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3-year PhD position at UNED (Spain)
by JORGE AMANDO CARRILLO DE ALBORNOZ CUADRADO 11 Jul '22

11 Jul '22

Madrid – 3-year PhD position The UNED IR & NLP group has an open 3-year PhD position. The successful candidate is expected to work on the CLARA: artifiCial inteLligence observAtory foR spAnish, that has the aim of measuring the gap in Artificial Intelligence between English and Spanish. The project focuses on monitoring the comparative state of the art of Natural Language Processing in English and Spanish, as well as quantifying the comparative adoption and use of Artificial Intelligence solutions in English and Spanish by citizens and organizations. As part of this team, the candidate will research in evaluation metrics and frameworks. Also, the candidate will collaborate in the design and development of the evaluation framework EvALL 2.0 (see EvALL 1.0 at www.evall.uned.es<http://www.evall.uned.es>), an online evaluation service for Artificial Intelligence systems. * Candidate profiles * * Academic background (university degree, preferably master) in computer science or related discipline. * Experience developing Python applications. * Excellent programming skills. * Collaborative work skills. * Fluent in English (knowledge of Spanish is a plus). * Terms and conditions * Location: NLP&IR UNED, Madrid, Spain Duration: 3 years (1+1+1) Salary: 30.000 € Context: CLARA: artifiCial inteLligence observAtory foR spAnish * Application * Please send an email to julio(a)lsi.uned.es and jcalbornoz(a)lsi.uned.es<mailto:jcalbornoz@lsi.uned.es> titled “Programador de Django y Python” and include CV, names of two references and a brief motivation letter stating your interests and past experience The position is open until filled. More details in the official call: https://www2.uned.es/bici/Curso2021-2022/220404/24-1.htm#9.-_____ * More about us * The UNED NLP & IR group is a leading research group (of around 30 members) in the areas of Natural Language Processing and Information Retrieval. See nlp.uned.es for details. AVISO LEGAL. Este mensaje puede contener información reservada y confidencial. Si usted no es el destinatario no está autorizado a copiar, reproducir o distribuir este mensaje ni su contenido. Si ha recibido este mensaje por error, le rogamos que lo notifique al remitente. Le informamos de que sus datos personales, que puedan constar en este mensaje, serán tratados en calidad de responsable de tratamiento por la UNIVERSIDAD NACIONAL DE EDUCACIÓN A DISTANCIA (UNED) c/ Bravo Murillo, 38, 28015-MADRID-, con la finalidad de mantener el contacto con usted. La base jurídica que legitima este tratamiento, será su consentimiento, el interés legítimo o la necesidad para gestionar una relación contractual o similar. En cualquier momento podrá ejercer sus derechos de acceso, rectificación, supresión, oposición, limitación al tratamiento o portabilidad de los datos, ante la UNED, Departamento de Política Jurídica de Seguridad de la Información<https://www.uned.es/dpj>, o a través de la Sede electrónica<https://sede.uned.es/> de la Universidad. Para más información visite nuestra Política de Privacidad<https://descargas.uned.es/publico/pdf/Politica_privacidad_UNED.pdf>.

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Postdoctoral Researcher opening at UT Austin
by Matt Lease 11 Jul '22

