- Corpora - ELRA lists

PhD position (Orsay and Montréal) : Statistical analyses of lexical distributions with an application to anomaly detection in natural texts
by François Yvon 29 Jun '22

29 Jun '22

[apologies for cross-posting] Dear all, We are offering a fully funded PhD position at the crossroads between Natural Language Processing and Information Theory. The proposed title is "Statistical analyses of lexical distributions with an application to anomaly detection in natural texts", and the thesis will be jointly supervised by: - François Yvon (LISN, CNRS), - Pablo Piantanida (ILLS, CNRS - University of Paris-Saclay) Application deadline: July 14th, 2022 The thesis will be a collaboration between LISN (Laboratoire Interdisciplinaire des Sciences du Numérique) of Université Paris-Saclay and the ILLS (International Laboratory on Learning Systems) of McGill University jointly with ETS Montreal and MILA (Institut québécois d'intelligence artificielle) in Canada. Further information are available on the respective web sites: - LISN: https://www.lisn.upsaclay.fr/ - ILLS: https://www.mcgill.ca/channels/fr/channels/news/un-laboratoire-internationa… Applications should be submitted only via this link, where more information about the position is available: https://emploi.cnrs.fr/Gestion/Offre/Default.aspx?Ref=UMR9015-FRAYVO-009 If you are interested, please submit your application including the following elements: • Detailed CV, • Letter of motivation, • Details of transcripts (especially M1 and M2), • Elements of bibliography or personal achievements related to a research activity (e.g. master project, research internship subject, etc.), • 2 recommendation letters François Yvon and Pablo Piantanida --- F. Yvon LISN/CNRS 01 69 15 82 42 rue John Von Neumann Campus Universitaire d'Orsay - Bâtiment 508 91 405 Orsay Cédex http://perso.limsi.fr/yvon

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Two Open PhD Positions in Machine Learning at the Chair for Data Science in Würzburg
by Albin Zehe 29 Jun '22

29 Jun '22

The Data Science Chair at JMU Würzburg [1] as a member of the Center for AI and Data Science (CAIDAS) offers two positions for doctoral researchers (m/w/d) in the area of machine learning. Both positions are bound to a project, with an initial duration of two years with the possibility of further extension. Payment is at the level of E13 according to the German federal wage agreement scheme (TV-L). Candidates are expected to have a strong background in computer science and mathematics, with a specialisation in machine learning and interest in the topic of one of the projects. The first project is focused on the development and application of methods to enrich live chats of typical stream platforms like Twitch.tv with links to relevant information: you will work with industry partners to analyse the current topics of discussions in live chats and provide links to the partners' websites with information about these topics. This will be done, for example, by developing metric learning methods to find accurate representations of the available content and matching them with the current topics as well as the users' interests. The second project, HydrAS [2] has a stronger focus on theoretical research. Here, you have the opportunity to work on our HypTrails method, which can be used to compare different hypotheses about user behaviour by means of bayesian statistics. HydrAS aims to extend this method with (semi-)automatic generation and testing of hypotheses as well as include more powerful statistical models like continuous time Markov chain models. Please send your application (letter of motivation, curriculum vitae, academic records) at your earliest convenience, but no later than July 15th, 2022, to Prof. Dr. Andreas Hotho (dmir-jobs(a)uni-wuerzburg.de). You are welcome to contact us on the same address for additional details. [1] https://www.informatik.uni-wuerzburg.de/datascience/home/ [2] https://gepris.dfg.de/gepris/projekt/438232455?context=projekt&task=showDet… — Albin Zehe Chair for Computer Science X — Data Science University of Würzburg Am Hubland 97074 Würzburg phone.: +49-(0)931-31-83217 https://www.informatik.uni-wuerzburg.de/datascience/staff/zehe/

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Call for Papers: The 20th Annual Workshop of the Australasian Language Technology Association (ALTA 2022)
by pradeesh＠cs.otago.ac.nz 29 Jun '22

