- Corpora - ELRA lists

Second Call for Task Proposals: PAN 2023 "Profiling Cryptocurrency Influencers with Few-shot Learning"
by mara.chinea＠symanto.com 23 Mar '23

23 Mar '23

Apologies for cross-posting. ---------------------------------------- We kindly invite you to participate at the Pan-2023 Task 2 - “Profiling Cryptocurrency Influencers with Few-Shot Learning”. This task is being held as part of CLEF 2023, and all participating teams will be able to publish their system description paper at the CLEF proceedings. This shared task focuses on the author profiling of cryptocurrency influencers in social media from a low-resource perspective, that is, with little training data. Moreover, we propose to profile types of influencers also using a low-resource setting. Specifically, we focus on English Twitter posts for three different sub-tasks: • Low-resource influencer profiling (subtask-1): profile authors according to their degree of influence (null, nano, micro, macro, mega). • Low-resource influencer interest profiling (subtask-2): profile authors according to their main interests or areas of influence (technical information, price update, trading matters, gaming, other). • Low-resource influencer intent profiling (subtask-3): profile authors according to the intent of their messages (subjective opinion, financial information, advertising, announcement). Important Links • Task Website - https://pan.webis.de/clef23/pan23-web/author-profiling.html • Dataset site - https://zenodo.org/record/7701748#.ZBxxrnbMKiM Important Dates • February 20, 2023: Training data ready • May 10, 2023: Early bird software submission phase (optional) • May 29, 2023: Software submission deadline • June 05, 2023: Participant paper submission • September 18-21, 2023: Conference Task organizers • Francisco Rangel (Symanto) • Mara Chinea-Rios (Symanto) - Contact Email: mara.chinea(a)symanto.com • Marc Franco-Salvador (Symanto) • Paolo Rosso (Universidad Politécnica de Valencia) Please reach out to the organizers at crypto-influencers-pan-organizers(a)googlegroups.com, or join the Slack workspace (https://pan2023profil-0q48349.slack.com) to connect with the other participants and organizers.

1 0

Lecturer in Computational Linguistics, University of Manchester
by Colin Bannard 23 Mar '23

23 Mar '23

The University of Manchester is hiring a Lecturer (UK equivalent to Assistant Professor) in Computational Linguistics, to be based in the Department of Linguistics and English Language. It is a permanent post. Applications are welcome from people working in all areas of Natural Language Processing. More information on the position and how to apply can be found here: https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=24945 The closing date for applications is April 24th 2023. Best, Colin

1 0

[meetings] Call for Participation: Communication in Human-AI Interaction" (CHAI) Workshop @Interact 2023
by Marta Romeo 23 Mar '23

