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Webminar by Xiang Ren (University of Southern California - USC)
by HiTZ zentroa 29 Sep '22

29 Sep '22

**** We apologize for the multiple copies of this email. In case you are already registered to the next webinar, you do not need to register again. **** Dear colleague, We are happy to announce the next webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). We are organizing one seminar every month. You can check the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars Next webinar: * *Speaker*: Xiang Ren (University of Southern California - USC) * *Title*: Commonsense Reasoning in the Wild * *Date*: October 6, 2022, 17:00 CET * *Summary*: Current NLP systems impress us by achieving close-to-human performance on benchmarks of answering commonsense questions or writing interesting stories. However, most of the progress is evaluated using static, closed-ended datasets created for individual tasks. To deploy commonsense reasoning services in the wild, we look to develop and evaluate systems that can generate answers in an open-ended way, perform robust logical reasoning, and generalize across diverse task formats, domains, and datasets. In this talk I will share our effort on introducing new formulations of commonsense reasoning challenges and novel evaluation protocols, towards broadening the scope in approaching machine common sense. We hope that such a shift of evaluation paradigm would encourage more research on externalizing the model reasoning process and improving model robustness and cross-task generalization. * *Upcoming webinars*: o Incorporating Commonsense Reasoning into NLP Models -- Vered Shwartz (November 3, 2022) o Title to be announced -- Maarit Koponen (December 1, 2022) Check past and upcoming webinars at the following url: http://www.hitz.eus/webinars If you are interested in participating, please complete this registration form: http://www.hitz.eus/webinar_izenematea If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info Best wishes, HiTZ Zentroa

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Two research positions in University of Edinburgh MT group
by Barry Haddow 29 Sep '22

29 Sep '22

Hi We are looking for two researchers (at post-doc or pre-doc level) to work with us in Edinburgh on two new Horizon Europe projects. Both projects start in Autumn 2022 and run for 3 years. The first project (High Performance Language Technologies -- HPLT) will create an open platform that trains reproducible high-quality machine translation systems and language models. The project is gathering over a million GPU hours and 7 petabytes of data. Research in HPLT focuses on efficiency and models that apply to a wide range of languages. The second project (UTTER -- Unified Transcription and Translation for Extended Reality) aims to use large language models to develop scalable, adaptable, contextualised, emotion-aware and explainable technologies for translation, summarisation and transcription. The project will develop prototypes for a multilingual meeting assistant and for dialogue translation in customer care. The new researchers will work on problems related to these goals. For more information, and how to apply, see https://neural.mt/jobs/ best Barry The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th’ ann an Oilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh SC005336.

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EACL 2023: Call for Papers
by Joel Tetreault 29 Sep '22