29 Jun '22

******************************************************************************************* 20th Annual Workshop of the Australasian Language Technology Association (ALTA 2022) ** Flinders University, Adelaide (Hybrid) ** 14th - 16th December 2022 http://alta2022.alta.asn.au/ ******************************************************************************************* Important Dates Submission Deadline (short and long papers): 30 September, 2022 Submission Deadline (presentation abstracts) 7 October, 2022 Author Notification: 7 November, 2022 Camera-Ready Deadline: 15 November, 2022 Tutorials: 14 December, 2022 Main Conference: 15-16 December, 2022 Submission deadlines are UTC-11 Overview The 20th Annual Workshop of the Australasian Language Technology Association will be held in a hybrid format at Flinders University, Adelaide, from the 14th to the 16th of December 2022. The hybrid format gives participants a valuable opportunity to socialise either in-person or via online platform. The ALTA 2022 workshop is the key local forum for socialising research results in natural language processing and computational linguistics, with presentations and posters from students, industry, and academic researchers. Like previous years, we would also like to encourage submissions and participation from industry and government researchers and developers. Note that ALTA is listed in recently updated CORE 2021 Conference Rankings as Australasian B. Topics ALTA invites the submission of papers and presentations on all aspects of natural language processing, including, but not limited to: -phonology, morphology, syntax, semantics, pragmatics, and discourse -speech recognition, understanding and generation -interpreting spoken and written language -natural language generation -linguistic, mathematical, and psychological models of language -NLP-based information extraction and retrieval -corpus-based and statistical language modelling -machine translation and translation aids -question answering and information extraction -natural language interfaces and dialogue systems -natural language and multimodal systems -message and narrative understanding systems -evaluations of language systems -embodied conversational agents -computational lexicography -summarisation -language resources -topic modelling, semantics and ontology -unsupervised language learning and analysis -social media analysis and processing -search and information retrieval -domain-specific adaptation of natural language processing algorithms -applied natural language processing and/or applications in industry We particularly encourage submissions that broaden the scope of our community through the consideration of practical applications of language technology and through multi-disciplinary research. We also specifically encourage submissions from industry. Format We invite submissions of two different formats: (1) Original Research Papers and (2) Abstract-based Presentations. (1) Original Research Papers We invite the submission of papers on original and unpublished research on all aspects of natural language processing. Long papers should be 6-8 pages and short papers should be 3-4 pages. Accepted papers will either be delivered as an oral presentation or as a poster presentation. Both short and long papers may include unlimited pages of references in addition to the page count requirements. Note that the review process is double-blind, and accordingly submitted papers should not include the identity of author(s) and the text should be suitably anonymised, e.g. using third person wording for self-citations, not providing URLs to your person website, etc. Original research papers will be included in the workshop proceedings, which will be published online in the ACL anthology and the ALTA website. Long papers will be distinguished from short papers in the proceedings. (2) Abstract-based Presentations To encourage broader participation and facilitate local socialisation of international results, we invite 1-2 page presentation abstracts. The organisers may offer the opportunity to give an oral presentation or a poster presentation. Submissions should include presentation title and abstract, name of the presenter, any publications relating to the work, and any information on collaboration with the local ALTA community. Abstracts will not be published in the proceedings, but simply reviewed by the ALTA executive committee to ensure that they are on topic, coherent and likely to be of interest to the ALTA community. Abstracts on work in progress and work published or submitted elsewhere are encouraged. ALTA invites submissions of all manner interesting research, not limited to, but including: established academics giving an overview of an exciting paper or paper/s published in international venues; completing research students giving an overview of their thesis work; early candidature research students presenting their work-in-progress and ideas, which may not have been published; and industry presenting research and development over linguistic data in the context of their business. Presentation abstracts should not be anonymised, any publications relating to the work should be cited in the submission, and the person who will give the presentation should be clearly stated. Multiple Submission Policy Original research papers that are under review for other publication venues or that you intend to submit elsewhere may be submitted in parallel to ALTA. We require that you declare at submission that your paper is submitted to another venue, and identify the venue. Should your paper be accepted to both ALTA and another venue, we allow you to decide whether the paper should be published in the ALTA proceedings, or if it should be treated as a Presentation (without archival publication). In this case you would still be able to present a research talk at the ALTA workshop. This is to encourage more internationally leading research to be presented at the workshop. Instructions for Authors Authors should submit their papers via Easychair (https://easychair.org/conferences/?conf=alta2022) There are 3 tracks in EasyChair this year: ALTA 2022 (Long) – use this for long papers ALTA 2022 (Short) – use this for short papers ALTA 2022 (Abstracts) – use this for abstracts Formatting Guidelines Submissions must follow the two-column ACL format Paper Length Long papers should be 6-8 pages Short papers should be 3-4 pages Abstracts ideally should be a few paragraphs and no more than 2 pages Anonymisation Short and long papers must be anonymised. Abstracts are NOT to be anonymised and must include the author's/authors' affiliation