23 Mar '23

This full-day "Communication in Human-AI Interaction" (CHAI) workshop welcomes submissions of position papers (8 pages maximum in Springer LNCS format). The workshop will be held as part of the *INTERACT 23 conference* (Aug 28 - Sep 1, York, UK and online, https://interact2023.org/). It will be organized as an interactive work group event, including a design activity and group discussions. Important dates and links * Paper deadline: April 28, 2023 AoE * Notification: May 19, 2023 * Workshop date: between August 28 and September 1, 2023 (TBD) * Workshop website:https://chai-workshop.github.io/ * Submission website:https://easychair.org/conferences/?conf=chai23 *Goal and topics:* Human interactions with AI systems are becoming part of our everyday life. If designed and developed efficiently, these interactions have great potential to enhance human work, abilities, and well-being. Communication, here is the iterative process of establishing shared meaning, is a crucial aspect of successful interaction and has been studied for years, from HCI, AI, and cognitive sciences points of view, among others. The goal of this workshop is to bring together experts from HCI, AI, and Cognitive Sciences to explore and understand the specificities and characteristics of communication in human-AI interactions, as well as the salient principles, methods, and theories one has to consider to build meaningful human-AI communication systems. Topics of interest include but are not limited to: * Blended social contexts, comprising both human and technological communication * Communication in multi-user interaction with intelligent agents * Verbal and non-verbal human-AI communication * Explicit and implicit human-AI communication * Rules of etiquette and social norms in human-AI communication * Communication in human-AI collaboration * Human-AI communication design * Language and communication * Theory of Mind * Common ground * Inclusion and Diversity in Human-AI Communication * Embodied multi-modal communication between humans and physical robots *Format:* The workshop will be a one-day event, envisioned as a collaborative thinking group activity focusing on the challenges surrounding Communication in Human-AI Interaction. The workshop aims at being interactive and will consist of two main parts. First, participants will be invited to collaborate on a design activity. For this activity, participants will be grouped as best as possible by topics and each group will be given the same challenge: analyzing and suggesting a solution to an HAI communication problem. At the end of the activity, each group will report on their solution. Second, we will have group discussions in two phases, for which groups will be shuffled to be cross-disciplinary. Each group will be given a separate topic. The goal of each group will be to identify common interests, open questions, and challenges related to this topic. The groups are shuffled between phases, and participants are encouraged to build on top of the previous groups’ discussion. Each discussion phase will be followed by a quick report of each group. The day will end by a longer plenary discussion during which we will also outline the after-workshop steps. The design activity problem and the discussion topics will be chosen following participants submissions so that they align with the expertise and interest of the workshop participants. By the end of the workshop, we expect to be as close as possible to a common agreement about an outline for the coordinated research agenda, including key points to explore further. Post-workshop, the results will be communicated to a larger audience through various activities, to be synchronized with the participants. *Submission Requirements:* We welcome interested participants to submit position papers stating existing work, conceptual design, or their position with respect to the workshop topics. The submission should also include one or two points of discussion that the participant would like to address during the workshop. Submissions should be made through EasyChair ( https://easychair.org/conferences/?conf=chai23) and be formatted according to the Springer LNCS format, templates available for LaTeX and Word, maximum 8 pages. We strongly encourage authors of position papers to follow the SIGCHI accessibility guidelines. Workshop organizers Jennifer Renoux, Örebro University, Sweden Jasmin Grosinger, Örebro University, Sweden Marta Romeo, Heriot-Watt University, UK Victor Kaptelinin, Umeå University, Sweden Antti Oulasvirta, Aalto University, Finland Contact information Workshop website:https://chai-workshop.github.io/ For inquiries about the workshop, please contact: jennifer.renoux(a)oru.se

1 0

Call-for-Participation: 1st GANs Task @ ImageCLEF 2023 (Synthetic Medical Images)
by Bogdan Ionescu 23 Mar '23