11 Jul '22

URL for this advertisement: <http://tiny.cc/postdocs> http://tiny.cc/ut-postdoc ------------------------------ Prof. Matt Lease <http://www.ischool.utexas.edu/~ml> is seeking a Postdoctoral Research Fellow to join his research lab <http://ir.ischool.utexas.edu/> at the University of Texas at Austin (UT Austin), USA. Applications will be reviewed as they are received, and the position will remain open until filled. Work Location. The candidate is expected to relocate to Austin, TX <https://www.ischool.utexas.edu/about/about-austin> (USA) for this position. Innovation and research come to life in Austin, known for its mix of culture and technology. Duration and Compensation. This postdoctoral position, with flexible start date, provides an initial year of support that is renewable for up to two additional years. Typically postdocs remain for multiple years unless they obtain a faculty position sooner. The salary will be $60,000 per year, plus a standard package of benefits. Responsibilities. The Fellow will be expected to pursue individual research and collaborative research projects: designing studies, collecting and analyzing data, disseminating findings, mentoring student researchers, attending regular meetings, and performing project administration. This position will be a 40 hour/week research appointment, with no obligation to teach, although teaching opportunities may be available if desired. About the Research. Our research spans Human Computation and crowdsourcing, Information Retrieval (IR), and Natural Language Processing (NLP). Our lab does both back-end artificial intelligence (AI) modeling and front-end human-computer interaction (HCI). We build and test predictive models, design ways to better annotate labeled data, and explore human-in-the-loop approaches for human-AI teaming. We think about building fair and transparent AI: e.g., how to build explainable AI systems that facilitate effective human-AI teaming, and how to annotate data in ways that mitigate AI bias. We conduct fundamental research and apply it to real-world problems, such as fighting fake news <https://sites.google.com/view/ut-misinformation-ai/> and hate speech. See our recent publications <https://www.ischool.utexas.edu/~ml/publications/> and talks <https://youtube.com/playlist?list=PLV4pUk6bTwEYCy8w_syoVFL-gYd6s4frL> in top conferences such as AAAI, ACL, AIES, CHI, CSCW, HCOMP, KDD, NeurIPS, and the Web Conference. Example research includes: - Annotation agreement and aggregation: WebConf’20 <https://www.ischool.utexas.edu/~ml/papers/braylan_web2020.pdf>, KDD’21 <https://utexas.box.com/v/braylan-kdd21>, WebConf’22 <https://utexas.box.com/v/braylan-webconf22> - Crowdsourcing task design: JAIR’20 <https://www.ischool.utexas.edu/~ml/papers/kutlu_jair20.pdf> (award), CSCW’21 <https://dl.acm.org/doi/10.1145/3476073ible-gold-can-help>, Frontiers’22 <https://www.frontiersin.org/articles/10.3389/frai.2022.828187/full> - Explainable fact-checking: AAAI’18 <https://www.ischool.utexas.edu/~ml/papers/nguyen-aaai18.pdf>, UIST’18 <https://www.ischool.utexas.edu/~ml/papers/nguyen-uist18.pdf>, CHIIR’22 <https://utexas.box.com/v/shi-chiir2022>, ACL’22 <http://x> - Hate speech detection: NeurIPS’21 <https://utexas.box.com/v/rahman-neurips21>, iConference’22 <https://utexas.box.com/v/prateek-iconf22> - Human-AI teaming: AIES’21 <https://dl.acm.org/doi/abs/10.1145/3461702.3462516>, ICJAI’21 <https://utexas.box.com/v/gao-ijcai2021> - Information Retrieval Evaluation: CIKM’18 <https://www.ischool.utexas.edu/~ml/papers/kutlu-cikm18.pdf>, SIGIR’18 <https://www.ischool.utexas.edu/~ml/papers/kutlu-sigir18.pdf>, ECIR’19 <https://www.ischool.utexas.edu/~ml/papers/gupta-ecir19.pdf> (award), ICTIR’20 <https://www.ischool.utexas.edu/~ml/papers/rahman-ictir20.pdf> - Multi-objective optimization: ICTIR’21 <https://utexas.box.com/v/gupta-ictir21>, UAI’22 <https://utexas.box.com/v/gupta-uai2022> - Supporting content moderators: HCOMP’20 <https://www.ischool.utexas.edu/~ml/papers/das_hcomp20.pdf>, CHI’21 <https://www.ischool.utexas.edu/~ml/papers/steiger-chi21.pdf> About UT Austin <http://www.utexas.edu/about/overview>. UT Austin is a nationally ranked, tier-one research institution. The university offers competitive salaries and benefits, an extensive support network, and above all, an enriching and highly collaborative community. Our Information School <https://www.ischool.utexas.edu/> (iSchool) is top-ranked <https://www.ischool.utexas.edu/news/texas-ischool-remains-top-tier-us-news-…>, and UT Austin has fantastic opportunities across campus in Computing Research <http://computing.utexas.edu/research>, such as our interdisciplinary Machine Learning Lab <https://ml.utexas.edu/> (including a NSF National Artificial Intelligence Research Institute <https://beta.nsf.gov/funding/opportunities/national-artificial-intelligence…>, the IFML <https://ifml.institute/>). Our university also boasts one of the world’s largest supercomputers <https://www.tacc.utexas.edu/> to facilitate compute intensive research (e.g., with clusters of large memory GPUs). Last but not least, the selected postdoc will have the opportunity to engage with researchers across campus in Good Systems <http://goodsystems.utexas.edu/>, an eight-year, Grand Challenge at UT Austin to design responsible AI technologies. About Austin, TX. Austin is one of the USA's sunniest and most vibrant cities in which to live and work. Our large and growing high-tech hub has further earned it the moniker of being the USA's "Silicon Hills <https://en.wikipedia.org/wiki/Silicon_Hills>". See https://www.austintexas.org/things-to-do/ How to Apply. Please email Matt Lease (ml(a)utexas.edu) with the subject "postdoc application”. Your email should: - Provide a current curriculum vitae (URL is fine) - Describe your interest and fit for the position - Describe one or more research projects or areas you would like to pursue. A formal Research Statement document is not required but welcome if available. Interviews will be conducted remotely via zoom, and candidates will be expected to present their research as part of the interview process. About the Faculty Supervisor. Matt Lease <http://www.ischool.utexas.edu/~ml> is a faculty member in the School of Information, with a secondary appointment in Computer Science <https://www.cs.utexas.edu/people/faculty-researchers/matthew-lease>. Lease is also an Amazon Scholar <https://www.amazon.science/scholars> in AWS’s Human-in-the-loop science team. Lease received early career awards from the NSF, IMLS, and DARPA. Recent honors include JAIR’s Award Winning Papers Track (2020), Best Student Paper at the European Conference for Information Retrieval (2019), and Best Paper at the Association for the Advancement of Artificial Intelligence (AAAI) Human Computation and Crowdsourcing conference (2016). Lease is a faculty founder and leader of Good Systems <http://goodsystems.utexas.edu>, an eight-year, university-wide Grand Challenge at UT Austin to design responsible AI technologies. Equal opportunity employment. The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions. -- Matt Lease Associate Professor School of Information University of Texas at Austin Voice: (512) 471-9350 · Fax: (512) 471-3971 · Office: UTA 5.536 http://www.ischool.utexas.edu/~ml