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[Corpora-List]First Call for Papers: EvoNLP (The First Workshop on Ever Evolving NLP) + Shared task
by Jose Camacho Collados 28 Jun '22

28 Jun '22

************************************ Call for Papers: EvoNLP - The First Workshop on Ever Evolving NLP + Shared task Workshop: https://sites.google.com/view/evonlp/ Shared Task: https://sites.google.com/view/evonlp/shared-task Submission deadline (for papers requiring review / non-archival): 10 October, 2022 Submission deadline (with ARR reviews): 25 October, 2022 Notification of acceptance: 31 October, 2022 Camera-ready paper deadline: 11 November, 2022 Workshop date: 7 December, 2022 ************************************ Advances in language modeling have led to remarkable accuracy on several NLP tasks, but most benchmarks used for evaluation are static, ignoring the practical setting under which training data from the past and present must be used for generalizing to future data. Consequently, training paradigms also ignore the time sensitivity of language and essentially treat all text as if it was written at a single point in time. Recent studies have shown that in a dynamic setting, where the test data is drawn from a different time period than the training data, the accuracy of such static models degrades as the gap between the two periods increases. -------------------------------------------------------------- This workshop focuses on these time-related issues in NLP models and benchmarks. We invite researchers from both academia and industry to redesign experimental settings, benchmark datasets, and modeling by especially focusing on the “time” variable. We will welcome papers / work-in-progress on several topics including (but not limited to): - Dynamic Benchmarks: Evaluation of Model Degradation in Time Measuring how NLP models age Random splits vs time-based splits (past/future) Latency (days vs years) at which models need to be updated for maintaining task accuracy Time-sensitivity of different tasks and the type of knowledge which gets stale Time-sensitivity of different domains (e.g., news vs scientific papers) and how domain shifts interact with time shifts Sensitivity of different models and architectures to time shifts - Time-Aware Models Incorporating time information into NLP models Techniques for updating / replacing models which degrade with time Learning strategies for improving temporal degradation Trade-offs between updating a degraded model vs replacing it altogether Mitigating catastrophic forgetting of old knowledge as we update models with new knowledge Improving plasticity of models so that they can be easily updated Retrieval based models for improving temporal generalization - Analysis of existing models / datasets Characterizing whether degradation on a task is due to outdated facts or changes in language use Effect of model scale on temporal degradation – do large models exhibit less degradation? Efficiency / accuracy trade-offs when updating models -------------------------------------------------------------- All accepted papers will be published in the workshop proceedings unless requested otherwise by the authors. Submissions can be made either via OpenReview where they will go through the standard double-blind process, or through ACL Rolling Review with existing reviews. See details below. ---- Submission guidelines ---- We seek submissions of original work or work-in-progress. Submissions can be in the form of long/short papers and should follow the ACL main conference template. Authors can choose to make their paper archival/non-archival. All accepted papers will be presented at the workshop. Archival track We will follow double-blind review process and use OpenReview for the submissions. We also will accept ACL rolling review (ARR) submissions with reviews. Since these submissions already come with reviews, the submission deadline is much later than the initial deadline. We will use Open Review for the submissions. Submission link: https://openreview.net/group?id=EMNLP/2022/Workshop/EvoNLP For papers needing review click “EMNLP 2022 Workshop EvoNLP submission” For papers from ARR click “EMNLP 2022 Workshop EvoNLP commitment Submission” ---- Non-archival track ---- Non-archival track seeks recently accepted / published work as well as work-in-progress. It does not need to be anonymized and will not go through the review process. The submission should clearly indicate the original venue and will be accepted if the organizers think the work will benefit from exposure to the audience of this workshop. Submission: Please email your submission as a single PDF file to evonlp(a)googlegroups.com. Include “EvoNLP Non-Archival Submission” in the title and the author names and affiliation within the body of your email. ---- Shared task ---- The workshop will feature a shared task on meaning shift detection in social media. Initial data already available! Winners of the shared task will also receive a cash prize. More details at the workshop website :https://sites.google.com/view/evonlp/shared-task. Best paper award Thanks to generous support from our sponsors Snap Inc, we will award the best paper award (with cash prize) to one of the submissions selected by our program committee and organizing committee. The best paper will be given the opportunity for a lightning talk to introduce their work. -- Jose Camacho Collados http://www.josecamachocollados.com<http://www.josecamachocollados.com/>

