- Corpora - ELRA lists

Call for Papers: The First Workshop on Context-aware NLP in eHealth, ICON 2022, India
by Mohammed Hasanuzzaman 29 Oct '22

29 Oct '22

Dear List members, WNLPe-Health 2022 - the first Workshop on Context-aware NLP in eHealth will be held at IIIT Delhi, India on December 15th, 2022 in conjunction with 19th International Conference on Natural Language Processing (ICON 2022) . It is currently recognised that as much as 30% of the world’s stored data is produced by the healthcare sector. However, this ‘data-rich’ sector does not currently explore data to the full potential which may allow the development of much more individual and person-centred AI technologies. For example, by combining ubiquitous data with user-generated and publicly available data, AI algorithms can guide and inform citizens about risk modifying behaviors in an appropriate context. Context can be defined as “any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant for the interaction between a user and an application, including the user and applications themselves.” The goal of this workshop is to provide a unique platform to bring together researchers and practitioners in healthcare informatics working with health-related data, especially textual data, and facilitate close interaction among students, scholars, and industry professionals on eHealth language processing tasks. In particular, we are interested in works that advance state-of-the-art NLP and ML techniques for eHealth domains by incorporating more contextual knowledge in order to make models explainable, trustable and robust in changing situations. We are interested in research on novel approaches, works in progress, comparative analyses of tools, and advancing state-of-the-art work in eHealth NLP methods, tools, and applications. Relevant topics for the workshop include, but are not limited to, the following areas: - Modelling of healthcare text in classical NLP tasks (tagging, chunking, parsing, entity identification, relation extraction, coreference, summarization, etc.) for under-resourced languages. - Person-centred NLP applications for eHealth including early risk prediction. - Algorithm for Context Data reasoning. - Context sensitive recommendations to individual citizens and patients. - Integration of structured and unstructured resources for health applications. - Domain adaptation techniques for clinical data. - Medical terminologies and ontologies. - Interpretability and analysis of NLP models for healthcare applications. - Processing clinical literature and trial reports. - Bayesian modelling and feature selection techniques for high-dimensional healthcare data. - Multimodal learning for decision support systems: Ubiquitous data, public databases, user generated content (in combination with wearable sensor technology). Full paper submissions are limited to 8 pages, while short paper submissions should be less than 4 pages (including bibliography). For more information: https://sites.google.com/view/wnlpe-health2022/submissions Important Dates Paper submission deadline: 20th November, 2022 (23:59 Hawaii Standard Time) Notification of acceptance: 26th November, 2022 Camera ready copy deadline: 1st December, 2022 Workshop date: 15th December, 2022 Best regards, Mohammed <https://sites.google.com/view/wnlpe-health2022/submissions#h.jxoic3mpxg99> Important Dates Paper submission deadline: 20th November, 2022 (23:59 Hawaii Standard Time) Notification of acceptance: 26th November, 2022 Camera ready copy deadline: 1st December, 2022 Workshop date: 15th December, 2022 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ *Dr. Mohammed Hasanuzzaman, Lecturer, Munster Technological University <https://www.mtu.ie/> * *Funded Investigator, ADAPT Centre- <https://www.adaptcentre.ie/> A <https://www.adaptcentre.ie/>* World-Leading SFI Research Centre <https://www.adaptcentre.ie/> *Member, Lero, the SFI Research Centre for Software <https://lero.ie/>**C**hercheur Associé*, GREYC UMR CNRS 6072 Research Centre, France <https://www.greyc.fr/en/home/> *Associate Editor:** IEEE Transactions on Affective Computing, Nature Scientific Reports, IEEE Transactions on Computational Social Systems, ACM TALLIP, PLOS ONE, Computer Speech and Language* Dept. of CS Munster Technological University Bishopstown campus Cork e: mohammed.hasanuzzaman(a)adaptcentre.ie <email(a)adaptcentre.ie>/ Ireland https://mohammedhasanuzzaman.github.io/ [image: Mailtrack] <https://mailtrack.io?utm_source=gmail&utm_medium=signature&utm_campaign=sig…> Sender notified by Mailtrack <https://mailtrack.io?utm_source=gmail&utm_medium=signature&utm_campaign=sig…> 29/10/22, 02:19:47