29 Sep '22

(apologies for cross-posting) *=== Important Information ===* Website: https://2023.eacl.org/ *Submission Deadline*: Thursday, 20 October 2022 *Conference Dates*: Tuesday, 2 May 2023 to 6 May 2023 *Location*: Dubrovnik, Croatia *Contact*: Alessandro Moschitti (General Chair): amoschitti(a)gmail.com // Isabelle Augenstein & Andreas Vlachos (Program Chairs): eacl2023pcs(a)googlegroups.com *=== Overview ===*The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023) invites the submission of long and short papers on substantial, original, and unpublished research on empirical methods for Natural Language Processing. As in recent years, some of the presentations at the conference will be for papers accepted by the Transactions of the ACL (TACL) and Computational Linguistics (CL) journals. EACL 2023 will follow EMNLP 2022 and go with a hybrid format with respect to ARR. This means that while EACL will accept ARR-reviewed papers, it will also accept submissions directly to EACL through the START system. However, in order to keep the review load on the community as a whole manageable, we ask authors to decide up-front if they want their papers to be reviewed through ARR or EACL. *Review Process:*Papers submitted directly to EACL will have the “regular” review process: paper reviewed by 3 reviewers, authors are invited to write an author response and revise their paper before the camera ready deadline, if accepted. ARR papers committed to EACL will be handled by the Senior Area Chairs. For these papers, the authors may provide an author response but not revise their paper (with the exception of adding the required “limitations” section, if it was missing from the ARR submission; see below). *Cross-Submission Policy with ARR:*Any ARR-reviewed paper that has received all of its reviews and meta-reviews available by the ARR-to-conference commitment deadline (January 8, 2023), can be committed to EACL 2023. Note: Submissions from ARR cannot be modified except that they can be associated with an author response. Note: While EACL will consider any ARR paper that has been fully reviewed by January 8, 2023, unlike for ACL and NAACL 2022, EACL does not guarantee a date such that all papers submitted to ARR before the date are guaranteed to receive necessary reviews in time for the EACL commitment deadline. Consequently, care must be taken in deciding whether a submission should be made to ARR or EACL directly if the work has not been submitted anywhere before the call. Plan accordingly. Note: The START system deadline for direct submission papers, namely non-ARR submission papers, is October 20, 2022. Papers submitted to ARR before October 13, 2022, can be withdrawn and submitted to EACL 2023. Note: In order for a paper to be submitted directly to EACL 2023, it must be inactive in the ARR system. This means that the submission must either be explicitly withdrawn by the authors, or the ARR reviews are finished and shared with the authors before October 13, 2022, and the paper was not re-submitted to ARR. Note: The authors can withdraw their paper from ARR by October 13, 2022, regardless of how many reviews it has received. Papers that are in the ARR system after October 13, 2022, either submitted after or submitted before and not withdrawn, cannot be directly submitted to EACL 2023. Papers submitted to EACL 2023 may not be submitted for review elsewhere (including ARR) while being under review at EACL 2023. *=== Important Dates ===*- Abstract registration deadline for START direct submissions: October 13, 2022 - Anonymity period begins: October 13, 2022 (same as the abstract registration date) - Direct paper submission deadline (long & short papers): October 20, 2022 - Author response period: December 6-12, 2022 - Commitment deadline for ARR papers: January 8, 2023 - Notification of acceptance (long & short papers): January 20, 2023 - Camera-ready papers due (long & short papers): February 10, 2023 - Workshops & Tutorials: May 2 and 6 2023 - Main Conference: May 3-5, 2023 All deadlines are 11.59 pm UTC -12h ("anywhere on Earth"). *=== Mandatory abstract submission ===*The paper title, author names, contact details, and a brief abstract must be submitted electronically through the EACL 2023 paper submission site by the abstract submission deadline (October 13, 2022). It will be possible to make minor edits to the title and abstract until the full paper submission deadline, but you cannot change authors and subject areas. Submissions with “placeholder” abstracts will be removed without consideration; Important: if you miss the abstract submission deadline, you cannot submit the full paper. *=== Submissions ===*EACL 2023 has the goal of a broad technical program. Relevant topics for the conference include, but are not limited to, the following areas (in alphabetical order): - Anaphora, Discourse and Pragmatics - Computational Social Science and Social Media - Dialogue and Interactive Systems - Document analysis, Text Categorization and Topic Models - Generation and Summarization - Green and Sustainable NLP - Information Retrieval and Search - Information Extraction - Interpretability and Model Analysis in NLP - Language Resources and Evaluation - Language Grounding and Multi-Modality - Linguistic Theories, Cognitive Modeling and Psycholinguistics - Machine Learning in NLP - Machine Translation - Multilinguality - Multidisciplinary and NLP Applications - Question Answering - Semantics: lexical - Semantics: sentence level and other areas - Sentiment Analysis and Argument Mining - Phonology, Morphology, and Word Segmentation - Tagging, Chunking, Syntax, and Parsing *=== Paper Submission Information ===* *Long Papers*Long paper submissions must describe substantial, original, completed and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included. Review forms will be made available prior to the deadlines. Long papers may consist of up to 8 pages of content, plus unlimited pages for references and appendix; final versions of long papers will be given one additional page of content (up to 9 pages) so that reviewers’ comments can be taken into account. *Short Papers*Short paper submissions must describe original and unpublished work. Please note that a short paper is not a shortened long paper. Instead short papers should have a point that can be made in a few pages. Short papers may consist of up to 4 pages of content, plus unlimited references and appendix. Upon acceptance, short papers will be given 5 content pages in the proceedings. Authors are encouraged to use this additional page to address reviewers’ comments in their final versions. *Presentation