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[Corpora-List]NLP Special Issue of "Mathematics" is out !
by Florentina Hristea 28 Jun '22

28 Jun '22

Dear all, On behalf of "Mathematics", Cornelia Caragea and I are happy to let you know that the NLP Special Issue has been closed. You can check it out here: https://www.mdpi.com/journal/mathematics/special_issues/Natural_Language_Pr… We thank the contributors and hope to meet you all on the occasion of the new Special Issue that will be launched soon. "Mathematics" has increased its Impact Factor as of today (new IF 2.592) and ranks 21/332 (Q1) in the category 'Mathematics'. Florentina Hristea

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[Corpora-List]Call for Paper: TextGraphs 2022 - 16th Workshop on Graph-based Natural Language Processing
by Yanjun Gao 28 Jun '22

28 Jun '22

(Apologize for cross-posting) Call for Paper: 16th Workshop on Graph-based Natural Language Processing (TextGraphs) Venue: COLING 2022 Location: Gyeongju, Republic of Korea Date: October 16, 2022 Papers Due: July 11, 2022 (Monday) Submission Site: https://www.softconf.com/coling2022/TextGraphs-16/ Workshop Website: https://sites.google.com/view/textgraphs2022 Workshop Description For the past sixteen years, the workshops in the TextGraphs series have published and promoted the synergy between the field of Graph Theory (GT) and Natural Language Processing (NLP). The mix between the two started small, with graph-theoretical frameworks providing efficient and elegant solutions for NLP applications. Graph-based solutions initially focused on single-document part-of-speech tagging, word sense disambiguation, and semantic role labeling. They became progressively larger to include ontology learning and information extraction from large text collections. Nowadays, graph-based solutions also target Web-scale applications such as information propagation in social networks, rumor proliferation, e-reputation, multiple entity detection, language dynamics learning, and future events prediction, to name a few. We plan to encourage the description of novel NLP problems or applications that have emerged in recent years, which can be enhanced with existing and new graph-based methods. The sixteenth edition of the TextGraphs workshop aims to extend the focus on graph-based representations for (1) integration and joint training and use of transformer-based models for graphs and text (such as Graph-BERT and BERT), and (2) domain-specific natural language inference. Related to the former point, we would like to advance the state-of-the-art natural language understanding facilitated with large-scale language models like GPT-3 and linguistic relationships represented by graph neural networks. Related to the latter point, we are interested in addressing a challenging task contributing to mathematical proof discovery. Furthermore, we also encourage research on applications of graph-based methods in knowledge graphs to link them to related NLP problems and applications. TextGraphs-16 invites submissions on (but not limited to) the following topics * Graph-based and graph-supported machine learning methods: Graph embeddings and their combinations with text embeddings; Graph-based and graph-supported deep learning (e.g., graph-based recurrent and recursive networks); Probabilistic graphical models and structure learning methods * Graph-based methods for Information Retrieval and Extraction: Graph-based methods for word sense disambiguation; Graph-based strategies for semantic relation identification; Encoding semantic distances in graphs; Graph-based techniques for text summarization, simplification, and paraphrasing; Graph-based techniques for document navigation and visualization * New graph-based methods for NLP applications: Random walk methods in graphs; Semi-supervised graph-based methods * Graph-based methods for applications on social networks * Graph-based methods for NLP and Semantic Web: Representation learning methods for knowledge graphs; Using graphs-based methods to populate ontologies using textual data Important dates * Papers Due: July 11, 2022 (Monday) * Notification of Acceptance: August 22, 2022 (Monday) * Camera-ready papers due: September 5, 2022 (Monday) * Conference date: October 12-17, 2022 * Shared task: TBD Submission * We invite submissions of up to eight (8) pages maximum, plus bibliography for long papers and four (4) pages, plus bibliography, for short papers. * The COLING 2022 templates must be used; these are provided in LaTeX and also Microsoft Word format. Submissions will only be accepted in PDF format. Download the Word and LaTeX templates here: https://coling2022.org/Cpapers<https://www.google.com/url?q=https%3A%2F%2Fcoling2022.org%2FCpapers&sa=D&sn…>. * Submit papers by the end of the deadline day (timezone is UTC-12) via our Softconf Submission Site. Contact Please direct all questions and inquiries to our official e-mail address (textgraphsOC(a)gmail.com<mailto:textgraphsOC@gmail.com>) or contact any of the organizers via their individual emails. Also you can join us on Facebook: https://www.facebook.com/groups/900711756665369<https://www.google.com/url?q=https%3A%2F%2Fwww.facebook.com%2Fgroups%2F9007…>. Organizers * Dmitry Ustalov, Yandex * Yanjun Gao, University of Wisconsin-Madison * Abhik Jana, University of Hamburg * Thien Huu Nguyen, University of Oregon * Gerald Penn, University of Toronto * Arti Ramesh, Binghamton University * Alexander Panchenko, Skolkovo Institute of Science and Technology (Skoltech) * Mokanarangan Thayaparan, University of Manchester & Idiap Research Institute * Marco Valentino, University of Manchester & Idiap Research Institute -- Yanjun Gao, Ph.D. Computer Science and Engineering Postdoctoral Research Associate, ICU Data Science Lab Department of Medicine School of Medicine and Public Health University of Wisconsin-Madison https://serenayj.github.io/