1 0

Internship at GETALP-LIG-UGA - 5/6 months : Context-Aware Neural Machine Translation Evaluation
by Emmanuelle Esperança-Rodier 28 Oct '22

28 Oct '22

Dear colleagues, Please find hereafter an internship proposal. Feel free to transfer it to your M2 students. Kind regards ---------------------------------------------------------------------------------------------------------------------------------- The LIG (Laboratoire d'Informatique de Grenoble) proposes the following Master 2 level internship: Title: Context-Aware Neural Machine Translation Evaluation Description: Context-Aware Neural Machine Translation (CA-NMT) [Tiedemann and Scherrer, 2017; Laubli et al., 2018; Miculicich et al., 2018; Maruf et al., 2019; Zheng et al., 2020; Ma et al. 2021; Lupo et al., 2022] is currently one of the main research axes in NLP, with strong impact on both academic and company research. CA-NMT systems are evaluated with both "average-quality-measuring" metrics such as BLEU [Papineni et al., 2002], and dedicated contrastive test suites [Voita et al., 2019; Muller&Rios 2018; Lopes et al., 2020]. The latter have been designed to measure specifically to which degree CA-NMT systems are able to exploit context while scoring sentences to be translated in context. Indeed the average translation quality measured by BLEU has been shown inadequate in this respect [Lupo et al., 2022]. When evaluating models with contrastive test suites however, models are only asked to score sentences and not to translate them. The ability of models to use context is thus only implicitly evaluated. With the work planned in this internship we would like to make a step ahead in the evaluation of CA-NMT systems. The idea is to exploit annotated data like those already used for [Muller&Rios 2018; Lopes et al., 2020] to explicitly involve discourse phenomena, such like coreferences and anaphora, in the evaluation procedure of CA-NMT models. Such evaluation procedure will allow possibly to design more accurate and adequate evaluation measures for "discourse-phenomena-aware" CA-NMT systems. Practical Aspects: In this internship the student will use Machine Learning and Deep Learning tools to automatically annotate parallel data (at least English-French, but possibly also English-German and other language pairs) used for NMT with discourse phenomena, as well as Neural Machine Translation tools for automatically generating translations that will be used for CA-NMT evaluation. Based on the annotation of discourse phenomena, we will design an adequate evaluation metric for CA-NMT systems, taking into account the capability of the system to exploit discourse phenomena. Finally, the evaluation metric will be tested by evaluating CA-NMT systems already available or trained from scratch at LIG by the student. Profile: Master 2 student level in computer science or NLP Interested in Natural Language Processing and Deep Learning approaches Skills in machine learning for probabilistic models Computer science skills: Python programming. Some knowledge of deep learning libraries such like Pytorch (Fairseq would be a plus). Data manipulation and annotation The internship may last from 5 up to 6 months, it will take place at LIG laboratory, GETALP team (http://lig-getalp.imag.fr/ <http://lig-getalp.imag.fr/>), starting from January/February 2022. The student will be tutored by Marco Dinarelli (http://www.marcodinarelli.it <http://www.marcodinarelli.it/>), andEmmanuelle Esperança-Rodier (https://lig-membres.imag.fr/esperane/ <https://lig-membres.imag.fr/esperane/>) Interested candidates must send a CV and a motivation letter to (both adresses) marco.dinarelli(a)univ-grenoble-alpes.fr <mailto:marco.dinarelli@univ-grenoble-alpes.fr>, Emmanuelle.Esperanca-Rodier(a)univ-grenoble-alpes.fr <mailto:Emmanuelle.Esperanca-Rodier@univ-grenoble-alpes.fr>. [Tiedemann and Scherrer, 2017] Neural ma- chine translation with extended context. Workshop on Discourse in Machine Translation 2017. [Laubli et al., 2018] Has machine translation achieved human parity? a case for document-level evaluation. EMNLP 2018. [Miculicich et al. 2018] Document-level neural machine translation with hierarchical attention networks. EMNLP 2018. [Maruf et al., 2019] Selective attention for context-aware neural machine translation. NAACL 2019. [Zheng et al., 2020] Towards Making the Most of Context in Neural Machine Translation. IJCAI 2020. [Ma et al., 2021] A Comparison of Approaches to Document-level Machine Translation. arXiv pre-print 2021. [Lupo et al., 2022] Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models. ACL 2022. [Papineni et al., 2022] Bleu: a method for automatic eval- uation of machine translation. ACL 2002. [Voita et al., 2019] "When a good translation is wrong in context: Context-aware machine translation improves on deixis, ellipsis, and lexical cohesion". ACL 2019. [Muller&Rios 2018] "A large-scale test set for the evaluation of context-aware pronoun translation in neural machine translation." CMT 2018 [Lopes et al., 2020] "Document-level neural MT: A systematic comparison". EAMT 2020 ---------------------------------------------------------------------------------------------------------------------------------- ___________________________________________ Emmanuelle Esperança-Rodier Enseignante-Chercheuse en Linguistique Informatique (Section 7) Maîtresse de Conférences - Hors Classe UMR 5217 - LIG (Laboratoire d’Informatique de Grenoble) GETALP (Groupe d’Étude en Traduction Automatique/Traitement Automatisé des Langues et de la Parole) Bâtiment IMAG - 700 avenue Centrale - Domaine Universitaire de Saint-Martin-d’Hères 04 57 42 14 92 Service des Langues UGA Coordinatrice des enseignements d’anglais pour la composante IM2AG - Mathématiques

