- Corpora - ELRA lists

HPLT Datasets version 2.0 released
by Andrey Kutuzov 03 Oct '24

03 Oct '24

(Apologies for cross-posting) Version 2.0 of the HPLT Datasets is now published, with web-derived corpora in 193 languages. These collections are available under the Creative Commons CC0 license and bring significant improvements compared to previous releases (version 1.2). Similarly to 1.2, the release comes in two variants: de-duplicated (21 TB in size) and cleaned (15 TB in size). The cleaned variant contains the same documents as de-duplicated minus those filtered out by our cleaning heuristics. The cleaned variant is the recommended one, unless you want to try your own cleaning pipelines. Download the corpora here: https://hplt-project.org/datasets/v2.0 Similar to the previous releases, version 2.0 datasets are hosted by Sigma2 NIRD Data Lake (https://www.sigma2.no/service/nird-data-lake), and text extraction pipeline was run on LUMI supercomputer (https://lumi-supercomputer.eu/). *What's new* - The size of the source web collections has increased 2.5x: 4.5 petabytes of compressed web data in total, mostly from Internet Archive (https://archive.org/), but also from Common Crawl (https://commoncrawl.org/). - The text extraction pipeline now uses Trafilatura (https://trafilatura.readthedocs.io/), which results in more efficient boilerplate removal: thus, less noise in the data. - Language identification now uses a refined version of OpenLID (https://aclanthology.org/2023.acl-short.75/). - This, in turn, allowed us to publish data in 193 languages, compared to 75 languages in version 1.2. - We switched from two-letter ISO 639-1 language codes to three-letter ISO 639-3 language codes, augmented with a postfix denoting writing system. For example, `pol_Latn` is Polish written in Latin script. Mapping from the old to the new codes is available at https://github.com/hplt-project/warc2text-runner/blob/main/stats/_langs/lan…. - The documents are now annotated with their compliance to the robots.txt file of the original website. This metadata field can be used to filter out documents explicitly forbidden for crawling by website owners, making the resulting corpora somewhat less prone to copyright violations . The cleaned variant contains only robots.txt compliant documents. More details at https://github.com/hplt-project/monotextor-slurm/blob/main/README.md#robots… - De duplication is done at collection-level, not at dataset level. - Documents have also been annotated for PII information with multilingual-pii-tool (https://github.com/mmanteli/multilingual-PII-tool). These are identified in the form of Unicode character offsets for every match. - Segment-level language-model-based scores have been replaced by document quality scores computed with web-docs-scorer. - Filtering and cleaning criteria have been simplified (https://github.com/hplt-project/monotextor-slurm?tab=readme-ov-file#filters). HPLT Monolingual Datasets version 2.0 (the de-duplicated variant) feature about 7.6 trillion whitespace-separated words and about 52 trillion characters extracted from 21 billion documents, compared to 5.6 trillion words and 42 trillion characters extracted from 5 billion documents in version 1.2. All in all, you can expect less noise and boilerplate, less duplicates, more unique documents, and generally better quality texts to train language models on or for other NLP tasks. *How was this dataset produced* You may want to read section 3 of our Deliverable HPLT pipeline and tools (https://hplt-project.org/HPLT_D7_2___HPLT_pipelines_and_tools.pdf) to have a full description on how did we produced this dataset. If you don't have much time for reading, maybe this chart is enough for your purposes: https://hplt-project.org/_next/static/media/dataset-pipeline-light.c2521ee1… Each language is accompanied with an HPLT Analytics report. These automated reports provide useful information and statistics about the clean version of the HPLT v.2.0 datasets. They are the result of running the HPLT Analytics Tool (https://github.com/hplt-project/data-analytics-tool) on them. They are helpful for inspecting the datasets even before downloading them. *What is HPLT?* HPLT (High Performance Language Technologies) is an EU Horizon Europe funded project which aims at collecting large quantities of data in many languages and training powerful and efficient language and translation models. An important feature of HPLT is openness and transparency: all the artifacts of the project are publicly available under permissive licenses. https://hplt-project.org/ -- Andrey Language Technology Group (LTG) University of Oslo

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Second Call for Papers: The First Workshop on Language Models for Low-Resource Languages (LoResLM 2025@COLING)
by Ranasinghe, Tharindu 03 Oct '24