23 Mar '23

[Apologies for multiple postings] ImageCLEFmedicalGANs (1st edition) Registration: https://www.imageclef.org/2023/medical/gans Run submission: May 10, 2023 Working notes submission: June 5, 2023 CLEF 2023 conference: September 18-21, Thessaloniki, Greece *** CALL FOR PARTICIPATION *** The task is focused on examining the existing hypothesis that GANs are generating medical images that contain the "fingerprints" of the real images used for generative network training. If the hypothesis is correct, artificial biomedical images may be subject to the same sharing and usage limitations as real sensitive medical data. On the other hand, if the hypothesis is wrong, GANs may be potentially used to create rich datasets of biomedical images that are free of ethical and privacy regulations. The participants will test the hypothesis by solving one or several tasks related to the detection of relations between real and artificial biomedical image datasets. *** TASK *** Given a set of real-world medical images comprising 2D axial CT image slices of the heart (including the middle sections and adjacent slices) of patients afflicted with lung #tuberculosis, the task challenges participants to develop #machinelearning solutions to automatically determine which real images were used in training the generator of realistic synthetic examples. *** DATA SET *** The image datasets comprise 2D axial CT image slices of the heart, including the middle sections of the heart and adjacent slices. These images are obtained from patients afflicted with Lung Tuberculosis and are stored in the form of 8 bit/pixel PNG images with dimensions of 256x256 pixels. The development dataset comprises three distinct sets of images. One set contains images that were generated using a GAN, while the other two sets are comprised of real images. The first of these real image sets contains images that were used during the algorithm's training process. The second set consists of real images that were not used during the training process. Test dataset is a collection of two image sets. The first set contains 10,000 images that have been generated, while the second set is made up of a combination of 200 real images that were either used or unused during the training process. *** IMPORTANT DATES *** - Run submission: May 10, 2023 - Working notes submission: June 5, 2023 - CLEF 2023 conference: September 18-21, Thessaloniki, Greece (https://clef2023.clef-initiative.eu/) *** OVERALL COORDINATION *** Serge Kozlovski, Belarusian Academy of Sciences, Belarus Vassili Kovalev, Belarusian Academy of Sciences, Belarus Ihar Filipovich, Belarus State University, Belarus Alexandra Andrei, Politehnica University of Bucharest, Romania Ioan Coman, Politehnica University of Bucharest, Romania Bogdan Ionescu, Politehnica University of Bucharest, Romania Henning Müller, University of Applied Sciences Western Switzerland, Switzerland *** ACKNOWLEDGEMENT *** Alexandra Andrei, Ioan Coman, Bogdan Ionescu, and Henning Müller contribution is supported under the H2020 AI4Media "A European Excellence Centre for Media, Society and Democracy" project, contract #951911 https://www.ai4media.eu/. On behalf of the Organizers, Bogdan Ionescu https://www.AIMultimediaLab.ro/

1 0

Workshop on Language Corpora in Australia -- 3 July 2023 (online, via Zoom)
by li.nguyen＠anu.edu.au 23 Mar '23

23 Mar '23

3 July 2023 (online, via Zoom) Organisers: Catherine Travis & Li Nguyen (ANU; Language Data Commons of Australia (LDaCA)) Over decades of work in Australia, significant collections of language data have been amassed, including of varieties of Australian English, Australian migrant languages, Australian Indigenous languages, sign languages and others. These collections represent a trove of knowledge not only of language in Australia, but also of Australia’s social and cultural history. And yet, not all are well known and many lack published descriptions. The purpose of this workshop is to provide an opportunity to share information about existing language corpora in Australia, with a view to producing a special issue of the Australian Journal of Linguistics that introduces a selection of these corpora, explores how they can contribute to our understanding of language, society, and history in Australia, and considers avenues that such corpora open up for future research. This workshop is being run as part of the Language Data Commons of Australia (LDaCA), which is working to build national research infrastructure for the Humanities and Social Sciences, facilitating access to and use of digital language corpora for linguists, scholars across the Humanities and Social Sciences, and non-academics. Abstract submission For a 20 min presentation, please submit a 250-300 word abstract in English (excluding references). The presentation should include the following information: · Speech community/fieldsite: Describe the location of the community and/or their brief history in Australia, the languages spoken and their current status. · Corpus design principles: Specify the sample size, sociolinguistic background of the participants, method of data collection and/or genre (e.g. sociolinguistic interviews, natural conversations, oral histories, elicited data, etc.); data format (written/spoken/audio/video, etc.) and where it is stored. · Corpus findings and implications: Summarise some key findings from the corpus and discuss other insights that might be obtained from the data in current or future work. Important dates 22 May Abstracts due 5 June Notification of acceptance 3 July Workshop How to Submit: Please submit your abstract by 22 May on https://forms.gle/1pwxVVmUV5hCCZ997 Inquiries: Please contact either Catherine Travis or Li Nguyen

1 0

Training set released! IberLEF 2023 Task - FinancES. Financial Targeted Sentiment Analysis in Spanish
by Rafael Valencia Garcia 23 Mar '23