1 0

Internship offer (with PhD opportunity), LS2N, Nantes, France. Diving into neural language models for improving discourse analysis tasks
by Nicolas HERNANDEZ 28 Oct '22

28 Oct '22

* Title: Diving into neural language models for improving discourse analysis tasks * Keywords: Neural Language Models, Discourse analysis, Argumentative structure, Probing, Transfer Learning * Supervisors: Nicolas.Hernandez(a)univ-nantes.fr and Laura.Monceaux(a)univ-nantes.fr * Location: TALN@LS2N, Nantes, France - https://taln-ls2n.github.io * Starting date: Jan-2023 (flexible) ~6 months * Opportunity: to pursue a PhD in the Lexhnology ANR project https://www.ls2n.fr/stage-these/diving-into-neural-language-models-for-impr… # MISSION Fine-tuning a pre-trained language model has become the de facto standard for handling natural language processing tasks. Since many of these tasks are dealing with discourse and dialogue structures (e.g. conversational agent, summarization, dialogue acts recognition, argumentation mining), it is crucial to understand how such information is captured by the language models and to study how to intervene on the learning of this type of information: what is learned, what is missing, how to add it, how to keep the useful information in a fine-tuned, distilled, pruned or quantized model... The internship mission will be defined in this context, collaboratively with the candidate. One possibility would be to start by probing the language models on discourse analysis tasks. We wish the successful candidate to pursue a PhD on the subject in the Lexhnology project. * A. Rogers, O. Kovaleva, and A. Rumshisky. A Primer in BERTology: What We Know About How BERT Works. Transactions of the Association for Computational Linguistics (TACL), 8:842–866. 2020. * V. Araujo, A. Villa, M. Mendoza, M.-F. Moens, and A. Soto, “Augmenting BERT-style Models with Predictive Coding to Improve Discourse-level Representations,” In EMNLP, Nov. 2021. * M. Lukasik, B. Dadachev, G. Simões, & K. Papineni, Text Segmentation by Cross Segment Attention, In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 4707–4716, November 16–20, 2020. * L. Huber, C. Memmadi, M. Dargnat, and Y. Toussaint. Do sentence embeddings capture discourse properties of sentences from scientific abstracts ? In the First ACL Workshop on Computational Approaches to Discourse, 86–95, 2020. * F. Koto, J. H. Lau, and T. Baldwin. Discourse Probing of Pretrained Language Models. In Proceedings of the 20th Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), Mexico (virtual), 2021 # THE LEXHNOLOGY PROJECT Lexhnology is a project funded by the French National Agency (ANR). It will start on January 2, 2023 for a period of 42 months. Given the growing extraterritoriality of American law, this domestic law is increasingly impacting other countries' jurisdiction. It is of prime importance that second-language (L2) users of legal English be able to analyze case law. Teaching the argumentative structure to L2 learners is a widely accepted method in languages for specific purposes (LSP) L2 teaching/learning and may help learners understand the legally-binding rationale behind judicial decisions. Despite this context, consensus about the linguistic definition of the communicative functions, also known as moves, in case law does not yet exist. In addition, no Natural Language Processing (NLP) techniques are currently able to automatically identify moves in case law. Finally, the effectiveness of making moves explicit to L2 learners has not been measured experimentally. To answer these questions, Lexhnology will take an innovative interdisciplinary approach – linguistic, NLP, LSP teaching/learning. The project is the joint collaboration of four laboratories, namely LS2N, CRINI, LAIRDIL and ATILF. # APPLICATION The successful candidate is expected to: * Have/Prepare a Master Degree (or equivalent) in Natural Language Processing, Computer Sciences, Computational Linguistics or Data sciences, * Have a excellent background in deep learning and more generally machine learning, * Have strong programming skills (software dev. and python) * Have good verbal communication and writing skills (in French/English) * Have facility with teamwork as well as working autonomously * Be dynamic and curious We look forward to receiving your meaningful online application including: * a letter of motivation * a CV * contacts for two references