03 Oct '24

Neural language models have revolutionised natural language processing (NLP) and have provided state-of-the-art results for many tasks. However, their effectiveness is largely dependent on the pre-training resources. Therefore, language models (LMs) often struggle with low-resource languages in both training and evaluation. Recently, there has been a growing trend in developing and adopting LMs for low-resource languages. LoResLM aims to provide a forum for researchers to share and discuss their ongoing work on LMs for low-resource languages. >> Topics LoResLM 2025 invites submissions on a broad range of topics related to the development and evaluation of neural language models for low-resource languages, including but not limited to the following. * Building language models for low-resource languages. * Adapting/extending existing language models/large language models for low-resource languages. * Corpora creation and curation technologies for training language models/large language models for low-resource languages. * Benchmarks to evaluate language models/large language models in low-resource languages. * Prompting/in-context learning strategies for low-resource languages with large language models. * Review of available corpora to train/fine-tune language models/large language models for low-resource languages. * Multilingual/cross-lingual language models/large language models for low-resource languages. * Applications of language models/large language models for low-resource languages (i.e. machine translation, chatbots, content moderation, etc. >> Important Dates * Paper submission due – 5th November 2024 * Notification of acceptance – 25th November 2024 * Camera-ready due – 13th December 2024 * LoResLM 2025 workshop – 19th / 20th January 2025 co-located with COLING 2025 >> Submission Guidelines We follow the COLING 2025 standards for submission format and guidelines. LoResLM 2025 invites the submission of long papers of up to eight pages and short papers of up to four pages. 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 COLING 2025 style files available here: * Latex - https://coling2025.org/downloads/coling-2025.zip * Word - https://coling2025.org/downloads/coling-2025.docx * Overleaf - https://www.overleaf.com/latex/templates/instructions-for-coling-2025-proce… Papers should be submitted through Softconf/START using the following link: https://softconf.com/coling2025/LoResLM25/ >> Organising Committee * Hansi Hettiarachchi, Lancaster University, UK * Tharindu Ranasinghe, Lancaster University, UK * Paul Rayson, Lancaster University, UK * Ruslan Mitkov, Lancaster University, UK * Mohamed Gaber, Birmingham City University, UK * Damith Premasiri, Lancaster University, UK * Fiona Anting Tan, National University of Singapore, Singapore * Lasitha Uyangodage, University of Münster, Germany >> Programme Committee * Burcu Can - University of Stirling, UK * Çağrı Çöltekin - University of Tübingen, Germany * Debashish Das - Birmingham City University, UK * Alphaeus Dmonte - George Mason University, USA * Daan van Esch - Google * Ignatius Ezeani - Lancaster University, UK * Anna Furtado - University of Galway, Ireland * Amal Htait - Aston University, UK * Ali Hürriyetoğlu - Wageningen University & Research, Netherlands * Diptesh Kanojia - University of Surrey, UK * Jean Maillard - Meta * Maite Melero - Barcelona Supercomputing Centre, Spain * Muhidin Mohamed - Aston University, UK * Nadeesha Pathirana - Aston University, UK * Alistair Plum - University of Luxembourg, Luxembourg * Sandaru Seneviratne - Australian National University, Australia * Ravi Shekhar - University of Essex, UK * Taro Watanabe - Nara Institute of Science and Technology, Japan * Phil Weber - Aston University, UK URL - https://loreslm.github.io/ Twitter - https://x.com/LoResLM2025 Best Regards Tharindu Ranasinghe

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[CFP] SemEval 2025 Task 5 - LLMs4Subjects - 1st Call for Shared Task Participation
by Jennifer D'Souza 03 Oct '24

03 Oct '24

[apologies if you receive multiple copies of this call] Dear colleagues and friends, *We are pleased to release the 1st Call for Participation to the LLMs4Subjects Shared Task organized as part of SemEval 2025.* *Overview:* As the first of its kind, LLMs4Subjects invites the research community to *develop cutting-edge LLM-based semantic solutions for the subject tagging of the Leibniz University's Technical Library's open-access collection*. The shared task provides an opportunity for the research community to creatively utilize LLMs for subject tagging of technical records. *Systems need to demonstrate bilingual language modeling in understanding technical documents in both German and English.* Moreover, successful solutions may be directly integrated into the operational workflows of the TIB Leibniz Information Centre for Science and Technology University Library. *What we provide to participants:* a human-readable form of a subject's taxonomy (this is the *GND* or *Gemeinsame Normdatei*, the integrated authority file used for cataloging in German-speaking countries) and a large collection of technical records tagged with these subjects from the TIB's open-access collection called *TIBKAT*. More details on the task website: https://sites.google.com/view/llms4subjects/ *LLMs4Subjects defines the following three tasks:* - Task 1: Learn the GND - Task 2: Align subject tagging to the TIBKAT collection - (Optional and Fun) Task 3: Develop Elegant Frontend Interfaces for Subject Tagging *LLMs4Subjects will have three separate evaluations:* - Evaluation 1: Quantitative Metrics-based Evaluations - Evaluation 2: Qualitative Evaluations by the Human Subject Specialists - (Optional) Evaluation 3: HCI evaluations for subject indexing interfaces submitted *To participate in the LLMs4Subjects shared task,* 1. please submit your interest to participate using our online form ( https://forms.gle/YQzupcoySAyJi45c6), 2. sign up to the shared task Google Groups ( https://groups.google.com/u/6/g/llms4subjects) for FAQs, news, and announcements, and, 3. last but not the least, download the datasets ( https://github.com/jd-coderepos/llms4subjects/) to begin development. *Dates* Training and validation datasets available:October 2, 2024 Test data available/Evaluation starts: January 10, 2025 Evaluation ends: January 31, 2025 Participant paper submissions due: February 28, 2025 Notification to authors: March 31, 2025 Camera ready due: April 21, 2025 SemEval workshop: TBD *Task Organizers* Jennifer D'Souza, Sameer Sadruddin, Holger Israel, Mathias Begoin et al. All organizers are affiliated with the TIB Leibniz Information Centre for Science and Technology - Germany (https://www.tib.eu/en/) *We look forward to having you on board!* *Contact: * llms4subjects [at] gmail.com