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[Corpora-List]Final Call for Papers: The 2022 SIGNLL Conference on Computational Natural Language Learning (CoNLL 2022)
by jackh＠allenai.org 28 Jun '22

28 Jun '22

The 2022 SIGNLL Conference on Computational Natural Language Learning (CoNLL 2022, Co-located with EMNLP 2022) Website: https://conll.org/ SIGNLL invites submissions to the 26th Conference on Computational Natural Language Learning (CoNLL 2022). The focus of CoNLL is on theoretically, cognitively and scientifically motivated approaches to computational linguistics, rather than on work driven by particular engineering applications. Such approaches include: - Computational learning theory and other techniques for theoretical analysis of machine learning models for NLP - Models of first, second and bilingual language acquisition by humans - Models of language evolution and change - Computational simulation and analysis of findings from psycholinguistic and neurolinguistic experiments - Analysis and interpretation of NLP models, using methods inspired by cognitive science or linguistics or other methods - Data resources, techniques and tools for scientifically-oriented research in computational linguistics - Connections between computational models and formal languages or linguistic theories - Linguistic typology, translation, and other multilingual work - Theoretically, cognitively and scientifically motivated approaches to text generation We welcome work targeting any aspect of language, including: - Speech and phonology - Syntax and morphology - Lexical, compositional and discourse semantics - Dialogue and interactive language use - Sociolinguistics - Multimodal and grounded language learning We do not restrict the topic of submissions to fall into this list. However, the submissions’ relevance to the conference’s focus on theoretically, cognitively and scientifically motivated approaches will play an important role in the review process. Submitted papers must be anonymous and use the EMNLP 2022 template. Submitted papers may consist of up to 8 pages of content plus unlimited space for references. Authors of accepted papers will have an additional page to address reviewers’ comments in the camera-ready version (9 pages of content in total, excluding references). Optional anonymized supplementary materials and a PDF appendix are allowed, according to the EMNLP 2022 guidelines. Please refer to the EMNLP 2022 Call for Papers for more details on the submission format. Submission is electronic, using the Softconf START conference management system. Note that, unlike EMNLP, we do not mandate that papers have a section discussion limitations of the work. However, we strongly encourage authors have such a section in the appendix. CoNLL adheres to the ACL anonymity policy, as described in the EMNLP 2022 Call for Papers. Briefly, non-anonymized manuscripts submitted to CoNLL cannot be posted to preprint websites such as arXiv or advertised on social media after May 30th, 2022. Multiple submission policy CoNLL 2022 will not accept papers that are currently under submission, or that will be submitted to other meetings or publications, including EMNLP. Papers submitted elsewhere as well as papers that overlap significantly in content or results with papers that will be (or have been) published elsewhere will be rejected. Authors submitting more than one paper to CoNLL 2022 must ensure that the submissions do not overlap significantly (>25%) with each other in content or results. CoNLL 2022 has the same policy as EMNLP 2022 regarding ARR submissions. This means that CoNLL 2022 will also accept submissions of ARR-reviewed papers, provided that the ARR reviews and meta-reviews are available by the ARR commitment deadline. We follow the EMNLP policy for papers that were previously submitted to ARR, or significantly overlap (>25%) with such submissions. Important Dates Anonymity period begins: May 30th, 2022 Submission deadline for START direct submissions: Thursday June 30th, 2022 Commitment deadline for ARR papers: August 1st, 2022 Notification of acceptance: Mid-September, 2022 Camera ready papers due: October 15th, 2022 Conference: December 7th, 8th, 2022 All deadlines are at 11:59pm UTC-12h ("anywhere on earth").