Mode*Long and short papers will be presented orally or as posters as determined by the program committee. The decisions as to which papers will be presented orally and which as poster presentations will be based on the nature rather than the quality of the work. While short papers will be distinguished from long papers in the proceedings, there will be no distinction in the proceedings between papers presented orally and as posters. *Authorship* The author list for submissions should include all (and only) individuals who made substantial contributions to the work presented. Each author listed on a submission to EACL 2023 will be notified of submissions, revisions and the final decision. No changes to the order or composition of authorship may be made to submissions to EACL 2023 after the abstract submission deadline. *Citation and Comparison*You are expected to cite all refereed publications relevant to your submission, but you may be excused for not knowing about all unpublished work (especially work that has been recently posted and/or is not widely cited). While not citing such unpublished works upon submission is not sufficient grounds for paper rejection, you are expected to cite such relevant work in camera ready, if notified about it by reviewers. In cases where a preprint has been superseded by a refereed publication, the refereed publication should be cited instead of the preprint version. Papers (whether refereed or not) appearing less than 3 months before the submission deadline are considered contemporaneous to your submission, and you are therefore not obliged to make detailed comparisons that require additional experimentation and/or in-depth analysis. However, you are expected to mention such works in your submission, and list their published results if they are directly relevant. For more information, see the ACL Policies for Submission, Review, and Citation: https://www.aclweb.org/adminwiki/index.php/ACL_Policies_for_Submission,_Rev… *Multiple Submission Policy* EACL 2023 will not consider any paper that is under review in a journal or another conference at the time of submission, and submitted papers must not be submitted elsewhere during the EACL 2023 review period. This policy covers all refereed and archival conferences and workshops (e.g., NeurIPS, ACL workshops), as well as ARR. In addition, we will not consider any paper that overlaps significantly in content or results with papers that will be (or have been) published elsewhere. Authors submitting more than one paper to EACL 2023 must ensure that their submissions do not overlap significantly (>25%) with each other in content or results. EACL 2023 will also accept submissions of ARR-reviewed papers, provided that the ARR reviews and meta-reviews are available by the ARR-to-conference submission deadline. However, EACL 2023 will not accept direct submissions that are actively under review in ARR, or that overlap significantly (>25%) with such submissions. *Mandatory Discussion of Limitations*We believe that it is also important to discuss the limitations of your work, in addition to its strengths. Following the EMNLP format, EACL 2023 requires all papers to have a clear discussion of limitations, in a dedicated section titled “Limitations”. This section will appear at the end of the paper, after the discussion/conclusions section and before the references, and will not count towards the page limit. Papers without a limitation section will be automatically rejected without review. ARR-reviewed papers that did not include “Limitations” section in their prior submission, should submit a PDF with such a section together when they commit their papers to EACL 2023 via Softconf. While we are open to different types of limitations, just mentioning that a set of results have been shown for English only probably does not reflect what we expect. Mentioning that the method works mostly for languages with limited morphology, like English, is a much better alternative. In addition, limitations such as low scalability to long text, the requirement of large GPU resources, or other things that inspire crucial further investigation are welcome. *Ethics Policy*Authors are required to honor the ethical code set out in the ACL Code of Ethics. The consideration of the ethical impact of our research, use of data, and potential applications of our work has always been an important consideration, and as artificial intelligence is becoming more mainstream, these issues are increasingly pertinent. We ask that all authors read the code, and ensure that their work is conformant to this code. Where a paper may raise ethical issues, we ask that you include in the paper an explicit discussion of these issues, which will be taken into account in the review process. We reserve the right to reject papers on ethical grounds, where the authors are judged to have operated counter to the code of ethics, or have inadequately addressed legitimate ethical concerns with their work. Authors will be allowed extra space after the 8th page (4th for short papers) for an optional broader impact statement or other discussion of ethics. The EACL review form will include a section addressing these issues and papers flagged for ethical concerns by reviewers or ACs will be further reviewed by an ethics committee. Note that an ethical considerations section is not required, but papers working with sensitive data or on sensitive tasks that do not discuss these issues will not be accepted. Conversely, the mere inclusion of an ethical considerations section does not guarantee acceptance. In addition to acceptance or rejection, papers may receive a conditional acceptance recommendation. Camera-ready versions of papers designated as conditional accept will be re-reviewed by the ethics committee to determine whether the concerns have been adequately addressed. Please read the ethics FAQ for more guidance on some problems to look out for and key concerns to consider relative to the code of ethics. *Paper Submission and Templates*Submission is electronic, using the Softconf START conference management system. Both long and short papers must follow the EACL 2023 two-column format, using the supplied official style files. Please do not modify these style files, nor should you use templates designed for other conferences. Submissions that do not conform to the required styles, including paper size, margin width, and font size restrictions, will be rejected without review. *Verification*To guarantee conformance to publication standards, we will be using the ACL Pubcheck tool (https://github.com/acl-org/aclpubcheck). The