23 Mar '23

CALL FOR PARTICIPATION IBERLEF 2023 Task - FinancES. Financial Targeted Sentiment Analysis in Spanish Training set released! Held as part of iberLEF 2023 <https://sites.google.com/view/iberlef-2023>, a shared evaluation campaign for Natural Language Processing (NLP) systems in Spanish and other Iberian languages September 26th 2023, Jaen Codalab link: https://codalab.lisn.upsaclay.fr/competitions/10052 Dear All, We are inviting researchers and students to participate in the shared-task FinancES. Financial Targeted Sentiment Analysis in Spanish held as part of iberLEF 2023, shared evaluation campaign for Natural Language Processing (NLP) systems in Spanish and other Iberian languages. This shared task aims to explore targeted sentiment analysis in the financial domain. Specifically, the approach adopted here is grounded in the field of microeconomics. In this regard, Bowles (2004) explains the role of economic agents, that is to say, individuals or organizations impacting the economy. The author states that the main microeconomic agents in the capital market are consumers (households/individuals), companies (firms), governments, and central banks. Consequently, in order to develop a sentiment analysis method where different viewpoints are considered, three different perspectives are included: (1) economic target of the news item; (2) individual economic agent: companies; and (3) individual economic agent: consumers –the target is the sector where the economic fact applies, and companies produce the goods and services that households/individuals consume. From these three viewpoints, the news item has an impact on the target and the economic agents which are considered as positive, negative, or neutral. With all, two tasks are proposed. On the one hand, a task combining the challenges of aspect-term extraction for identifying the target entity in text, and aspect-based sentiment classification for determining the sentiment polarity towards the target. On the other hand, a task devoted to assessing the impact of a news headline on both other economic agents, namely, companies and consumers. The participants will be provided development, development_test, training and test datasets in Spanish. The dataset for this task is composed of news headlines written in Spanish collected from digital newspapers specialized in economic, financial and political news. The dataset is labeled with the target entity and the sentiment polarity on three dimensions: target, companies, and consumers. That is, given a headline, it has been manually classified as positive, neutral, or negative for three specific entities: (1) target entity (i.e., the specific company or asset where the economic fact applies), (2) companies (i.e., the entities producing the goods and services that others consume), and (3) consumers (i.e., households/individuals). Each headline was annotated by three members of the organization committee. In case of disagreement, the annotators discussed the special case and, if no agreement was reached, the headline was discarded. During this first step, we compiled about 14k headlines, the headlines with a short length or those that did not specify a target entity were filtered out. The final dataset is composed of 8k-10k news headlines. For the shared tasks, training and test sets will be released (80%-20%). Today, we have released the training dataset that can be found in the "Files" subsection of the "Participate" tab. It is worth mentioning that this dataset includes all the instances that were also released during the Practice stage; so, it is not needed to combine both datasets. Finally, remember that the CodaLab competition is open to submit your results with the development dataset provided. This dataset is also available in the same section as the training dataset. Best regards, The FinancES 2023 organizing committee References - Bowles, S. (2004). Microeconomics: Behavior, institutions, and evolution. Princeton University Press. Important dates - Release of development corpora: Feb 13, 2023 - Release of training corpora: Mar 13, 2023 - Release of test corpora and start of evaluation campaign: Apr 17, 2023 - End of evaluation campaign (deadline for runs submission): May 3, 2023 - Publication of official results: May 5, 2023 - Paper submission: May 28, 2023 - Review notification: Jun 16, 2023 - Camera ready submission: Jul 6, 2023 - IberLEF Workshop (SEPLN 2023): Sep 26, 2023 - Publication of proceedings: Sep ??, 2023 Organizing committee - José Antonio García-Díaz (UMUTeam,, Universidad de Murcia) - Ángela Almela Sánchez-Lafuente (UMUTeam, Universidad de Murcia) - Francisco García-Sánchez (UMUTeam, Universidad de Murcia) - Gema Alcaraz-Mármol (UMUTeam, Universidad de Castilla La Mancha) - María José Marín (UMUTeam, Universidad de Murcia) - Rafael Valencia-García (UMUTeam, Universidad de Murcia)