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WMT 2022 Quality Estimation Shared Tasks, Call for Participation
by Chrysoula Zerva 28 Jun '22

28 Jun '22

Dear all, we invite you to participate in this year's WMT shared tasks on Quality Estimation, where the goal is to predict the translation quality based on just the source and translation text. This year we introduce the following new elements: - Updated quality annotation scheme: the majority of the tasks uses Multidimensional Quality Metrics (MQM) instead of direct assessments (DA); - QE as a Metric: we share part of the data used in this year's Metrics task, to promote research that bridges the two domains; - New language pairs: English-Marathi, with sentence level and word level annotations (direct assessments) and a _surprise_ language pair in the testing phase; - An explainability subtask, following up on the 1st edition of Eval4NLP shared task; - Updated data and task definition for the critical error detection task. ## Tasks description Task 1 -- Quality prediction - Word-level: predict the translation errors, assigning OK/BAD tags to each word of the target. - Sentence-level: predict the quality score for each source-target sentence pair. Task 2 -- Explainable QE Infer translation errors as an explanation for sentence-level quality scores. Task 3 -- Critical Error Detection Predict sentence-level binary scores indicating whether or not a translation contains a critical error. Links to the data on the QE shared task website: https://wmt-qe-task.github.io/ ## Important dates: - Release of training data: 30 May - Release of dev data: TBA - Release of test data: 21 July - Test predictions deadline: 16 August - System description paper: 18 August - Conference: 7-8 December To ask questions and receive the latest announcements, join our Google Group: https://groups.google.com/g/wmt-qe-shared-task/ Best, The organisers.

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[Corpora-List]Call for Paper: 16th Workshop on Graph-based Natural Language Processing (TextGraphs 2022)
by Yanjun Gao 28 Jun '22

28 Jun '22

Call for Paper: 16th Workshop on Graph-based Natural Language Processing (TextGraphs) Venue: COLING 2022 Location: Gyeongju, Republic of Korea Date: October 16, 2022 Papers Due: July 11, 2022 (Monday) Workshop Description For the past sixteen years, the workshops in the TextGraphs series have published and promoted the synergy between the field of Graph Theory (GT) and Natural Language Processing (NLP). The mix between the two started small, with graph-theoretical frameworks providing efficient and elegant solutions for NLP applications. Graph-based solutions initially focused on single-document part-of-speech tagging, word sense disambiguation, and semantic role labeling. They became progressively larger to include ontology learning and information extraction from large text collections. Nowadays, graph-based solutions also target Web-scale applications such as information propagation in social networks, rumor proliferation, e-reputation, multiple entity detection, language dynamics learning, and future events prediction, to name a few. We plan to encourage the description of novel NLP problems or applications that have emerged in recent years, which can be enhanced with existing and new graph-based methods. The sixteenth edition of the TextGraphs workshop aims to extend the focus on graph-based representations for (1) integration and joint training and use of transformer-based models for graphs and text (such as Graph-BERT and BERT), and (2) domain-specific natural language inference. Related to the former point, we would like to advance the state-of-the-art natural language understanding facilitated with large-scale language models like GPT-3 and linguistic relationships represented by graph neural networks. Related to the latter point, we are interested in addressing a challenging task contributing to mathematical proof discovery. Furthermore, we also encourage research on applications of graph-based methods in knowledge graphs to link them to related NLP problems and applications. TextGraphs-16 invites submissions on (but not limited to) the following topics * Graph-based and graph-supported machine learning methods: Graph embeddings and their combinations with text embeddings; Graph-based and graph-supported deep learning (e.g., graph-based recurrent and recursive networks); Probabilistic graphical models and structure learning methods * Graph-based methods for Information Retrieval and Extraction: Graph-based methods for word sense disambiguation; Graph-based strategies for semantic relation identification; Encoding semantic distances in graphs; Graph-based techniques for text summarization, simplification, and paraphrasing; Graph-based techniques for document navigation and visualization * New graph-based methods for NLP applications: Random walk methods in graphs; Semi-supervised graph-based methods * Graph-based methods for applications on social networks * Graph-based methods for NLP and Semantic Web: Representation learning methods for knowledge graphs; Using graphs-based methods to populate ontologies using textual data Important dates * Papers Due: July 11, 2022 (Monday) * Notification of Acceptance: August 22, 2022 (Monday) * Camera-ready papers due: September 5, 2022 (Monday) * Conference date: October 12-17, 2022 * Shared task: TBD Submission * We invite submissions of up to eight (8) pages maximum, plus bibliography for long papers and four (4) pages, plus bibliography, for short papers. * The COLING 2022 templates must be used; these are provided in LaTeX and also Microsoft Word format. Submissions will only be accepted in PDF format. Download the Word and LaTeX templates here: https://coling2022.org/Cpapers<https://www.google.com/url?q=https%3A%2F%2Fcoling2022.org%2FCpapers&sa=D&sn…>. * Submit papers by the end of the deadline day (timezone is UTC-12) via our Softconf Submission Site. Contact Please direct all questions and inquiries to our official e-mail address (textgraphsOC(a)gmail.com<mailto:textgraphsOC@gmail.com>) or contact any of the organizers via their individual emails. Also you can join us on Facebook: https://www.facebook.com/groups/900711756665369<https://www.google.com/url?q=https%3A%2F%2Fwww.facebook.com%2Fgroups%2F9007…>. Organizers * Dmitry Ustalov, Yandex * Yanjun Gao, University of Wisconsin-Madison * Abhik Jana, University of Hamburg * Thien Huu Nguyen, University of Oregon * Gerald Penn, University of Toronto * Arti Ramesh, Binghamton University * Alexander Panchenko, Skolkovo Institute of Science and Technology (Skoltech) * Mokanarangan Thayaparan, University of Manchester & Idiap Research Institute * Marco Valentino, University of Manchester & Idiap Research Institute -- Yanjun Gao, Ph.D. Computer Science and Engineering Postdoctoral Research Associate, ICU Data Science Lab Department of Medicine School of Medicine and Public Health University of Wisconsin-Madison https://serenayj.github.io/