PDFs of camera-ready papers must be run through this tool prior to their final submission, and we recommend its use also at submission time. *Optional Supplementary Materials: Appendices, Software and Data*Each EACL 2023 submission can be accompanied by an appendix, which will appear in the main paper’s PDF, after the bibliography. A submission may also be accompanied by one .tgz or .zip archive containing software, and one .tgz or .zip archive containing data. EACL 2023 encourages the submission of these supplementary materials to improve the reproducibility of results, and to enable authors to provide additional information that does not fit in the paper. For example, anonymised related work (see above), preprocessing decisions, model parameters, feature templates, lengthy proofs or derivations, pseudocode, sample system inputs/outputs, and other details that are necessary for the exact replication of the work described in the paper can be put into the appendix. However, the paper submissions need to remain fully self-contained, as these supplementary materials are completely optional, and reviewers are not even asked to review or download them. If the pseudo-code or derivations or model specifications are an important part of the contribution, or if they are important for the reviewers to assess the technical correctness of the work, they should be a part of the main paper, and not appear in the appendix. Supplementary materials need to be fully anonymized to preserve the double-blind reviewing policy. *=== Anonymity Period ===*The following rules and guidelines are meant to protect the integrity of double-blind review and ensure that submissions are reviewed fairly. The rules make reference to the anonymity period, which runs from 1 week before the direct full paper submission deadline (starting October 13, 2022) up to the date when your paper is accepted or rejected (January 20, 2023). Papers that are withdrawn during this period will no longer be subject to these rules. - You may not make a non-anonymized version of your paper available online to the general community (for example, via a preprint server) during the anonymity period. Versions of the paper include papers having essentially the same scientific content but possibly differing in minor details (including title and structure) and/or in length. - If you have posted a non-anonymized version of your paper online before the start of the anonymity period, you may submit an anonymized version to the conference. The submitted version must not refer to the non-anonymized version, and you must inform the programme chairs that a non-anonymized version exists. - You may not update the non-anonymized version during the anonymity period, and we ask you not to advertise it on social media or take other actions that would further compromise double-blind reviewing during the anonymity period. - You may make an anonymized version of your paper available (for example, on OpenReview), even during the anonymity period. - For arXiv submissions, October 13, 2022 11:59pm UTC-12h (anywhere on earth) is the latest time the paper can be uploaded. *=== Instructions For Double-Blind Review ===*As reviewing will be double blind, papers must not include authors’ names and affiliations. Furthermore, self-references or links (such as github) that reveal the author’s identity, e.g., “We previously showed (Smith, 1991) …” must be avoided. Instead, use citations such as “Smith previously showed (Smith, 1991) …” Papers that do not conform to these requirements will be rejected without review. Papers should not refer, for further detail, to documents that are not available to the reviewers. For example, do not omit or redact important citation information to preserve anonymity. Instead, use third person or named reference to this work, as described above (“Smith showed” rather than “we showed”). If important citations are not available to reviewers (e.g., awaiting publication), these paper/s should be anonymised and included in the appendix. They can then be referenced from the submission without compromising anonymity. Papers may be accompanied by a resource (software and/or data) described in the paper, but these resources should also be anonymized. *=== Reproducibility Criteria ===*Reviewers will be asked to assess the reproducibility of the work as part of their reviews. The following are the criteria that reviews will take under consideration. For all reported experimental results: - A clear description of the mathematical setting, algorithm, and/or model. - Submission of a zip file containing source code, with specification of all dependencies, including external libraries, or a link to such resources (while still anonymized) - Description of computing infrastructure used - The average runtime for each model or algorithm (e.g., training, inference, etc.), or estimated energy cost - Number of parameters in each model - Corresponding validation performance for each reported test result - Explanation of evaluation metrics used, with links to code For all experiments with hyperparameter search: - The exact number of training and evaluation runs - Bounds for each hyperparameter - Hyperparameter configurations for best-performing models - Number of hyperparameter search trials - The method of choosing hyperparameter values (e.g., uniform sampling, manual tuning, etc.) and the criterion used to select among them (e.g., accuracy) - Summary statistics of the results (e.g., mean, variance, error bars, etc.) For all datasets used: - Relevant details such as languages, and number of examples and label distributions - Details of train/validation/test splits - Explanation of any data that were excluded, and all pre-processing steps - A zip file containing data or link to a downloadable version of the data - For new data collected, a complete description of the data collection process, such as instructions to annotators and methods for quality control. This list is based on Dodge et al, 2019 and Joelle Pineau's reproducibility checklist. *=== Presentation Requirement ===*All accepted papers must be presented at the conference—either on-line or in-person—in order to appear in the proceedings. Authors of papers accepted for presentation at EACL 2023 must notify the program chairs by the camera-ready deadline if they wish to withdraw the paper. At least one author of each accepted paper must register for EACL 2023 by the early registration deadline. More information can be found in the Committee blog. If you have questions that are not answered there, please email the program co-chairs at eacl2023pcs(a)gmail.com.