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Deadline extension: the 9th Argument Mining workshop
by Gabriella Lapesa 11 Jul '22

11 Jul '22

The 9th Argument Mining Workshop Special Theme: Argument Mining in Real-World Applications Shared task: Automated Assessment of Argument Validity and Novelty https://phhei.github.io/ArgsValidNovel/ ############################################################### NEWS WITH RESPECT TO THE PREVIOUS CFP: Extended deadline: July 18th 2022 Invited talk: Hans Hoeken (University of Utrecht), “Mining for Persuasive Ingredients: What’s the Right Mix?” Panel on applications of Argument Mining: - Legal: Laura Alonso Alemany (University of Cordoba) - Finance: Chung-Chi Chen (AIST) - Education: Beata Beigman Klebanov (ETS) - E-governance: Joonsuk Park (University of Richmond) - Business: Michael Yeomans (Imperial College London) Workshop date: October 17 ################################################################## Location: In conjunction with COLING 2022 in Gyeongju, Republic of Korea - in a hybrid format Webpage: https://argmining-org.github.io/2022/ Contact: argmining.org(a)gmail.com <mailto:argmining.org@gmail.com> Date: October 17 Final Call for Papers - Deadline extension (apologies for cross-posting) Argument mining (also known as "argumentation mining") is a growing research area within computational linguistics. At its heart, argument mining involves the automatic identification of argumentative structures in free text, such as the conclusions, premises, and inference schemes of arguments, as well as their pro- and con-relations. To date, researchers have investigated argument mining in many genres, such as legal documents, product reviews, news articles, online debates, Wikipedia articles, essays, academic literature, tweets, and dialogues. In addition, argument quality assessment and generation are also important problems. Argument mining gives rise to various practical applications of great importance. In particular, it provides methods that can find and visualize the main pro and con arguments in written text and dialogue and that enable argument search on the web for a topic of interest. In educational contexts, argument mining can be applied to written and diagrammed arguments for instructing and assessing students' critical thinking. In information retrieval, argument mining is expected to play a salient role in the emerging field of conversational search. We are looking for diverse research work on argument mining in real-world applications from various domains. Real-world applications include argument analysis in education, finance, law, public policy, and other social sciences, argument web search, opinion analysis in customer reviews, argument analysis in meetings, and scientific writing. CALL FOR PAPERS ArgMining 2022 invites the submission of long and short papers on substantial, original, and unpublished research in all aspects of argument mining. The workshop solicits LONG and SHORT papers for oral and poster presentations, as well as DEMOS of argument mining systems and tools. The topics for submissions include but are not limited to: • Automatic identification of argument components (premises and conclusions or more fine-grained), and relations between arguments and counterarguments (support and attack or more fine-grained) within/across documents • Automatic assessment of properties of arguments and argumentation, such as argumentation schemes, stance, quality, and persuasiveness • Automatic synthesis of arguments and their components, including the consideration of discourse goals (e.g., stages of a critical discussion or rhetorical strategies) and the possibly needed preceding analyses • Creation and evaluation of argument annotation schemes, relationships to linguistic and discourse annotations, (semi-) automatic argument annotation methods and tools, and creation of argumentation corpora • Management of spoken and transcribed dialogue, argument mining from such data, including additional challenges posed by real-time processing • Combination of NLP methods and AI models developed for argumentation, such as abstract and structured argumentation frameworks • Combination of information retrieval methods with argument mining, e.g. in order to build the next generation of argumentative (web) search engines • Use of argument mining for studying research questions from education, finance, law, public policy, digital humanities, and any other social sciences • Reflection on the ethical aspects and societal impact of argument mining methods Submission Information Three types of papers can be submitted: Long papers (8 pages + references), short papers (4 pages + references), and demo papers (4 pages + references). Demo papers must include a URL to a running demo. Accepted papers will be given an additional page to account for the reviewers' comments. All papers will be treated equally in the workshop proceedings. The workshop follows ACL’s policies for submission, review, and citation. Moreover, authors are expected to adhere to the ethical code set out in the ACL Code of Ethics. Submissions that violate any of the policies will be rejected without review. Please use the COLING 2022 style sheets for formatting your paper: https://coling2022.org/ Submission URL: https://www.softconf.com/coling2022/AM_2022 The workshop is running a double-blind review process. In preparing your manuscript, do not include any information which could reveal your identity, or that of your co-authors. The title section of your manuscript should not contain any author names, email addresses, or affiliation status. If you do include any author names on the title page, your submission will be automatically rejected. In the body of your submission, you should eliminate all direct references to your own previous work. That is, avoid phrases such as "this contribution generalizes our results for XYZ". Also, please do not disproportionately cite your own previous work. In other words, make your submission as anonymous as possible. We need your cooperation in our effort to maintain a fair, double-blind reviewing process - and to consider all submissions equally. Double Submission Papers that have been or will be submitted to other venues should indicate this at submission time. Upon acceptance at either event, the submission must be withdrawn from the other. To save reviewers' efforts, avoid submitting (or withdraw early) papers that are on track to be accepted elsewhere. Important Dates • Submission due: July 18, 2022 • Notification of acceptance: August 25, 2021 • Camera-ready papers due: September 5, 2022 • Workshop: TBD: COLING 2022 October 12-17, 2022 All deadlines are 11:59 pm UTC -12h (“anywhere on Earth”). ORGANIZERS Gabriella Lapesa (University of Stuttgart) Jodi Schneider (University of Illinois Urbana-Champaign) Yohan Jo (Amazon) Sougata Saha (University at Buffalo, New York) SHARED TASK: AUTOMATED ASSESSMENT OF ARGUMENT VALIDITY AND NOVELTY Organizers: Philipp Heinisch, Philipp Cimiano (University of Bielefeld), Anette Frank, and Juri Opitz (University of Heidelberg) Webpage: https://phhei.github.io/ArgsValidNovel/ Brief description In recent years, there have been increased interests in understanding how to assess the quality of arguments systematically. To foster more research on this topic in the community, we plan to organize a task consisting of assessing whether computational models can reliably assess the validity and novelty of a conclusion given a set of the textual premises. Tasks Participants can choose either Task A or Task B, or both. Task A: The first task consists of a binary classification task along the dimensions of novelty and validity, classifying a conclusion as being valid/novel or not given a textual premise. Task B: The second subtask will consist in comparing two conclusions in terms of validity / novelty.