1 0

[Jobs] ELLIS PhD Program: 150+ PhD positions in machine learning (incl. NLP)
by lynn.anthonissen＠uni-tuebingen.de 28 Oct '22

28 Oct '22

Apply by November 15, 2022, to join the ELLIS PhD Program in 2023 – Details at: https://ellis.eu/news/ellis-phd-program-call-for-applications-2022 The ELLIS PhD program has launched its yearly recruiting round and is now accepting applications. A key pillar of the ELLIS initiative, the program's central aim is to foster and educate the best talent in machine learning and related research areas by pairing outstanding students from across the globe with leading researchers in Europe. The program also offers a variety of networking and training activities. Each PhD student is co-supervised by two ELLIS scientists based in different European countries. Over the course of their degree, students complete a mandatory exchange of at least six months at their co-advisor's lab. One of the advisors may also come from industry, in which case the student will collaborate closely with the industry partner and spend their exchange conducting research at an industrial lab. Research areas include (but are not limited to) the following machine learning-driven research fields: - AutoML - Bayesian & Probabilistic Learning - Bioinformatics - Causality - Computational Neuroscience - Computer Graphics - Computer Vision - Deep Learning - Earth & Climate Sciences - Health - Human Behavior, Psychology & Emotion - Human Computer Interaction - Human Robot Interaction - Information Retrieval - Interactive & Online Learning - Interpretability & Fairness - Law & Ethics - Machine Learning Algorithms - Machine Learning Theory - ML in Chemistry & Material Sciences - ML in Finance - ML in Science & Engineering - ML Systems - Multi-agent Systems & Game Theory - Natural Language Processing - Optimization & Meta Learning - Privacy - Quantum & Physics-based ML - Reinforcement Learning & Control - Robotics - Robust & Trustworthy ML - Safety - Security, Synthesis & Verification - Symbolic Machine Learning - Unsupervised Learning You can watch our introductory video here: https://www.youtube.com/watch?v=kWXNpnxkfg0. The deadline for applications is November 15, 2022. Interested candidates should apply online through the ELLIS application portal. For details on the program, specific research areas, and the application process, please consult the call for applications: https://ellis.eu/news/ellis-phd-program-call-for-applications-2022.