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Job: Research Assistant/ML Engineer
by Mihael Arcan 28 Sep '22

28 Sep '22

** *Applications are invited from suitably qualified candidates for a full-time, fixed term position as a Research Assistant with the Unit for Natural Language Processing (NLP) at the Data Science Institute, University of Galway. * * Project Background: **Candidates for this position should have an MSc or equivalent in a relevant field of study with an emphasis on areas such as machine learning and/or natural language processing. The candidate should have good programming skills in python (preferably experience with pytorch). The position is for a fixed period of 6 months with the possibility of extension, depending on the successful acquisition of project funding. **This positionis available in the context of the Insight SFI Research Centre for Data Analytics from November 1st2022 (or as soon as possible). The post is available in the context of a commercialisation project on language pattern detection for mental health issues. Essential Requirements: * MSc in Natural Language Processing or Computer Science * Relevant experience with natural language processing, machine and deep learning * Experience in classification task, including multiclass, multilabel, multiclass-multioutputclassification * Understanding of experimental design and scientific methodologies * Excellent programming skills in Python * Programming experience with deep learning (e.g. pytorch, transformers) Desirable Requirements: * Experience in data processing in health domain * Evidence of previously completed software projects, e.g. in github ** ** Employment permit restrictions apply for this category of the post. Salary: €27,380 – €36,786 per annum, (commensurate with qualifications and experience) To Apply: Applications, including a cover letter and CV in PDF and the contact details of three referees should be sent to Dr Mihael Arcan (mihael.arcan(a)insight-centre.org) *Closing date for receipt of applications is 5.00 pm 14th October 2022* *

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Where do you publish the datasets you create?
by Surangika Ranathunga 28 Sep '22

28 Sep '22

Dear Community NLP community usually quantifies the 'resourcefulness' of a language based on the datasets (annotated/unannotated) available in public repositories. However, our recent analysis on the LREC 2022 papers revealed that most of the datasets have not been published in these public repositories. In order to identify reasons for this, we created the below survey. Please spend 2mins responding to this survey. It is anonymous and raw data will NOT be published. The aggregated results will be published at an xCL venue. We hope our findings would be beneficial to the wider NLP community. Survey: https://forms.gle/nQbEBtUhEPxx2tux9 We will be collecting responses till Oct 8th. Regards Surangika Surangika Ranathunga, PhD Senior Lecturer, Department of Computer Science and Engineering, Faculty of Engineering, University of Moratuwa surangika(a)cse.mrt.ac.lk

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2 PhD Positions in Clinical NLP and Decision Support at DFKI, Berlin
by Roland Roller 28 Sep '22

28 Sep '22

The Speech and Language Technology group of the German Research Center for Artificial Intelligence (DFKI), offers two research/PhD positions in clinical text processing and clinical decision support. The position is located in Berlin and would be in close collaboration with colleagues at DFKI, but also partially with clinical partners. Position 1: Clinical text processing Your tasks: The candidate will work within our team on topics related to (neural) information extraction, concept normalization and medical guideline matching. A PhD could be developed within the scope of the given tasks, but could address problems such as cross-domain/cross-language learning, few shot learning, knowledge integration or generation of synthetic (patient) data. This research brings the opportunity to test, interdisciplinary, novel technologies for medical care. Your qualifications: - A completed Masters degree (or equivalent qualification) in Computer Science, Computational Linguistics, or a comparable field - Good knowledge of and preferably hands-on experience with natural language technologies (tools and libraries) - Experience with python - Experience in machine learning (e.g. Pytorch, Spacy, Transformers…) - Ability to efficiently familiarize yourself with new tools and topics - Team player, result-driven, highly self-motivated - Very good English language skills (written and spoken) - At least some Basic knowledge of German Your benefits : - A wide and interesting range of tasks and extensive development opportunities - Contribution to trend-setting, innovative projects in the field of Language Technology and AI - An innovative, agile and professional work environment - An attractive workplace in the heart of Berlin Position 2: Clinical decision support: Your tasks: The candidate will work within our team on the development of machine learning models integrating longitudinal, semi-structured data, to support physicians and clinical staff. The field would be in the intersection of machine learning, natural language processing and explainability and would include interdisciplinary work. A PhD could be defined/developed within the scope of the given tasks. Your qualifications: - A completed Masters degree (or equivalent qualification) in Computer Science, Computational Linguistics, or a comparable field - Experience with python - Experience in machine learning or neural networks (e.g. Pytorch, SPacy, Transformers,...) - Preferably hands-on experience with medical data - Ability to efficiently familiarize yourself with new tools and topics - Team player, result-driven, highly self-motivated - Very good English language skills (written and spoken) - At least some Basic knowledge of German Your benefits : - A wide and interesting range of tasks and extensive development opportunities - Contribution to trend-setting, innovative projects in the field of Language Technology and AI - An innovative, agile and professional work environment - An attractive workplace in the heart of Berlin Successful applicants will be employed according to their qualifications. We offer excellent working conditions with interesting research topics in an interdisciplinary team at an internationally renowned research centre. The position is initially limited to the duration of the underlying project (until mid/end 2025). Severely disabled applicants with essentially the same professional and personal suitability will be given priority. The DFKI intends to increase the proportion of women in the science sector and therefore explicitly invites women to apply. We look forward to receiving your application documents. Please send them in electronic form to Roland Roller (roland.roller(a)dfki.de) and Philippe Thomas (philippe.thomas(a)dfki.de). Deadline: October 14. Applicants who submit their documents after the deadline may also be considered - depending on whether the position has already been filled.