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eLex 2025: Intelligent lexicography - first announcement
by Iztok Kosem 03 Oct '24

03 Oct '24

Dear all, This is the first announcement for the eLex 2025 conference on electronic lexicography, so please mark your calendars. Dates: 18-20 November 2025 Location: Bled, Slovenia Website: https://elex.link/elex2025/ Organiser: Centre for Language Resources and Technologies, University of Ljubljana The theme of next year’s conference will be “Intelligent lexicography”. More information on the theme and the first call for papers will be published soon. We are also accepting proposals for pre- or postconference workshops. Looking forward to seeing you in Slovenia Iztok Kosem In the name of the organising committee

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[2nd CFP] The 1st Workshop and Shared Task on Multilingual Counterspeech Generation
by mevallec＠ujaen.es 03 Oct '24

03 Oct '24

----------------------------------------------------- Workshop on Multilingual Counterspeech Generation ----------------------------------------------------- Background and Scope --------------------- While interest in automatic approaches to Counterspeech generation has been steadily growing, including studies on data curation (Chung et al., 2019a; Fanton et al., 2021), detection (Chung et al., 2021a; Mathew et al., 2018), and generation (Tekiroglu et al., 2020; Chung et al., 2021b; Zhu and Bhat, 2021; Tekiroglu et al., 2022), the large majority of the published experimental work on automatic Counterspeech generation has been carried out for English. This is due to the scarcity of both non-English manually curated training data and to the crushing predominance of English in the generative Large Language Models (LLMs) ecosystem. A workshop on exploring Multilingual Counterspeech Generation is proposed to promote and encourage research on multilingual approaches for this challenging topic. Thus, this workshop aims to test monolingual and multilingual LLMs in particular and Language Technology in general to automatically generate counterspeech not only in English but also in languages with fewer resources. In this sense, an important goal of the workshop will be to understand the impact of using LLMs, considering for example how to deal with pressing issues such as biases, hallucinated content, data scarcity or data contamination. We seek to maximize the scientific and social impact of this workshop by promoting the creation of a community of researchers from diverse fields, such as computer and social sciences, as well as policy makers and other stakeholders interested in automatic counterspeech generation. By doing so we aim to gain a deeper understanding of how counterspeech is currently used to tackle abuse by individuals, activists, and organizations and how Natural Language Processing (NLP) and Generation (NLG) may be best applied to counteract it. Call for Papers --------------------- We welcome submissions on the following topics (but not limited to): - Models and methods for generating counterspeech in different languages. - Automatic Counterspeech generation for low resource languages with scarce training data. - Dialogue agents that use counterspeech to combat offensive messages that are directed to individuals or groups, targeted based on various aspects such as ideology, gender, sexual orientation and religion. - Methods for human and automatic evaluation of counterspeech. - Multidisciplinary studies providing different perspectives on the topic such as computer science, social science, psychology, etc. - Development of taxonomies and quality datasets for counterspeech in multiple languages. - Potentials and limitations (e.g., fairness, biases, hallucinated content) of applying different NLP methods, such as LLMs, to generate counterspeech. - Social impact and empirical studies of counterspeech in social networks, including research on the effectiveness and consequences for users of using counterspeech to combat hate online. Submission --------------------- We welcome two types of papers: regular workshop papers and non-archival submissions. Regular workshop papers will be included in the workshop proceedings. All submissions must be in PDF format and made through START [https://softconf.com/coling2025/MCG25/] - Regular workshop papers: Authors can submit papers up to 8 pages, with unlimited pages for references. Authors may submit up to 100 MB of supplementary materials separately and their code for reproducibility. All submissions undergo an double-blind single-track review. Accepted papers will be presented as posters with the possibility of oral presentations. - Non-archival submissions: Cross-submissions are welcome. Accepted papers will be presented at the workshop, but will not be included in the workshop proceedings. Papers must be in PDF format and will be reviewed in a double-blind fashion by workshop reviewers. We also welcome extended abstracts (up to 2 pages) of papers that are work in progress, under review or to be submitted to other venues. Papers in this category need to follow the COLING format. Important Dates --------------------- - Submission: November 20th, 2024 - Notification of Acceptance: December 2nd, 2024 - Camera-Ready Papers Due: December 10th, 2024 ----------------------------------------------------- Shared Task on Multilingual Counterspeech Generation ----------------------------------------------------- *TRAIN DATA RELEASED!