1 0

PhD studentship in Natural Language Processing at the University of Edinburgh funded by DeepMind
by Mirella Lapata 28 Oct '22

28 Oct '22

The School of Informatics, University of Edinburgh, is thrilled to announce a PhD scholarship funded by DeepMind. The scholarship covers tuition fees (at the Home/International tuition fee rate), provides annual stipend of £17,668 annum (for 4 years full time study) and provides a research training and support grant. The student will be supervised by Dr. Mirella Lapata and will also benefit from mentoring from DeepMind staff during their period of study.  Applicants would be expected to work on an topic drawn from the following research areas: - multimodal natural language understanding and generation - long-form and retrieval-augmented text generation - Multilingual generation Applicants wishing to apply for the scholarship should meet one OR both of the following criteria: - are resident of a country and/or region underrepresented in AI; - identify as women including cis and trans people and non-binary or gender fluid people who identify in a significant way as women or female; - and/or identify as Black or other minority ethnicity; The successful candidate will have a good honours degree or equivalent in artificial intelligence, computer science, machine learning, or a related discipline; or have a breadth of relevant experience in industry/academia/public sector, etc. They will have strong programming skills and previous experience in natural language processing. If you have further questions, please Dr. Mirella Lapata, mlap(a)inf.ed.ac.uk. To apply, please follow the instructions at: http://www.inf.ed.ac.uk/postgraduate/apply.html As your research area, please select "Informatics: ILCC: Language Processing, Speech Technology, Information Retrieval, Cognition". On the application form under "Research Project", please state "DeepMind Scholarship". IMPORTANT: After submitting your application through the website, please email your applicant number to mlap(a)inf.ed.ac.uk. Application deadline: 10th December 2022 [applications received after the deadline may be considered, but this cannot be guaranteed]. -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

1 0

Webminar by Vered Shwartz (The University of British Columbia-Vancouver)
by HiTZ Zentroa 28 Oct '22

28 Oct '22

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*: Vered Shwartz (The University of British Columbia-Vancouver) * *Title*: Incorporating Commonsense Reasoning into NLP Models * *Date*: November 3, 2022, 15:30 CET * *Summary*: NLP models are primarily supervised, and are by design trained on a sample of the situations they may encounter in practice. The ability of models to generalize to and address unknown situations reasonably is limited, but may be improved by endowing models with commonsense knowledge and reasoning skills. In this talk, I will present several lines of work in which commonsense is used for improving the performance of NLP tasks: for completing missing knowledge in underspecified language, interpreting figurative language, and resolving context-sensitive event coreference. Finally, I will discuss open problems and future directions in building NLP models with commonsense reasoning abilities. * *Bio*:Vered Shwartz is an Assistant Professor of Computer Science at the University of British Columbia and a faculty member at the Vector Institute for Artificial Intelligence. Her research interests include commonsense reasoning, computational semantics and pragmatics, and multiword expressions. Previously, Vered was a postdoctoral researcher at the Allen Institute for AI (AI2) and the University of Washington, and received her PhD in Computer Science from Bar-Ilan University. * *Upcoming webinars*: o Machine translation as a tool for multilingual information: different users and use scenarios -- 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

1 0

Job-Research Assistant-Inclusive Language Detection-Galway- Last Date 5.00 pm 28th October 2022
by Bharathi Raja Asoka Chakravarthi 28 Oct '22