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2nd Call for Papers - CODI 2021: 2nd Workshop on Computational Approaches to Discourse
by Chloé Braud 09 Jul '22

09 Jul '22

2nd Call for Papers - CODI 2021: 2nd Workshop on Computational Approaches to Discourse https://sites.google.com/view/codi-2021 Held in conjunction with EMNLP 2021 November 10-11, 2021 Update: Note that we accept double submissions, see the dedicated section below. Important information: The CODI workshop organization should be hybrid, following the EMNLP program chairs’ decision: “EMNLP 2021 is currently officially scheduled to be held in hybrid mode, online and in Punta Cana, in the Dominican Republic. ”. The 2-days workshop will take place on November 10 and 11. **Aims and scope** The last five years have seen a dramatic improvement in the ability of NLP systems to understand and produce words and sentences. This development has created a renewed interest in discourse problems as researchers move towards the processing of long-form text and conversations. There is a surge of activity in discourse parsing, coherence models, text summarization, corpora for discourse level reading comprehension, and discourse related/aided representation learning, to name a few. At this juncture, we envision that a workshop that brings together discourse experts and upcoming researchers will catalyze the speed and knowledge needed to solve such problems, as well as serve as a forum for the discussion of suitable datasets and reliable evaluation methods. The previous workshops on discourse in machine translation (DiscoMT), linking lexical, sentential and discourse semantics (LSDSem), discourse structure in natural language generation (DSNNLG), discourse parsing and treebanking (DisRPT) and coreference (CORBON/ CRAC), have shown that there is considerable interest and success in bringing together the community working on specific problems. We believe that the discourse community will also benefit from a general forum where work ranging from corpus development/analysis to computational models, and evaluation is discussed, and desiderata can be drawn for future progress. The Workshop on Computational Approaches to Discourse (CODI) brings together researchers interested in all aspects of discourse and its computational modeling. The first CODI workshop was held at EMNLP 2020 and showcased diverse discourse research (see the papers presented: https://codi-workshop.github.io/accepted-papers/). This year, the workshop will also host two shared tasks: - CODI-CRAC - Anaphora Resolution in Dialogues: https://competitions.codalab.org/competitions/30312 - CODI-DISRPT2021- Discourse Relation Parsing and Treebanking: https://sites.google.com/georgetown.edu/disrpt2021 Please visit the corresponding websites for more information. **Topics of interest** We welcome symbolic and probabilistic approaches, corpus development and analysis, as well as machine and deep learning approaches to discourse. We appreciate theoretical contributions as well as practical applications, including demos of systems and tools. The goal of the workshop is to provide a forum for the community of NLP researchers working on all aspects of discourse. Topics of interest include, but are not limited to:- discourse structure - discourse connectives - discourse relations - annotation tools and schemes for discourse phenomena - corpora annotated with discourse phenomena - discourse parsing - cross-lingual discourse processing - cross-domain discourse processing - anaphora and coreference resolution - event coreference - argument mining - coherence modeling - discourse and semantics - discourse in applications such as machine translation, summarization, etc. - evaluation methodology for discourse processing **Submissions** We solicit four categories of papers: (1) regular workshop papers, (2) demos, (3) extended abstracts and (4) shared tasks papers. Only regular workshop papers, shared task papers and demos will be included in the proceedings as archival publications. Regular papers must describe original unpublished research. Long papers may consist of up to 8 pages of content, plus unlimited pages for references. Short papers can have up to 4 pages, plus unlimited pages for references. Demo submissions may describe systems, tools, visualizations, etc., and may consist of up to 4 pages, plus unlimited pages for references. Accepted long, short, and demo papers will be presented orally. Extended abstracts can describe work in progress or those already published elsewhere. These may be two pages long (without references). Extended abstracts are non-archival. They will be presented orally, and included in the workshop program and handbook, but will not appear in the workshop proceedings. For shared task papers, please refer to the corresponding websites:- CODI-CRAC: https://competitions.codalab.org/competitions/30312#learn_the_details-overv… - CODI-DISRPT2021: https://sites.google.com/georgetown.edu/disrpt2021/submission?authuser=0 Shared task papers will be presented during the dedicated sessions, either orally or as posters. They will be included in the workshop proceedings. Final versions of all types of papers will be given one additional page of content. **Double submission** We allow for double submissions. Please indicate during submission to which other conference or workshop your work has been submitted. We may also invite authors of papers accepted to the conferences (e.g. EMNLP, ACL) including Findings to present their work at the workshop. Please indicate whether your paper has been accepted to e.g. ACL during submission, or let us know by email that your paper has been accepted elsewhere (including Findings) upon notification. These papers will not be part of the proceedings of the workshop. **Submission website** All submissions must follow the EMNLP 2020 formatting instructions described here: https://2021.emnlp.org/call-for-papers/style-and-formatting Please submit your papers using the link indicated on our website. **Important dates** * 18 May, 2021: 1st Call for Workshop Papers * 15 June, 2021: 2nd Call for Workshop Papers * 5 July, 2021: Anonymity period starts * 15 July, 2021: 3rd Second Call for Papers * 5 Aug, 2021: Workshop Papers Due (long, short, demo, extended abstracts) * 5 Sept, 2021: Notification of Acceptance * 15 Sept, 2021: Camera-ready papers due * Nov 10-11, 2021: Workshop Date Please check the dedicated websites to get information about the deadlines for the two shared tasks. All deadlines are 11.59 pm UTC -12h (“anywhere on Earth”).

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CfP (updated deadline): 16th Workshop on Graph-Based Natural Language Processing (TextGraphs-16)
by Alexander Panchenko 09 Jul '22

09 Jul '22

Venue: COLING 2022 Location: Gyeongju, Republic of Korea Date: October 16, 2022 Papers Due: July 17, 2022 (Sunday) 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 17, 2022 (Sunday) - Notification of Acceptance: August 28, 2022 (Sunday) - Camera-ready papers due: September 11, 2022 (Sunday) - Conference date: October 16, 2022 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. - Submit papers by the end of the deadline day (timezone is UTC-12) via our Softconf Submission Site: https://www.softconf.com/coling2022/TextGraphs-16/ Shared Task We invite participation in the 1st Shared Task on Natural Language Premise Selection associated with the 16th Workshop on Graph-Based Natural Language Processing (TextGraphs 2022). The task proposed this year is the Natural Language Premise Selection (NLPS) (Ferreira et al., 2020a), inspired by the field of automated theorem proving. The task of NLPS takes as input a mathematical statement, written in natural language, and outputs a set of relevant sentences (premises) that could support an end-user finding a proof for that mathematical statement. The premises are composed of supporting definitions and propositions that can act as explanations for the proof process: https://codalab.lisn.upsaclay.fr/competitions/5692 Contact Please direct all questions and inquiries to our official e-mail address ( textgraphsOC(a)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. Organizers - Dmitry Ustalov, Yandex - Yanjun Gao, University of Wisconsin-Madison - Abhik Jana, University of Hamburg - Thein Huu Nguyen, University of Oregon - Gerald Penn, University of Toronto - Arti Ramesh, ETS AI Labs - Alexander Panchenko, Skolkovo Institute of Science and Technology - Mokanarangan Thayaparan, University of Manchester & Idiap Research Institute - Marco Valentino, University of Manchester & Idiap Research Institute

