Papers should be submitted through Softconf/START using the following link: https://softconf.com/ranlp25/EthicalLLMs2025/ Topics of interest The workshop invites submissions on a broad range of topics related to the ethical development and evaluation of LLMs, including but not limited to the following. 1. Bias Detection and Mitigation in LLMs Research focused on identifying, measuring, and reducing social, cultural, and algorithmic biases in large language models. 2. Ethical Frameworks for LLM Deployment Approaches to integrating ethical principles—such as fairness, accountability, and transparency—into the development and use of LLMs. 3. LLMs in Sensitive Domains: Risks and Safeguards Case studies or methodologies for deploying LLMs in high-stakes fields such as healthcare, law, and education, with an emphasis on ethical implications. 4. Explainability and Transparency in LLM Decision-Making Techniques and tools for improving the interpretability of LLM outputs and understanding model reasoning. 5. Cultural and Contextual Understanding in NLP Systems Strategies for enhancing LLMs’ sensitivity to cultural, linguistic, and social nuances in global and multilingual contexts. 6. Human-in-the-Loop Approaches for Ethical Oversight Collaborative models that involve human expertise in guiding, correcting, or auditing LLM behaviour to ensure responsible use. 7. Mental Health and Emotional AI: Limits of LLM Empathy Discussions on the role of LLMs in mental health support, highlighting the boundary between assistive technology and the need for human empathy. Organisers Damith Premasiri – Lancaster University, UK Tharindu Ranasinghe – Lancaster University, UK Hansi Hettiarachchi – Lancaster University, UK Contact If you have any questions regarding the workshop, please contact Damith: d.dolamullage(a)lancaster.ac.uk

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Survey on Queries in Syntactically Annotated Corpora
by Niklas Deworetzki 17 Jun '25

17 Jun '25

Dear all, We are currently doing a project aiming to make querying in syntactically annotated corpora easier and more accessible. For this purpose, we want to know what researchers are actually searching for. If you have a minute of your time, please feel free to fill out this form. https://forms.office.com/e/a8DgETSabB Feel free to reach out to ekavol(a)chalmers.se or nikdew(a)chalmers.se if you have any further questions. Best regards Niklas Deworetzki & Katja Voloshina PhD Students Department of Computer Science and Engineering Chalmers University of Technology | University of Gothenburg SE-412 96 Göteborg, Sweden www.gu.se<http://www.gu.se/> www.chalmers.se<http://www.chalmers.se/> [cid:a8138665-78e4-4530-80d5-cf9cbf2bd3c2]

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2025

2024

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2022