* In addition to paper contributions, we are organizing a shared task on multilingual counterspeech generation with the aim of sharing in a central space current efforts, especially those for languages different to English. It is envisaged that the shared task would allow the community to study how we can improve counterspeech generation for both lower resource languages but also to reinforce the strong body of research already existing for English. The counterspeech generated by participants should be respectful, non-offensive, and contain information that is specific and truthful with respect to the following targets: Jews, LGBT+, immigrants,, people of color, women. Data --------------------- We release new data consisting of 596 Hate Speech-Counter Narrative (HS-CN) pairs. In this dataset, the HS are taken from MTCONAN [https://github.com/marcoguerini/CONAN/tree/master/Multitarget-CONAN], while the CN are newly generated. Together with each HS-CN pair, we also provide 5 background knowledge sentences, some of which are relevant for obtaining the Counter Narratives. The dataset is available in 4 different languages (Basque, English, Italian and Spanish) and divided in the following splits: - Development: 100 pairs. [AVAILABLE NOW!] [https://huggingface.co/datasets/LanD-FBK/ML_MTCONAN_KN] - Train: 396 pairs [AVAILABLE NOW!] [https://huggingface.co/datasets/LanD-FBK/ML_MTCONAN_KN] - Test: 100 pairs [AVAILABLE ON 21st OCTOBER] In order to score the shared task participants, the CNs will be kept hidden during the shared task while the HS and the background knowledge will be released for participants to prepare their submissions. The languages, Basque, English, Italian and Spanish, offer a varied spectrum of complexity including an agglutinative language isolate (Basque), two romance languages (Italian, Spanish) and a Germanic one (English). The choice of languages obeys to the existing linguistic expertise among the organizers required to successfully run the shared task. Additional Multilingual Data --------------------- Participants also have available the English, Italian, Basque and Spanish CONAN manually curated data: - CONAN (English and Italian) [https://github.com/marcoguerini/CONAN/tree/master/CONAN] - CONAN (Basque and Spanish) [https://huggingface.co/datasets/HiTZ/CONAN-EUS] - CONAN-MT-SP (Spanish) [https://github.com/sinai-uja/CONAN-MT-SP] or [https://huggingface.co/datasets/SINAI/CONAN-MT-SP] - Multitarget-CONAN (English) [https://github.com/marcoguerini/CONAN/tree/master/Multitarget-CONAN] Participation --------------------- The aim of the shared task is, given a HS (and optionally any additional knowledge the participants may like to use), generate a CN to counteract the HS. An example of CN appear bellow: - English: + HS: We should ban all homosexuals. + CN: When will the love prosper and the hatred start to dissipate? I will not only respect my fellow LGBT+ people, I will promote their rights. - Italian: + HS: Dovremmo espellere tutti gli omosessuali. + CN: Quand'è che l'amore prospererà e l'odio inizierà a dissiparsi? Non solo rispetterò i miei compagni LGBT+, ma promuoverò i loro diritti. - Spanish: + HS: Deberíamos prohibir a todos los homosexuales. + CN: ¿Cuándo prosperará el amor y empezará a disiparse el odio? No sólo respetaré a mis compañeros LGBT+, sino que promoveré sus derechos. - Basque: + HS: Homosexual guztiak debekatu beharko genituzke. + CN: Noiz hasiko da maitasuna irabazten eta gorrotoa desagertzen? LGBT+ pertsonak errespetatzeaz gain, haien eskubideak sustatuko ditut. Participants will download the test HS for the 4 languages and generate at most three different CNs per HS for each language). The test window will last 5 days. Participants are allowed to use any resource (language model, data, etc.) to generate the CN. **Note:** If you are going to participate in the shared task, please fill the following form: [https://docs.google.com/forms/d/e/1FAIpQLSeAZTJsrEXt35HfFFchPNdPi289q5kKerq…] Evaluation --------------------- The CNs submitted by the participants will be evaluated: - Using traditional automatic metrics as in Tekiro ̆glu et al.( 2022), which include BLEU, ROUGE, Novelty and Repetition Rate. - Using LLM as a Judge following the approach described in this paper: https://arxiv.org/abs/2406.15227 Important Dates --------------------- - Test dataset release: October 21st, 2024 - Results submission: October 25th, 2024 - Results notification: November 10th, 2024 - Working papers submission: November 20th, 2024 - Notification of Acceptance: December 3rd, 2024 - Camera-Ready Papers Due: December 10th, 2024 - Workshop: January 19th, 2025 For more information you can joint the Google group [https://groups.google.com/g/multilingual-cs-generation-coling2025] or visit our website [https://sites.google.com/view/multilang-counterspeech-gen/home] [https://sites.google.com/view/multilang-counterspeech-gen/shared-task] Best regards, The Multilingual Counterspeech Generation Workshop Organizers.