28 Oct '22

*Research Assistant* *Natural Language Processing and Linked Data* *School of Computer Science and Data Science Institute* *Ref. No. University of Galway 272-22* Applications are invited from suitably qualified candidates for a full-time, fixed-term position as a Research Assistant with the School of Computer Science and Data Science Institute at the University of Galway. This position is funded by SFI Insight Research Centre for Data Analytics and Fidelity Investments and is available from 1 November 2022 to contract end date of 30 October 2023. The School of Computer Science is ambitious and growing, and we invite the new appointees to contribute to this together with us. The vision of the School of Computer Science is to build a strong and sustainable learning environment with world-recognised research that informs high-quality undergraduate and postgraduate teaching that is inclusive and relevant to the needs of our stakeholders and society in general. The School of Computer Science was initially established in 1991 as the Information Technology Discipline, and became a School in 2019, recognising its growth and significance. DSI incorporates the University of Galway node of the nationwide Insight Centre for Data Analytics. DSI hosts more than 100 staff and has established itself as a top player worldwide in the areas of Semantic Web and Linked Data. It has successfully implemented a research strategy around the goal of “Enabling Networked Knowledge”, which aims at capitalizing on knowledge as the fuel for the digital service economy, by linking information and exploiting the resulting knowledge graphs as the basis for economic productivity. The institute performs fundamental and applied research in a range of research areas to enable this, including data streams and sensor networks, knowledge discovery, natural language processing, social semantics and social network analysis, among others. Research outcomes are applied in use cases across a range of domains, including eGovernment, financial services, manufacturing, eHealth and Life Sciences. School of Computer Science - University of Galway <https://www.universityofgalway.ie/science-engineering/school-of-computer-sc…> *https://www.insight-centre.org/* <https://www.insight-centre.org/> *Job Description:* This research assistant position is in the area of Inclusive language detection, and will focus on the combination of existing natural language processing and linked data technologies. This work will build on the definition of inclusive language provided in the Fidelity report “Inclusion Guide: Language, Accessibility and more”. In addition, we will investigate open benchmarks. The successful candidate supports the activities of the project through provision of research and administrative assistance and will work under the direction of the Project Leaders Dr Bharathi Raja Chakravarthi and Dr. John McCrae. The School of Computer Science and Data Science Institute (DSI) at University of Galway is inviting applications for the position of research assistant for 1 year in the context of the SFI Insight Research Centre for Data Analytics. *Duties:* *Research* - Actively participate as a member of a research team and assist an individual research leader or team to conduct a particular study (or group of studies). - To provide assistance in conducting research activities, including planning, organizing, conducting, and communicating research studies within the overall scope of a research project. - To coordinate and perform a variety of independent tasks and team activities involved in the collection, analysis, documentation and some interpretation of information/results. - Conduct literature and database searches and interpret and present the findings of the literature searches as appropriate. - Assist in analysis and interpretation of results of own research. *Write up & Disseminate* - Write up results from own research activity (e.g. as project report) for review by PI, including preparing technical reports, conclusions and recommendations. - Contribute to the publication of findings. - Provide input into the research project’s dissemination, in whatever form (report, papers, chapters, book) as directed by the PI/project leader. Authorship should be decided in line with guidelines such as the Vancouver Protocol, or similar authorship guidelines as appropriate. - Present on research progress and outcomes e.g. to bodies supervising research; steering groups; other team members, as agreed with the PI/project leader. - Should write at least workshop level papers. *Management* - Work under the direction of the Principal Investigator/Project Leader. Plan and manage own day-to-day research activity within this framework & direction. - Provide guidance as required to any support staff and/or research students assisting with the research project, as agreed with the Principal Investigator/Grant holder. - To perform other related duties incidental to the work described herein. - Where appropriate provide advice and / or assistance to support staff, research students. *Qualifications/Skills required:* *Essential Requirements:* - MSc in Natural Language Processing, Computer Science or Linguistics - Experience with natural language processing, linked data or related technologies - Excellent understanding of experimental design and scientific methodologies - Strong command of oral and written English - Good programming skills and evidence of previously completed software projects *Desirable Requirements:* - Strong knowledge of language technology for equality, diversity, and inclusion - Knowledge of debiasing techniques in NLP task - Knowledge of gender inclusive languages - Programming experience with deep learning in Python - Strong publication record - Track record of contribution to open source projects. *Employment permit restrictions apply for this category of post* *Salary: *€27,380 to €31,050 per annum, per annum pro rata for shorter and/or part-time contracts (public sector pay policy rules pertaining to new entrants will apply *Start date*: Position is available from November 2022 *Continuing Professional Development/Training*: Further information on research and working at University of Galway is available on Research at University of Galway <http://www.nuigalway.ie/our-research/> Researchers at University of Galway are encouraged to avail of a range of training and development opportunities designed to support their personal career development plans. University of Galway provides continuing professional development supports for all researchers seeking to build their own career pathways either within or beyond academia. Researchers are encouraged to engage with our Researcher Development Centre (RDC) upon commencing employment - see https://www.universityofgalway.ie/rdc/ for further information. For information on moving to Ireland please see www.euraxess.ie Further information about the School of Computer Science and Data Science Institute is available at School of Computer Science - University of Galway <https://www.universityofgalway.ie/science-engineering/school-of-computer-sc…> https://www.universityofgalway.ie/dsi/ *NB*: Gárda vetting is a requirement for this post *To Apply:* Applications to include a covering letter, CV, and the contact details of three referees should be sent, via e-mail (in word or PDF only) to Dr. Bharathi Raja Chakravarthi ( bharathiraja.asokachakravarthi(a)universityofgalway.ie) and Dr. John P. McCrae, (john.mccrae(a)universityofgalway.ie) Please put reference number *University of Galway 272-22 *in subject line of e-mail application. *Closing date for receipt of applications is 5.00 pm 28th October 2022* We reserve the right to re-advertise or extend the closing date for this post. University of Galway is an equal opportunities employer. All positions are recruited in line with Open, Transparent, Merit (OTM) and Competency based recruitment with regards, Dr. Bharathi Raja Chakravarthi, Assistant Professor / Lecturer-above-the-bar School of Computer Science, University of Galway, Ireland Insight SFI Research Centre for Data Analytics, Data Science Institute, University of Galway, Ireland E-mail: bharathiraja.akr(a)gmail.com , bharathiraja.asokachakravarthi(a)universityofgalway.ie Google Scholar: https://scholar.google.com/citations?user=irCl028AAAAJ&hl=en