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The first workshop on Transcript Understanding at COLING 2022
by Viet Lai 09 Jul '22

09 Jul '22

Call for Paper: 1st workshop on Transcript Understanding Venue: COLING 2022 Location: Gyeongju, Republic of Korea Submission deadline: July 25, 2022 Submission Site: https://www.softconf.com/coling2022/TU Workshop Website: https://tuworkshop.github.io Overview: Videos have become an omnipresent source of knowledge: courses, presentations, conferences, documentaries, livestreams, meeting recordings, vlogs. This has created a strong demand for transcript understanding. However, the quality of audio and video content shared online and the nature of speech, video transcripts pose many challenges to the existing natural language processing technologies. At the First workshop on Transcript Understanding (TU@COLING2022), we aim to bring together researchers from various domains to make the best of the knowledge that all these videos contain. Researchers from related domains are invited to paper on recent advanced technologies, resources, tools, and challenges for Transcript Understanding. Topics: The TU workshop holds a research track and a shared task track. The research track aims to explore recent advances and remaining challenges on video transcript understanding. As this topic is a multi-modal subject, researchers from artificial intelligence, computer vision, speech processing, natural language processing, data mining, statistics, and other fields are invited to submit papers on recent advances, resources, tools, challenges for video transcript understanding. To this end, the topics of the workshop include but are not limited to the following: - Fundamental processing for video transcript, such as punctuation restoration, chunking, parsing, and named entity recognition. - Subtitle segmentation - Text summarization and keyword extraction for transcripts - Event extraction, intent detection, and slot filling - Sentiment analysis for speech text processing - Noisy text processing - Fact-checking, evidence extraction - Question-Answering extraction from transcripts - Automatic Speech Recognition, and related system such as speaker identification and filler word detection - Multi-modal, multilingual video-speech-text processing Important Dates Papers Due: July 25, 2022 (Monday) Notification of Acceptance: August 22, 2022 (Monday) Camera-ready papers due: September 5, 2022 (Monday) Workshop proceedings due: September 19, 2022 (Monday) Workshop date: October 17, 2022 All deadlines are “anywhere on earth” (UTC-12) Submissions: Authors are invited to submit their unpublished work that represents novel research. The papers should be written in English using the *ACL style. Authors can also submit the supplementary materials, including technical appendices, source codes, datasets, and multimedia appendices. All submissions, including the main paper and its supplementary materials, should be fully anonymized. For more information on formatting and anonymity guidelines, please refer to COLING 2022 submission guidelines. TU accepts both long papers (8 pages) and short papers (4 pages). The paper can include unlimited appendix and references. Upon the acceptance, the authors are provided with 1 more page to address the reviewer comments. All papers will be double blind peer reviewed. Two reviewers with the same technical expertise will review each paper. Authors of the accepted papers will present their work in either the Oral or Poster session. All accepted papers will appear on the workshop proceedings that will be published on CEUR-WS. The authors will keep the copyright of their papers that are published on CEUR-WS. The workshop proceedings will be indexed by DBLP. Both research paper and shared task paper must be submitted using SoftConf at https://www.softconf.com/coling2022/TU/. We look forward to seeing you all at the virtual conference. TU@COLING2022 Organizers: Franck Dernoncourt (Adobe Research, USA) Thien Huu Nguyen (University of Oregon, USA) Viet Dac Lai (University of Oregon, USA) Amir Pouran Ben Veyseh (University of Oregon, USA)

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FigLang 2022 (co-located with EMNLP 2022): Shared Task on Euphemism Detection
by Anna Feldman 08 Jul '22