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Job offer: Researcher in Speech and Natural Language Processing (Junior and Senior Positions)
by Arantza Del Pozo Echezarreta 03 Oct '24

03 Oct '24

*** Apologies for cross-postings *** *Researcher positions in Speech and Natural Language Processing (Junior & Senior Positions) @ Vicomtech, San Sebastian/Bilbao, Spain* Vicomtech (https://www.vicomtech.org/en/), an international applied research centre specialised in Artificial Intelligence, Visual Computing and Interaction located in Spain, has several research positions in the field of speech and natural language processing. We are seeking talented and motivated individuals to join our dynamic Speech and Natural Language Technologies team in either our Donostia - San Sebastián or Bilbao premises. If you have experience in speech and/or natural language processing technologies and are passionate about applying cutting-edge research to solve real-world needs through advanced prototypes, this opportunity is for you! Whether you are a junior researcher (BSc/MSc graduate) looking to kickstart your career or a senior researcher (PhD graduate) eager to take on research leadership roles, we are interested in your profile. We offer the perfect environment with outstanding equipment and the best human team for growth. You will participate in advanced research and development projects, with opportunities to manage high-profile projects and/or lead technical teams depending on your experience. *Key Responsibilities: * - Conduct cutting-edge research in Speech and Natural Language Processing (NLP) technologies such as automatic speech recognition and synthesis, audio deep fake detection, information extraction, machine translation, text simplification and dialogue systems, among others. - Contribute to national and international research projects. - Develop advanced prototypes that transfer technology to businesses and institutions. - Manage or lead research projects, depending on experience. *Requirements: * - Bachelor’s or Master’s degree in Computer Science, Telecommunications Engineering or related fields. - For senior profiles, a PhD in Speech Processing, NLP, AI or related disciplines is preferred. A PhD is not required for junior candidates. - Strong programming skills (Python, Bash). - Fluency in both spoken and written Spanish and English. *Preferred Skills (Not Required but Valued): * - Experience with speech and natural language processing tools and libraries (e.g. Kaldi, Whisper, Marian NMT, HuggingFace Transformers, Rasa, etc.). Deep learning frameworks (Pytorch, Tensorflow, ONNX). - Virtualization technologies (Docker, Kubernetes). - Experience in industrial and/or European research projects. *What We Offer: * - A vibrant, innovative research environment with state-of-the-art AI, Visual Computing, and Interaction technologies. - Exciting national and international research projects. A multidisciplinary and renowned team in Speech and Language Technologies. - Creative freedom in research, aligned with the centre’s goals. - Opportunities for personal development through continuous learning. - Clear career progression paths and leadership opportunities. - Work-life balance policies and a commitment to equal employment opportunities. If you are passionate about research and eager to apply or develop your expertise to real-world challenges, we encourage you to send us your CV and join our forward-thinking team! To apply via LinkedIn: https://www.linkedin.com/jobs/view/4034768411 -- [image: Vicomtech] <https://www.vicomtech.org> Dr. Arantza del Pozo Echezarreta Director of Speech and Natural Language Technologies adelpozo(a)vicomtech.org +(34) 943 30 92 30 +(34) 619 910 422 The information contained in this electronic message is intended only for the personal and confidential use of the recipients. If you have received this e-mail by mistake, please, notify us and delete it. Avoid printing this message if it is not strictly necessary.

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CfP: SemEval task on hallucination detection Mu-SHROOM
by Tiedemann, Jörg 02 Oct '24