1 0

PhD Position in Conversational AI / NLP in St. Gallen, Switzerland
by Niklaus, ChristinaMarianne 23 Mar '23

23 Mar '23

The Chair of Data Science and Natural Language Processing (Prof. Siegfried Handschuh) invites applications for a PhD position as part of the recently granted Swiss National Science Foundation (SNF) research project "Conversational AI: Dialogue-based Adaptive Argumentative Writing Support". You will contribute to its successful implementation, as well as the chair's varied activities in teaching and outreach. Our research at the Data Science and NLP Chair at ICS-HSG focuses on the cutting-edge field of Natural Language Processing (NLP) and Natural Language Understanding (NLU). Our group delves into various aspects, including conversational AI, Large Language Models (LLM), intricate language analysis, Knowledge Graphs and more. Utilising sophisticated methods and algorithms, we aim to extract deeper knowledge and understanding from vast amounts of textual and auditory data. Our research not only delves into the core principles of NLP but also explores its practical applications across various industries. Details of the post and how to apply: https://bit.ly/phd_conversational_ai HSG: PhD in Conversational AI (m/f/d)<https://bit.ly/phd_conversational_ai> You have a university-level master degree in Computer Science, Computational Linguistics, Data Science or related disciplines. You have a strong background in Machine Learning and Natural Language Processing; knowledge of Deep Learning architectures (e.g., Transformer, BERT) and frameworks (e.g., PyTorch, Tensorflow) is a plus. You have good programming skills in Python. Desirable qualifications include one or more of the following areas: Chatbots, Argument Mining and Text Generation. You have excellent written and verbal communication skills in English. You have a strong analytical, structured and independent working style, as well as first experience in writing scientific papers. bit.ly -- Prof. Dr. Siegfried Handschuh Full Professor of Data Science and Natural Language Processing Director, Institute of Computer Science University of St.Gallen E-mail: siegfried.handschuh(a)unisg.ch

1 0

Invitation NLP Challenge day
by Nissa 23 Mar '23

23 Mar '23

Hi, this is an invitation to attend the NLP challenge day organized by CERIST, Algeria on March 29, 2023. The link to attend the event is: https://visioconf.cerist.dz/CERISTNLPChallenge The program is available at: http://www.nlpchallenge.cerist.dz/ Thank you. Best regards. Hassina Aliane. *Dr. Hassina Aliane, Direcctor of Research* *Head of Natural Language Processing and Digital Content Team,* *Director of the Digital Humanities R&D laboratory, * *Editor of the Information Processing at The Digital Age Review. * *Research Center on Scientific and Technical Information.*

1 0

CFP: 6th Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL)
by d.odekerken＠uu.nl 23 Mar '23

23 Mar '23

The 6th ASAIL workshop, focused on Natural Language Processing for legal texts and co-located with ICAIL 2023 in Braga, Portugal, is coming up soon. We would like to invite you to submit papers on, and demonstrations of, original work on automated detection, extraction and analysis of semantic information in legal texts. Submission deadline: 26th April 2023 Workshop date: 23rd June 2023 We are accepting three tiers of (two column format) papers: long (10 pages); short (6 pages); and position (2 pages). Since we are very interested in sparking discussion around ideas and work in their early stages, we welcome short and position papers as particularly suitable for this ambition. You can find more information, including the full call for papers, at our website: https://sites.google.com/view/asail/asail-2023-call-for-papers Best wishes, Daphne Odekerken On behalf of the ASAIL Organising Committee