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[Corpora-List]3rd CFP and deadline extension: CL for Political Text Analysis (CPSS)
by Ines Rehbein 28 Jun '22

28 Jun '22

Call for Papers: 3rd Workshop on Computational Linguistics for Political and Social Sciences (CPSS 2022) https://gscl.org/en/arbeitskreise/cpss/cpss-2022/cfp-2022 * Workshop description * Recent years have seen more and more applications of computational methods to the analysis of political texts. This has led to the emergence of different communities (one with a background in political / social science and the other in the areas of NLP/computer science) which struggle to get awareness of the relevant work taking place in the respective other community. The main goal of this workshop is to bridge this gap and bring together researchers and ideas from the different communities, to foster collaboration and catalyze further interdisciplinary research efforts. *Keynote* by David Jurgens https://jurgens.people.si.umich.edu/ * Important Dates * Workshop papers due: **10.07.2022** (extended) Notification of acceptance: 10.08.2022 Camera-ready papers due: 01.09.2022 Workshop date: 12.09.2022 * Submissions * We welcome submissions of long and short papers, posters, and demonstrations relating to any aspect of Political Text Analysis using computational methods. Our workshop will accept two types of submissions: * archival papers describing original and unpublished work * non-archival papers (abstracts) that present already published research or ongoing work. The availability of both submission formats will meet the different needs of researchers from different communities, allowing them to come together and exchange ideas in an "get to know each other" environment which is likely to foster future collaborations. * Special Theme and Panel * The workshop will host a panel with invited speakers from the different communities, with a focus on theory-driven modelling of complex political or socio-psychological constructs in text, such as populism, polarisation or political cynicism. The panel will discuss challenges for modelling such multifaceted concepts from a theoretical as well as from a machine learning point of view, and how such models can be evaluated in a meaningful way. For more information, please refer to the workshop website: gscl.org/en/arbeitskreise/cpss/cpss-2022 If you have any questions, please feel free to contact the program co-chairs: ines(a)informatik.uni-mannheim.de * Organisers * * Ines Rehbein (U-Mannheim) * Christopher Klamm (U-Mannheim) * Gabriella Lapesa (U-Stuttgart) * Simone Ponzetto (U-Mannheim) -- Ines Rehbein Data and Web Science Group University of Mannheim, Germany

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