08 Jul '22

https://sites.google.com/view/figlang2022/shared-tasks?authuser=0 Euphemism Detection Shared Task Euphemisms are mild or indirect expressions used in place of harsher or more offensive ones. Euphemisms are often used to mask profanity or refer to taboo topics such as death, disability, sex, religion or personal relationships in a polite way. Euphemisms are often ambiguous: their literal and non-literal interpretation is context-dependent: Asked to choose *between jobs* and the environment, a majority -- at least in our warped, first-past-the-post system -- will pick jobs. [non-euphemistic] vs. This summer, the budding talent agent was *between jobs* and free to babysit pretty much any time. [euphemistic] The state of the art language models perform well on many major NLP benchmarks; however, it is unclear how such models perform on euphemisms. Thus, we propose a euphemism detection task: given an input sentence, identify whether the sentence contains a euphemism. For more information about the shared task and to participate visit https://codalab.lisn.upsaclay.fr/competitions/5726 <https://www.google.com/url?q=https%3A%2F%2Fnam10.safelinks.protection.outlo…> . *Important dates:* - July 5, 2022: CodaLab competition is open; training data can be downloaded - Aug 5, 2022: Test data can be downloaded and results submitted; performance will be tracked on CodaLab dashboard - Aug 20, 2022: Last day for submitting predictions on test data - Sept 7, 2022: Papers describing the systems are due - Oct 9, 2022: Notification of acceptance - TBD, 2022: Camera-ready papers due - December 7 or 8, 2022: Workshop -- ********************************************** Anna Feldman, Ph.D. Professor of Linguistics and Computer Science Graduate Program Coordinator & Chair of Linguistics Montclair State University http://www.purl.org/net/fa <http://www.purl.org/NET/fa>

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FigLang2022 Shared Task on “Understanding Figurative Language” (competition opens July 10, 2022)
by Smaranda Muresan 08 Jul '22

08 Jul '22

Shared Task on Understanding Figurative Language at FigLang2022 We are happy to announce a new shared task on Understanding Figurative Language as part of the Figurative Language Workshop (FigLang 2022) at EMNLP 2022. In recent years, there have been several benchmarks dedicated to figurative language understanding, which generally frame "understanding" as a recognizing textual entailment task -- deciding whether one sentence (premise) entails/contradicts another (hypothesis) (Chakrabarty et al 2021, Stowe et al 2022). We introduce a new shared task for figurative language understanding around this textual entailment paradigm, where the hypothesis is a sentence containing the figurative language expression (e.g., metaphor, sarcasm, idiom, simile) and the premise is a literal sentence containing the literal meaning. There are two important aspects of this task: 1) the task requires not only to generate the label (entail/contradict) but also to generate a plausible explanation for the prediction; 2) the entail/contradict label and the exploration are related to the meaning of the figurative language expression. For more information about the shared task, including the link to the datasets, evaluation metrics and scripts important dates please visit the Shared task website (https://figlang2022sharedtask.github.io/). Participants can use the following CodaLab ( https://codalab.lisn.upsaclay.fr/competitions/5908) link to participate in the task as well as submit the predictions. Important dates: · July 10, 2022: CodaLab competition is open; training data can be downloaded · Aug 15, 2022: Test data (available only to registered participants) can be downloaded and results submitted; performance will be tracked on CodaLab dashboard · Aug 20, 2022: Last day for submitting predictions on test data · Sept 7, 2022: Papers describing the systems are due · Oct 9, 2022: Notification of acceptance · TBD, 2022: Camera-ready papers due · December 8, 2022: Workshop at EMNLP 2022 Organizing Team Tuhin Chakrabarty, Columbia University; tuhin.chakr(a)cs.columbia.edu Arkadiy Saakyan, Columbia University; as5423(a)columbia.edu Debanjan Ghosh, Educational Testing Service; dghosh(a)ets.org Smaranda Muresan, Data Science Institute, Columbia University;smara(a)columbia.edu

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[CFP] Dialogue & Discourse journal: Fall 2022 Regular Issue
by Ryuichiro Higashinaka 07 Jul '22