1 0

Second Call for Task Proposals: SemEval-2024
by Atul K. Ojha 22 Mar '23

22 Mar '23

Apologies for cross-posting. ---------------------------------------- We invite proposals for tasks to be run as part of SemEval-2024 <https://semeval.github.io/SemEval2024/>. SemEval (the International Workshop on Semantic Evaluation) <https://semeval.github.io/>is an ongoing series of evaluations of computational semantics systems, organized under the umbrella of SIGLEX <https://siglex.org/>, the Special Interest Group on the Lexicon of the Association for Computational Linguistics. SemEval tasks explore the nature of meaning in natural languages: how to characterize meaning and how to compute it. This is achieved in practical terms, using shared datasets and standardized evaluation metrics to quantify the strengths and weaknesses and possible solutions. SemEval tasks encompass a broad range of semantic topics from the lexical level to the discourse level, including word sense identification, semantic parsing, coreference resolution, and sentiment analysis, among others. For SemEval-2024, we welcome any task that can test an automatic system for the semantic analysis of text, which could be an intrinsic semantic evaluation or an application-oriented evaluation. We especially encourage tasks for languages other than English, cross-lingual tasks, and tasks that develop novel applications of computational semantics. See the websites of previous editions of SemEval to get an idea about the range of tasks explored, SemEval-2022 <https://semeval.github.io/SemEval2022/> and SemEval-2023 <https://semeval.github.io/SemEval2023/>. We strongly encourage proposals based on pilot studies that have already generated initial data, as this can provide concrete examples and can help to foresee the challenges of preparing the full task. In the event of receiving many proposals, preference will be given to proposals that have already run a pilot study. In case you are not sure whether a task is suitable for SemEval, please feel free to get in touch with the SemEval organizers at semevalorganizers(a)gmail.com to discuss your idea. === Task Selection === Task proposals will be reviewed by experts, and reviews will serve as the basis for acceptance decisions. Everything else being equal, more innovative new tasks will be given preference over task reruns. Task proposals will be evaluated on: - Novelty: Is the task on a compelling new problem that has not been explored much in the community? Is the task a rerun, but covering substantially new ground (new subtasks, new types of data, new languages, etc.)? - Interest: Is the proposed task likely to attract a sufficient number of participants? - Data: Are the plans for collecting data convincing? Will the resulting data be of high quality? Will annotations have meaningfully high inter-annotator agreements? Have all appropriate licenses for use and re-use of the data after the evaluation been secured? Have all international privacy concerns been addressed? Will the data annotation be ready on time? - Evaluation: Is the methodology for evaluation sound? Is the necessary infrastructure available or can it be built in time for the shared task? Will research inspired by this task be able to evaluate in the same manner and on the same data after the initial task? - Impact: What is the expected impact of the data in this task on future research beyond the SemEval Workshop? === New Tasks vs. Task Reruns === We welcome both new tasks and task reruns. For a new task, the proposal should address whether the task would be able to attract participants. Preference will be given to novel tasks that have not received much attention yet. For reruns of previous shared tasks (whether or not the previous task was part of SemEval), the proposal should address the need for another iteration of the task. Valid reasons include: a new form of evaluation (e.g. a new evaluation metric, a new application-oriented scenario), new genres or domains (e.g. social media, domain-specific corpora), or a significant expansion in scale. We further discourage carrying over a previous task and just adding new subtasks, as this can lead to the accumulation of too many subtasks. Evaluating on a different dataset with the same task formulation, or evaluating on the same dataset with a different evaluation metric, typically should not be considered a separate subtask. === Task Organization === We welcome people who have never organized a SemEval task before, as well as those who have. Apart from providing a dataset, task organizers are expected to: - Verify the data annotations have sufficient inter-annotator agreement - Verify licenses for the data to allow its use in the competition and afterwards. In particular, text that is publicly available online is not necessarily in the public domain; unless a license has been provided, the author retains all rights associated with their work, including copying, sharing and publishing. For more information, see: https://creativecommons.org/faq/#what-is-copyright-and-why-does-it-matter - Resolve any potential security, privacy, or ethical concerns about the data - Make the data available in a long-term repository under an appropriate license, preferably using Zenodo: https://zenodo.org/communities/semeval/ - Provide task participants with format checkers and standard scorers. - Provide task participants with baseline systems to use as a starting point (in order to lower the obstacles to participation). A baseline system typically contains code that reads the data, creates a baseline response (e.g. random guessing, majority class prediction), and outputs the evaluation results. Whenever possible, baseline systems should be written in widely used programming languages and/or should be implemented as a component for standard NLP pipelines. - Create a mailing list and website for the task and post all relevant information there. - Create a CodaLab or other similar competition for the task and upload the evaluation script. - Manage submissions on CodaLab or a similar competition site. - Write a task description paper to be included in SemEval proceedings, and present it at the workshop. - Manage participants’ submissions of system description papers, manage participants’ peer review of each others’ papers, and possibly shepherd papers that need additional help in improving the writing. - Review other task description papers. === Important dates === - Task proposals due April 17, 2023 (Anywhere on Earth) - Task selection notification May 22, 2023 === Preliminary timetable === - Sample data ready July 15, 2023 - Training data ready September 1, 2023 - Evaluation data ready December 1, 2023 (internal deadline; not for public release) - Evaluation starts January 10, 2024 - Evaluation end by January 31, 2024 (latest date; task organizers may choose an earlier date) - Paper submission due February 2024 - Notification to authors on March 2024 - Camera-ready due April 2024 - SemEval workshop Summer 2024 (co-located with a major NLP conference) Tasks that fail to keep up with crucial deadlines (such as the dates for having the task and CodaLab website up and dates for uploading samples, training, and evaluation data) may be cancelled at the discretion of SemEval organizers. While consideration will be given to extenuating circumstances, our goal is to provide sufficient time for the participants to develop strong and well-thought-out systems. Cancelled tasks will be encouraged to submit proposals for the subsequent year’s SemEval. To reduce the risk of tasks failing to meet the deadlines, we are unlikely to accept multiple tasks with overlap in the task organizers. === Submission Details === The task proposal should be a self-contained document of no longer than 3 pages (plus additional pages for references). All submissions must be in PDF format, following the ACL template <https://github.com/acl-org/acl-style-files>. Each proposal should contain the following: - Overview - Summary of the task - Why this task is needed and which communities would be interested in participating - Expected impact of the task - Data & Resources - How the training/testing data will be produced. Please discuss whether existing corpora will be re-used. - Details of copyright, so that the data can be used by the research community both during the SemEval evaluation and afterwards - How much data will be produced - How data quality will be ensured and evaluated - An example of what the data would look like - Resources required to produce the data and prepare the task for participants (annotation cost, annotation time, computation time, etc.) - Assessment of any concerns with respect to ethics, privacy, or security (e.g. personally identifiable information of private individuals; potential for systems to cause harm) - Pilot Task (strongly recommended) - Details of the pilot task - What lessons were learned and how these will impact the task design - Evaluation - The evaluation methodology to be used, including clear evaluation criteria - For Task Reruns - Justification for why a new iteration of the task is needed (see criteria above) - What will differ from the previous iteration - Expected impact of the rerun compared with the previous iteration - Task organizers - Names, affiliations, email addresses - (optional) brief description of relevant experience or expertise - (if applicable) years and task numbers, of any SemEval tasks you have run in the past Proposals will be reviewed by an independent group of area experts who may not have familiarity with recent SemEval tasks, and therefore all proposals should be written in a self-explanatory manner and contain sufficient examples. The submission webpage is: https://openreview.net/group?id=aclweb.org/ACL/2023/Workshop/SemEval === Chairs === Atul Kr. Ojha, SFI Insight Centre for Data Analytics, DSI, University of Galway A. Seza Doğruöz, Ghent University Giovanni Da San Martino, University of Padua Harish Tayyar Madabushi, The University of Bath Ritesh Kumar, Dr. Bhimrao Ambedkar University Contact: semevalorganizers(a)gmail.com

1 0

2025

2024

2023

2022