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FIRST CALL FOR TASK PARTICIPATION: NTCIR-17 FairWeb-1 Task
by Nicola Ferro 28 Sep '22

28 Sep '22

http://sakailab.com/fairweb1/ # Overview The FairWeb-1 task is a new English web search task that considers both relevance and group fairness. Each of our search topic seeks information about specific entity types: R (researher), M (movies), T (Twitter accounts), and Y (YouTube contents); accordingly, we have four topic types: R-topics (e.g., information retrieval researchers) M-topics (e.g., Daniel Craig 007 movies) T-topics (e.g., Twitter accounts that provide info on COVID) Y-topics (e.g., Coldplay covers on YouTube) For evaluating group fairness, we consider the following attribute sets containing either ordinal or nominal groups: R-topics: h-index (ordinal) AND gender (nominal) M-topics: #reviews on IMDb (ordinal) AND geographic region (nominal) T-topics: #followers (ordinal) Y-topics: #subscribers of the YouTube account (ordinal) For R- and M-topics, we will evaluate intersectional groupfairness. For example, for each R-topic, we want the search engine result page (SERP) to contain information about researchers with varying levels of h-index (not just high h-index people), AND with different genders (not just "men"). # Task input/ouput INPUT: - a search topic (R, M, T, or Y) - attribute set(s) and target distribution(s) OUTPUT: - a TREC-style run (a SERP for each topic) # Evaluation method We will use the Group Fairness and Relevance (GFR) framework: please visit our webpage for details. # Timeline October 7, 2022 Release of 1st CFP with sample topics and evaluation protocol December 16, 2022 Pilot relevance assessments for the sample topics and a few pilot runs released; topic set size determined Dec 19-Feb 28, 2023 Topic development March 1, 2023 Topics released; task registrations due May 12, 2023 Run submissions due May 15-July 31, 2023 Entity annotations; runs evaluated August 1, 2023 Evaluation results and draft overview released September 1, 2023 Draft participant papers due November 1, 2023 Camera ready papers due December 2023 NTCIR-17@NII, Tokyo, Japan # Inquiries: fairweb1org(a)list.waseda.jp # Organisers: Sijie Tao, Nuo Chen, Tetsuya Sakai (Waseda University, Japan) Zhumin Chu (Tsinghua University, P.R.C.) Nicola Ferro (University of Padua, Italy) Maria Maistro (University of Copenhagen, Denmark) Ian Soboroff (NIST, USA) Hiromi Arai (RIKEN AIP, Japan)

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EVALITA 2023: Call for tasks - NEW DEADLINES and TIMELINE
by Marco Polignano 27 Sep '22