1 0

Clickbait Spoiling at SemEval 2023: Call for Participation
by maik.froebe＠uni-jena.de 28 Oct '22

28 Oct '22

We invite you to participate in the SemEval 2023 shared task on clickbait spoiling. Clickbait spoiling means generating or extracting a short message for a clickbait post that spoils the clickbait by filling its curiosity gap. Learn more at https://clickbait.webis.de/ ------------------------------------------------------------------------------- Important Dates ------------------------------------------------------------------------------- Now open: Registration January 10, 2023: Submission deadline February 2023: Participant paper submission March 2023: Peer review notification April 2023: Camera-ready participant papers submission Summer 2023: SemEval workshop (co-located with a major NLP conference) Best regards, PAN team

1 0

Prof / Ass Prof in Computer Science, Leeds-SWJTU Joint School, Chengdu China
by Eric Atwell 28 Oct '22

28 Oct '22

An interesting promotion opportunity to teach our Leeds CS curriculum in English to top Chinese students in the Leeds-SWJTU Joint School, Chengdu, China https://www.timeshighereducation.com/unijobs/listing/314259/tenure-track-pr…<https://www.timeshighereducation.com/unijobs/listing/314259/tenure-track-pr…> "... to deliver courses in English, supervise Joint School students in research projects, contribute to various services at SWJTU-Leeds Joint School, and conduct academic research in teams at corresponding parent school ..."