07 Jul '22

Apologies for cross-posting It is our pleasure to announce the first call for submissions for the next issue of the journal Dialogue and Discourse. Submissions are invited on all topics in the formal, computational, or psycholinguistic study of dialogue and discourse. Submissions received by August 1, 2022 will be considered for the next regular issue. Later submissions will be slated for the next available issue. http://www.dialogue-and-discourse.org/cfps-current.shtml Dialogue and Discourse (D&D http://www.dialogue-and-discourse.org/) is the first peer-reviewed free open access journal dedicated exclusively to work that deals with language "beyond the sentence". The journal adopts an interdisciplinary perspective, accepting work from Linguistics, Computer Science, Psychology, Sociology, Philosophy, and other associated fields with an interest in formally, technically, empirically or experimentally rigorous approaches. Descriptive papers should make a substantial theoretical contribution to be considered. We are committed to ensuring the highest editorial standards and rigorous peer-review of all submissions, while granting open access to all interested readers. D&D has published regular issues every year since 2010, and occasionally special issues on common topics. As of June 2022, D&D has published 99 papers, and the journal's h-index is 26. D&D is endorsed by ACL SIGdial, ACL SemDial, and AMLaP. D&D is indexed by Scopus and the European Reference Index for the Humanities and Social Sciences. Submissions are made via the online submission system at http://www.dialogue-and-discourse.org/submission.shtml. Authors are required to indicate if a submission is an extended version of one or more previously published conference papers (to which we would expect substantial additions); simultaneous submission to another venue is prohibited. Submissions will undergo rigorous peer-review. Once accepted and finalized, papers will appear online immediately, as part of the current issue. Selected papers will furthermore be offered the opportunity to present a poster at the following SIGDIAL Conference. Dialogue and Discourse Editors Issue Editor: Ryuichiro Higashinaka (Volume 13, Issue 2) Junyi Jessy Li (Volume 13, Issue 1) Editor In Chief: Barbara Di Eugenio, University of Illinois at Chicago, United States Associate Editors: Vera Demberg, Saarland University, Germany Kallirroi Georgila, University of Southern California, United States Jonathan Ginzburg, Université Paris-Diderot (Paris 7), France Pat Healey, Queen Mary University London, United Kingdom Ryuichiro Higashinaka, Nagoya University, Japan Junyi Jessy Li, University of Texas at Austin, United States Massimo Poesio, Queen Mary University London, United Kingdom Manfred Stede, University of Potsdam, Germany David R. Traum, University of Southern California, United States Amir Zeldes, Georgetown University, United States Full editorial board at: http://www.dialogue-and-discourse.org/editors.shtml

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Announcement: Release of BabelNet 5.1
by Roberto Navigli 07 Jul '22

07 Jul '22

We are proud to announce the release of a new version of BabelNet <https://babelnet.org/> and its APIs, *both Java and the brand-new Python version*, developed jointly by the Sapienza NLP Group <http://nlp.uniroma1.it> of the *Sapienza University of Rome* under the supervision of prof. Roberto Navigli <https://www.diag.uniroma1.it/navigli/> and Babelscape <http://babelscape.com/>, *a successful deep-tech multilingual NLP Company* providing innovative solutions for multilingual NLP. BabelNet -- winner of the *prominent paper award 2017* from the Artificial Intelligence Journal and the META prize 2015, and covered in media such as The Guardian <https://www.theguardian.com/news/2018/feb/23/oxford-english-dictionary-can-…> and Time magazine <http://wwwusers.di.uniroma1.it/~navigli/img/Redefining_the_modern_dictionar…> -- is today’s *most far-reaching multilingual resource* which, according to need, can be used as an *encyclopedic dictionary*, or a *semantic network* or a huge *knowledge base/ontology*. It has been used by more than *1000 universities and research institutions*, enabling multilinguality in several fields of AI and NLP, such as semantic search, Word Sense Disambiguation, Semantic Role Labeling and image tagging. BabelNet was created by means of the seamless integration and interlinking of the largest multilingual Web encyclopedia - i.e., Wikipedia - with the most popular computational lexicon of English - i.e., WordNet, and other lexical resources such as Wiktionary, OmegaWiki, Wikidata, dozens of wordnets, Wikiquote, GeoNames, and ImageNet. BabelNet provides *multilingual synsets*, i.e., concepts and named entities lexicalized in many languages, and connected with large amounts of semantic relations. *Version 5.1* comes with the following features: - *500 languages* and *22 million synsets* covered; - *53 resources *linked and integrated; - *Wikipedia* and *Wikidata* updated thanks to *BabelNet live*; - *Open English WordNet* has been updated to version 2021; - Added *Q-codes* identifiers (e.g. https://www.hetop.eu/hetop/3CGP/?la=en&rr=CGP_QC_QD8); - Added *string tags *from *Wikipedia labels*; - *French wordnets cleaned up* by removing most potentially incorrect translations; - *Italian wordnet definitions *cleaned up; - *General data cleanup* (glosses, senses, Named Entity vs. concept labels); - *Lemma casing corrected in 24 languages* (English, Italian, Spanish, German, French, Dutch, Polish, Portuguese, Russian, Bulgarian, Czech, Danish, Greek, Estonian, Finnish, Croatian, Hungarian, Lithuanian, Latvian, Maltese, Romanian, Slovak, Slovenian, Swedish). More statistics are available at: babelnet.org/statistics. Kind regards, The BabelNet team -- ============================================== Roberto Navigli* - Professor* Department of Computer, Control and Management Engineering Sapienza University of Rome Via Ariosto, 25 00185 Roma Italy Phone: +39 06 77274109 Home Page: https://www.diag.uniroma1.it/navigli/ Sapienza NLP Group: http://nlp.uniroma1.it Co-founder of Babelscape <https://babelscape.com> ==============================================

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