27 Sep '22

* ***************************************************************************** EVALITA 2023: Call for tasks - NEW DEADLINES and TIMELINE ***************************************************************************** EVALITA 2023is an initiative of AILC(Associazione Italiana di Linguistica Computazionale, AILC https://www.ai-lc.it/ <https://www.ai-lc.it/>). The final workshop will be held on **September 7th-8th in Parma, Italy**. As in the previous editions (https://www.evalita.it/ <https://www.evalita.it/>), EVALITA 2023 will be organized along a few selected tasks, which provide participants with opportunities to discuss and explore both emerging and traditional areas of Natural Language Processing and Speech for Italian. The participation is encouraged for teams working both in academic institutions and industrial organizations. TASK PROPOSAL SUBMISSION Tasks proposals should be no longer than 4 pages and should include: - task title and acronym; - names and affiliation of the organizers (minimum 2 organizers); - brief task description, including motivations and state of the art; - explanation of the international relevance of the task; - description and examples of the data, including information about their availability, development stage, and issues concerning privacy and data sensitivity. The examples are mandatory because they are intended to give potential participants an idea of what the task data will look like, how it’ll be formatted, etc. - expected number of participants and attendees; - names and contact information of the organizers. In submitting your proposal, please bear in mind that we encourage: - challenging tasks involving linguistic analysis, e.g., beyond “simple” classification problems; - tasks focused on multimodality, e.g., considering both textual and visual information; - tasks characterized by different levels of complexity, e.g., with a straightforward main subtask and one or more sophisticated additional subtasks; - the re-annotation/expansion of datasets from previous years with new annotation levels, and texts from publicly available corpora; - both new tasks and re-runs: for new tasks, organizers will have to specify in the proposal why it would attract a reasonable number of participants, and why it is needed; - application-oriented tasks, that is tasks that have a clearly defined end-user application showcasing; - multilingual tasks, i.e. with data both in Italian and in other languages; - industrial tasks, i.e. tasks with real data provided by companies. The organizers of the accepted tasks should take care of planning, according to the scheduled deadlines (see below): - the development and distribution of datasets needed for the contest, i.e. data for training and development, and data for testing; the scorer to be used to evaluate the submitted systems should be included in the release of development data; - the development of task guidelines, where all the instructions for the participation are made clear together with a detailed description of data and evaluation metrics applied for the evaluation of the participant results; - the collection of participants results; - the evaluation of participants results according to standard metrics and baseline(s); - the solicitation of participation and of submissions; - the reviewing process of the papers describing the participants approach and results (according to the template to be made available by the EVALITA 2023 chairs); - the production of a paper describing the task (according to the template to be made available by the EVALITA 2023 chairs). *** Email your proposal in PDF format to evalita2023(a)gmail.com with "EVALITA 2023 TASK Proposal" as the subject line by the submission deadline: October 17th 2022. *** Please feel free to contact the EVALITA 2023 chairs at evalita2023(a)gmail.com in case of any questions or suggestions. NEW deadlines of the task proposal: - October 4th 2022 October 17th 2022: submission of task proposals - October 18th 2022 October 24th 2022: notification of task proposal acceptance NEW timeline of EVALITA 2023: - 7th February 2023: development data available to participants - 30th April 2023: registration closes - 2nd-19th May 2023: evaluation windows - 30th May 2023: assessment returned to participants - 14th June 2023: final reports (from participants) due to task organizers - 28th June 2023: final reports (from task organizers) due to EVALITA chairs - 10th July 2023: review deadline - 25th July 2023: camera ready version deadline - 7th-8th September 2023: final workshop in Parma EVALITA 2023 CHAIRS Mirko Lai (Università di Torino) Stefano Menini (Fondazione Bruno Kessler) Marco Polignano (Università di Bari Aldo Moro) Valentina Russo (Logogramma SRL) Rachele Sprugnoli (Università degli Studi di Parma) Giulia Venturi (Istituto di Linguistica Computazionale “A. Zampolli” - CNR) *

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PhD position on hate speech and misinformation on social media, at the University of Tartu, Estonia
by Rajesh Sharma 27 Sep '22

27 Sep '22

Hello Everyone, I hope this email finds you well and sorry for cross-posting. Computational Social Science group (in the University of Tartu, Estonia) has a PhD position related to hate speech and misinformation on online social media. Please feel free to spread among your contacts. Deadline: 30 September. Please contact me before 30 Sept, as I will assist you in the application process (we need CV, motivation letter). We expect the candidate to know one or more aspects of the following techniques and programming languages (if not all): (i) Preferred programming languages: Python or R. (ii) Exploratory data analysis: feature extraction, visualization, etc. (ii) Machine learning and deep learning with some hands-on experience. (iv) Social media analysis: This includes collecting data from Twitter/Reddit and analyzing it for insights. An ideal candidate should be mindful of what's going on social media as well. (v) Social network analysis and Natural Language Processing Program Benefits ================ The funding is for 4 years for PhD Health insurance is provided Academic and industrial professional development including travel support. Interaction with world-renowned external board members and speakers. Travel grant for attending conferences and workshops. Location: Institute of Computer Science, University of Tartu, Estonia. Institute of Computer Science is located in the University of Tartu Delta Centre (https://delta.ut.ee/en/) and it is a unique multidisciplinary centre for digital technology, analytics and economic thought, bringing together more than 2500 students, university teachers, scientists and R&D staff from companies. In short you will get an opportunity to work with diverse and collaborative colleagues. Delta Centre opened in January 2020 and is one of the most modern centres of digital technology, analytical and economic thought in the Nordic region. University of Tartu is the leading higher education and research center in Estonia, with more than 16000 students and 1800 academic staff. It is also the highest ranked university in the Baltic States according to both the Times Higher Education and the QS World University rankings. University of Tartu's Institute of Computer Science, ranks 176-200 (according to Times Higher Education), and hosts 750 Bachelors and Masters students and 60 doctoral students. The institute has a strong international orientation: over 40% of graduate students and a quarter of academic and research staff members are international. Graduate teaching in the institute is in English. Estonia is famous for its e-approach and home to many startups like Skype, Transferwise and Bolt to name a few. Tartu, university town, is the second largest city of Estonia and is relatively less expensive and is surrounded by nature within the walkable distance from the city. The successful candidate will work on an European research project within the "computational social science lab" (https://css.cs.ut.ee/) at the Institute of Computer Science. The group conducts leading-edge research in the fields of social media analytics and social network analysis. The applicant should have: - Should have a master's/PhD degree in computer science, IT, mathematics or other relevant discipline for PhD/Postdoc - Excellent programming skills. - A good command of spoken and written English, - Background in statistics/Data Mining/Machine Learning, social media analysis would be ideal. Knowledge of social network analysis would be an additional advantage. All applications should include a CV (PDF format, at the most 2 pages), research statement of suitability (PDF format, at the most 2 pages), Transcripts (master and bachelor), master thesis (or paper writing experience evidence). Applications can be sent to rajesh.sharma(a)ut.ee with the subject "(PhD application in hate speech/mental health". We will get back to you in case your application is shortlisted. Kind regards Rajesh Sharma, Associate Prof and Erasmus+ Coordinator, Head, Computational Social Science Group <https://css.cs.ut.ee/> Institute of Computer Science, University of Tartu, Estonia Google Scholar <https://scholar.google.com/citations?hl=en&user=GKegbo0AAAAJ&view_op=list_w…> LinkedIn <https://www.linkedin.com/in/rajesh-sharma-9a03408/>Twitter <https://twitter.com/RajeshS44973898>