1 0

First CfP: KONVENS 2023 Ingolstadt, Germany
by Friedrich Annemarie (CR/AIR3 GS/PJ-TOP98) 27 Oct '22

27 Oct '22

Call for Papers: KONVENS 2023, Ingolstadt, Germany We cordially invite submissions of papers and abstracts to KONVENS 2023, which takes place from September 18-22, 2023 at the Technische Hochschule Ingolstadt (Bavaria, Germany). Next to its technical program, KONVENS will feature a lively exchange between academic researchers and colleagues from industry, as well as workshops, tutorials, shared tasks, and networking events. SPECIAL THEME Natural language processing (NLP) technology is already part of our everyday life. We hence particularly invite contributions discussing the interaction of language technology and its users, including the application of speech and text technology in various settings (e.g., dialogue processing, mobility, medicine, e-commerce, or digital humanities). We encourage authors to discuss ethical aspects. We invite two types of submissions: 1. long and short papers that will be archived in the ACL Anthology, and 2. abstracts on ongoing work, student/PhD theses, etc., which will not be archived. PAPER SUBMISSION INFORMATION We welcome original, unpublished contributions on research, development, applications and evaluation, covering all areas of natural language processing, ranging from basic questions to practical implementations of natural language resources, components and systems. We encourage the submission of NLP approaches to the German language, and survey papers describing the state of the art in German language and speech processing. We invite contributions from both academia and industry. We welcome the following types of paper submissions: · Long papers (8 pages plus references and appendix), describing original research with substantial new results. · Short papers (4 pages plus references and appendix), including small focused contributions, work in progress, as well as descriptions of projects, systems and resources. Accepted papers will be presented orally or as posters as determined by the program chairs. The decisions will be based on the nature rather than the quality of the work. The conference languages are English and German. We encourage the submission of contributions in English. Each submission must include a mandatory discussion of Ethical Considerations as well as a section on Limitations (both sections do not count towards the page limit). Papers without these sections will be desk-rejected. The review process will be double-blind. Submissions must be anonymized accordingly. The conference proceedings will be published in the ACL Anthology. ABSTRACT SUBMISSION INFORMATION To foster interaction and discussion in our community, we also invite abstracts (max. 2 pages plus references) on the following topics: * Ongoing projects, open source toolkits and software, repositories, etc. * Bachelor or Master theses, student projects * PhD theses (ongoing or finished) * Use of NLP technology within industrial products * Opinion pieces Abstracts should not be anonymized. They will be made available to conference participants, but they will not be archived. Accepted abstracts will be presented as posters at the conference. We explicitly invite students and doctoral researchers to join the event and present their work and obtain feedback in our student poster session by submitting an abstract. IMPORTANT DATES * May 19th, 2023: Paper submission due (all submission types) * June 30th, 2023: Notification of acceptance * July 15th, 2023: Camera-ready papers due * September 18-22 2023: KONVENS INSTRUCTIONS FOR AUTHORS Papers and abstracts must be formatted in accordance with the ACL style sheets<https://github.com/acl-org/acl-style-files>. We strongly encourage authors to use LaTeX in preparing their document. Information on the submission procedure will follow shortly. On Behalf of the Organization Committee Munir Georges, TH Ingolstadt Annemarie Friedrich, Bosch Center for Artificial Intelligence, Renningen Aaricia Herygers, TH Ingolstadt ========================================================================================= Mit freundlichen Grüßen / Best regards Dr. Annemarie Friedrich Natural Language Processing and Semantic Reasoning (CR/PJ-AI-R26) Robert Bosch GmbH | Postfach 10 60 50 | 70049 Stuttgart | GERMANY | www.bosch.com Tel. +49 711 811-49626 | Mobil +49 172 3008243 | Annemarie.Friedrich(a)de.bosch.com<mailto:Annemarie.Friedrich@de.bosch.com> Sitz: Stuttgart, Registergericht: Amtsgericht Stuttgart, HRB 14000; Aufsichtsratsvorsitzender: Prof. Dr. Stefan Asenkerschbaumer; Geschäftsführung: Dr. Stefan Hartung, Dr. Christian Fischer, Filiz Albrecht, Dr. Markus Forschner, Dr. Markus Heyn, Rolf Najork

1 0

2025

2024

2023

2022

Corpora