02 Oct '24

TL;DR Mu-SHROOM<https://helsinki-nlp.github.io/shroom/> is a non-English-centric SemEval-2025 shared task to advance the SOTA in hallucination detection for content generated with LLMs. We’ve annotated hallucinated content in 10 different languages from top -tier LLMs. Participate in as many languages as you’d like by accurately identifying spans of hallucinated content. Stay informed by joining our Google group<https://groups.google.com/g/semeval-2025-task-3-mu-shroom> or our Slack<https://join.slack.com/t/shroom-shared-task/shared_invite/zt-2mmn4i8h2-HvRB…> or follow our Twitter account<https://x.com/mushroomtask>! Full Invitation We are excited to announce the Mu-SHROOM shared task on hallucination detection (link to website<https://helsinki-nlp.github.io/shroom/>). We invite participants to detect hallucination spans in the outputs of instruction-tuned LLMs in a multilingual context. About This shared task builds upon our previous iteration, SHROOM<https://helsinki-nlp.github.io/shroom/2024>, with three key improvements: LLM-centered, multilingual annotations & hallucination-span prediction. LLMs frequently produce "hallucinations," where models generate plausible but incorrect outputs, while the existing metrics prioritize fluency over correctness. This results in an issue of growing concern as these models are increasingly adopted by the public. With Mu-SHROOM, we want to advance the state-of-the-art in detecting hallucinated content. This new iteration of the shared task is held in a multilingual and multimodel context: we provide data produced by a variety of open-weights LLMs in 10 different languages (Arabic (modern standard), Chinese (Mandarin), English, Finnish, French, German, Hindi, Italian, Spanish, and Swedish). Participants are invited to participate in any of the languages available and are expected to develop systems that can accurately identify and mitigate hallucinations in generated content. As is usual with SemEval shared tasks, participants will be invited to submit system description papers, with the option to present them in poster format during the next SemEval workshop (collocated with an upcoming *ACL conference). Participants that elect to write a system description paper will be asked to review their peers’ submissions (max 2 papers per author) Key Dates: All deadlines are “anywhere on Earth” (23:59 UTC-12). * Dev set available by: 02.09.2024 * Test set available by: 01.01.2025 * Evaluation phase ends: 31.01.2025 * System description papers due: 28.02.2025 (TBC) * Notification of acceptance: 31.03.2025 (TBC) * Camera-ready due: 21.04.2025 (TBC) * SemEval workshop: Summer 2025 (co-located with an upcoming *ACL conference) Evaluation Metrics: Participants will be ranked along two (character-level) metrics: 1. intersection-over-union of characters marked as hallucinations in the gold reference vs. predicted as such 2. how well the probability assigned by the participants' system that a character is part of a hallucination correlates with the empirical probabilities observed in our annotations. Rankings and submissions will be done separately per language: you are welcome to focus only on the languages you are interested in! How to Participate: * Register: Please register your team before making a submission on https://mushroomeval.pythonanywhere.com * Submit results: use our platform to submit your results before 31.01.2025 * Submit your system description: system description papers should be submitted by 28.02.2025 (TBC, further details will be announced at a later date). Want to be kept in the loop? Join our Google group mailing list<https://groups.google.com/g/semeval-2025-task-3-mu-shroom> or the shared task Slack<https://join.slack.com/t/shroom-shared-task/shared_invite/zt-2mmn4i8h2-HvRB…>! You can also follow us on Twitter<https://x.com/mushroomtask>. We look forward to your participation and to the exciting research that will emerge from this task. Best regards, Raúl Vázquez and Timothee Mickus On behalf of all the Mu-SHROOM organizers

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Call for Papers: 1st Workshop on Ecology, Environment, and Natural Language Processing (EcoNLP 2024 at NoDaLiDa/Baltic-HLT 2025)
by Valerio Basile 02 Oct '24