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PhD position on mental health at the University of Tartu
by Rajesh Sharma 27 Sep '22

27 Sep '22

I hope this email finds you well and sorry for cross-posting. Computational Social Science has a PhD position on the topic related to mental health. Please feel free to spread among your contacts. We expect the candidate to know one or more aspects of the following techniques and programming languages (if not all): (i) Preferred programming languages: Python or R. (ii) Exploratory data analysis: feature extraction, visualization, etc. (ii) Machine learning and deep learning with some hands-on experience. (iv) Social media analysis: This includes collecting data from Twitter/Reddit and analyzing it for insights. An ideal candidate should be mindful of what's going on social media as well. (v) Social network analysis and Natural Language Processing Program Benefits ================ The funding is for 4 years for PhD Health insurance is provided Academic and industrial professional development including travel support. Interaction with world-renowned external board members and speakers. Travel grant for attending conferences and workshops. Location: Institute of Computer Science, University of Tartu, Estonia. Institute of Computer Science is located in the University of Tartu Delta Centre (https://delta.ut.ee/en/) and it is a unique multidisciplinary centre for digital technology, analytics and economic thought, bringing together more than 2500 students, university teachers, scientists and R&D staff from companies. In short you will get an opportunity to work with diverse and collaborative colleagues. Delta Centre opened in January 2020 and is one of the most modern centres of digital technology, analytical and economic thought in the Nordic region. University of Tartu is the leading higher education and research center in Estonia, with more than 16000 students and 1800 academic staff. It is also the highest ranked university in the Baltic States according to both the Times Higher Education and the QS World University rankings. University of Tartu's Institute of Computer Science, ranks 176-200 (according to Times Higher Education), and hosts 750 Bachelors and Masters students and 60 doctoral students. The institute has a strong international orientation: over 40% of graduate students and a quarter of academic and research staff members are international. Graduate teaching in the institute is in English. Estonia is famous for its e-approach and home to many startups like Skype, Transferwise and Bolt to name a few. Tartu, university town, is the second largest city of Estonia and is relatively less expensive and is surrounded by nature within the walkable distance from the city. The successful candidate will work on an European research project within the "computational social science lab" (https://css.cs.ut.ee/) at the Institute of Computer Science. The group conducts leading-edge research in the fields of social media analytics and social network analysis. The applicant should have: - Should have a master's/PhD degree in computer science, IT, mathematics or other relevant discipline for PhD/Postdoc - Excellent programming skills. - A good command of spoken and written English, - Background in statistics/Data Mining/Machine Learning, social media analysis would be ideal. Knowledge of social network analysis would be an additional advantage. All applications should include a CV (PDF format, at the most 2 pages), research statement of suitability (PDF format, at the most 2 pages), Transcripts (master and bachelor), master thesis (or paper writing experience evidence). Applications can be sent to rajesh.sharma(a)ut.ee with the subject "(PhD application in hate speech/mental health". We will get back to you in case your application is shortlisted. Kind regards Rajesh Sharma, Associate Prof and Erasmus+ Coordinator, Head, Computational Social Science Group <https://css.cs.ut.ee/> Institute of Computer Science, University of Tartu, Estonia Google Scholar <https://scholar.google.com/citations?hl=en&user=GKegbo0AAAAJ&view_op=list_w…> LinkedIn <https://www.linkedin.com/in/rajesh-sharma-9a03408/>Twitter <https://twitter.com/RajeshS44973898> ReplyForward <https://drive.google.com/u/0/settings/storage?hl=en&utm_medium=web&utm_sour…> <https://www.google.com/intl/en/policies/terms/> <https://www.google.com/intl/en/policies/privacy/> <https://www.google.com/gmail/about/policy/>

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