02 Oct '24

We invite submissions to the *1st Workshop on Ecology, Environment, and Natural Language Processing <https://econlpws2025.di.unito.it/>*. This workshop will bring together the NLP community and stakeholders from various disciplines to explore how computational linguistics and NLP tools, methods, and applications can help address pressing climate change and environment-related challenges. We are particularly interested in contributions that push the boundaries of linguistics and NLP research in the context of ecological and environmental crises and that foster interdisciplinary collaboration. The *topics of interests* include, but are not limited to: *Sentiment Analysis of Environmental Topics*: Evaluating public opinions on environmental issues across platforms such as social media, news outlets, and other media (e.g., Bosco et al., 2023 <https://ceur-ws.org/Vol-3596/paper11.pdf>; Ibrohimelmustafaelmustafa et al., 2023 <https://dl.acm.org/doi/pdf/10.1145/3604605>). Automated Linguistic Analysis: Studying grammatical, syntactical and lexical patterns from an ecolinguistic perspective (e.g., Widanti, 2022 <http://influence-journal.com/index.php/influence/article/view/18>), including analyses of corporate environmental reports and other institutional communications (e.g., Gong, 2019 <https://helda.helsinki.fi/server/api/core/bitstreams/5a38650d-71c2-4a62-a33…> ). Detection of Anthropocentric and Speciesist Biases Identifying harmful biases in language and NLP applications, and developing methods to mitigate them (e.g., Leach et al., 2021 <https://bpspsychub.onlinelibrary.wiley.com/doi/pdfdirect/10.1111/bjso.12561>; Takeshita et al., 2022 <https://www.sciencedirect.com/science/article/pii/S0306457322001558?casa_to…> ). *Topic Modeling & Discourse/Frame Analysis*: Investigating how environmental issues are framed in media and political discourse and how these frames influence public perception and policymaking (e.g., Dehler-Holland et al., 2021 <https://www.sciencedirect.com/science/article/pii/S2666389920302336>). *Geo-tagging and sentiment mapping of environmental discussions*: Mapping environmental discussions and sentiments across geographical locations (e.g., Yao & Wang, 2020). *Ecofeminism, environmental justice, and language*: Exploring the intersections of gender, justice, and ecological narratives, and how NLP can help analyze language in these contexts. *Text Classification in Environmental Contexts*: Categorizing texts into specific environmental subfields such as biodiversity, climate change, and conservation, and using NLP to monitor compliance with environmental regulations (e.g., Schimanski et al., 2023 <https://aclanthology.org/2023.emnlp-main.975.pdf>; Grasso & Locci, 2024 <https://link.springer.com/chapter/10.1007/978-3-031-70242-6_29>). Entity Recognition, Relation Extraction, and Environmental Monitoring Identifying and tracking mentions of species, habitats, pollutants, and ecological phenomena in text (e.g., Abdelmageed et al., 2022). Fact-checking & Greenwashing Detection Analyzing corporate sustainability reports for accuracy and detecting greenwashing practices (e.g., Moodaley & Telukdarie, 2023 <https://www.mdpi.com/2071-1050/15/2/1481>; Cojoianu et al., 2020 <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3627157>). Further topics include: - Ecolinguistic applications of NLP. - Large Language Models (LLMs) application in Climata Change and Environmental domain. - Analyzing Social Media for Harmful Environmental Narratives. - Corpora creation and annotation. - Fairness and ethics in environmental data analysis. - Environmental communication in low-resource languages. - Multimodal analysis for ecological and environmental challenges. - Lexical analysis in the context of sustainability and environmental discourse. - Linked Data and Knowledge Graphs on ecological topics. - Language diversity and inclusion in environmental narratives. - Cognitive models and ecological narratives. - NLP for understanding indigenous knowledge in environmental contexts. - Machine learning techniques for analyzing environmental communication. - NLP for tracking environmental legislation and policy discourse. - NLP for analyzing environmental education and awareness campaigns. - Speech recognition technologies to support ecological field research; - Development of educational chatbots or FAQs for raising environmental awareness. Key Dates - *Paper Submission Deadline*: December 16, 2024 - *Notification of Acceptance*: TBA - *Camera-Ready Deadline*: February 3, 2025 - *Workshop Date*: March 2, 2025 *Submission Instructions:* The workshop will accept *archival* submissions, *non-archival* submissions, as well as *research communications* . *Non-archival submissions* refer to new work that will not appear in the proceedings, while *research communications* consist of work already published at other venues (e.g., conferences, journals) that can be presented at the workshop but will not be included in the proceedings. Submissions should follow the *NoDaLiDa/Baltic-HLT 2025 <https://www.nodalida-bhlt2025.eu/call-for-papers> *formatting templates and guidelines; We invite paper submissions of three types: - Regular paper (up to 8 pages) - Short papers (up to 4 pages) - Demo papers (up to 4 pages) For all three submission types, these page limits do not include additional pages with bibliographic references. We do not allow any extra pages for appendices. *Submission and reviewing* will be conducted through *OpenReview* (link to submission TBA) All submissions will undergo *double-blind peer review*, adhering to professional standards.

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Extended Deadline - October 4 - ACM SAC 2025 - Knowledge and Natural Language Processing Track
by Patrizio Bellan 02 Oct '24

02 Oct '24

The 40th ACM/SIGAPP Symposium on Applied Computing ACM SAC 2025 March 31 - April 4, 2025 - Catania, Italy Knowledge and Natural Language Processing Track ***************************************** Important Dates Author deadline for submissions: September 20, 2024 October 4, 2024 Author notification of acceptance: October 30, 2024 Author camera ready and registration due: November 29, 2024 ***************************************** Aim Aim of the Knowledge and Natural Language Processing (KNLP) track at ACM SAC is to investigate techniques and application of knowledge engineering and natural language processing, two extremely interdisciplinary and lively research areas at the core of Artificial Intelligence. In particular, the track welcomes contributions combining and complementing methods and approaches from both areas. Topics of interest include, but are not limited to: - Natural Language Processing NLP tasks for Knowledge Extraction NLP for Ontology Population and Learning Sentiment Analysis and Opinion Mining for Knowledge Applications Interplay between Language and Ontologies NLP for Explainable Knowledge Machine Translation techniques for Multi-lingual Knowledge NLP for the Web (Large) Language Models and Knowledge - Knowledge Knowledge to improve NLP tasks Knowledge for Information Retrieval Knowledge-based Sentiment Analysis and Opinion Mining Combining Knowledge and Deep Learning for NLP Knowledge for Text Summarization and Generation Knowledge for Persuasion Knowledge-based Machine Translation Knowledge for the Web Linked Data for NLP Knowledge-based NL Explainability RAG and Knowledge injection for Language Models - Applications Real-world applications that exploit Knowledge and NLP Knowledge and NLP Systems for Big Data scenarios Knowledge and NLP technology for diverse, equitable, and inclusive society Deployment of Knowledge and NLP Systems in specific domains, such as: Digital Humanities and Social Sciences eGovernment and public administration Life sciences, health and medicine News and Data Streaming ***************************************** Paper Submission Research papers and experience reports related to the above topics are solicited. Submissions must not have been published or be concurrently considered for publication elsewhere. Papers should be submitted in PDF using the ACM-SAC proceedings format using the submission link on the SAC 2025 website (https://www.google.com/url?q=https://www.sigapp.org/sac/sac2025/&source=gma…). Authors' names and affiliations should be entered separately at the submission site and not appear in the submitted papers. Each submission will be reviewed in a DOUBLE-BLIND process according to the ACM-SAC Regulations. Student Research Competition (SRC) submissions are welcome (see SAC 2025 website for details). Full papers are limited to 8 pages, in camera-ready format, included in the registration fee. Authors have the option to include up to two (2) extra pages (paying an extra charge). Posters are limited to 2 pages, in camera-ready format, included in the registration fee. Authors have the option to include only one (1) extra page (paying an extra charge). SRC Abstracts are limited to 3 pages, in camera-ready format, included in the registration fee. No extra pages are allowed. Paper selection is based on originality, technical contribution, presentation quality, and relevance to the Knowledge and Natural Language Processing Track. Some papers may be accepted as posters. Paper registration is required, allowing the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for the paper/poster to be included in the ACM digital library. No-show of registered papers and posters will result in excluding them from the ACM digital library. ***************************************** Track Co-Chairs Patrizio Bellan, Fondazione Bruno Kessler (FBK) Marco Bombieri, Università degli Studi di Verona Mauro Dragoni, Fondazione Bruno Kessler (FBK) Marco Rospocher, Università degli Studi di Verona ***************************************** Programme Committee TBA ***************************************** General Inquiries For further information, please visit SAC Knowledge and Natural Language Processing Track (https://www.google.com/url?q=https://knlp-sac.github.io/2025/&source=gmail-…) and SAC 2024 conference websites (https://www.google.com/url?q=https://www.sigapp.org/sac/sac2025/&source=gma…) or feel free to contact the Track Co-Chairs at knlp(a)fbk.eu<mailto:knlp@fbk.eu> . -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all'indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material. -=-=-=-=-=-=-=-=-=-=-=- Groups.io Links: You receive all messages sent to this group. View/Reply Online (#973): https://www.google.com/url?q=https://isal.groups.io/g/announce/message/973&… Mute This Topic: https://www.google.com/url?q=https://groups.io/mt/108555270/8769941&source=… Group Owner: announce+owner(a)isal.groups.io Unsubscribe: https://www.google.com/url?q=https://isal.groups.io/g/announce/unsub&source… [pbellan(a)fbk.eu] -=-=-=-=-=-=-=-=-=-=-=- -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all'indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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ENEOLI Survey on Studying and Documenting Neologisms
by Kris Heylen 02 Oct '24

02 Oct '24

Dear colleague, working on lexical innovation and neologisms, We kindly invite you to participate in the following survey on neology: https://1ka.arnes.si/eneoli. This survey is being conducted as part of the European Network on Lexical Innovation (ENEOLI<https://eneoli.eu/>) Cost Action CA22126. Its objective is to gather insights into the methods, practices, tools, and resources used in neology, the study of lexical innovations, including both neologisms (new words or expressions) and new senses of existing words. The survey is intended for research groups, individual researchers, and language specialists involved in this field. It is organized around specific projects or research topics, which may include resource creation in lexicography and terminology, software development for neology tracking, or academic research in lexicology, linguistics, and translation studies. Additionally, a section is dedicated to teaching and training practices related to neology. The survey will be available for responses until November 1. The results will be disseminated through open-access scientific publications. At the end of the survey, you will have the option to indicate whether you would like to be acknowledged as a contributor. Best regards, On behalf of the ENEOLI action, Kris Heylen Dr. Kris Heylen senior onderzoeker/taalkundige (senior researcher/linguist) /instituut voor de Nederlandse taal/ (Dutch Language Institute) Postbus 9515 / 2300 RA / Leiden / Nederland (The Netherlands) Tel.+32 475844166 Email: kris.heylen(a)ivdnt.org<mailto:kris.heylen@ivdnt.org> Website: https://ivdnt.org/profile/?smid=5921 Google Scholar profile<https://scholar.google.com/citations?hl=nl&user=aKUjl4sAAAAJ&view_op=list_w…> ________________________________ Denk je aan het milieu? Print alleen als het nodig is. Aan dit bericht kunnen geen rechten worden ontleend. Het bericht is alleen bestemd voor de geadresseerde. Indien het bericht niet voor u is bestemd, verzoeken wij u dit aan ons te melden en het bericht te verwijderen. This message shall not constitute any obligations. This message is intended solely for the addressee. If you have received this message in error, please inform us and delete the message. ________________________________

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2026

2025

2024

2023

2022