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PhD Scholorship in e-Health and/or Sign Language Translation] @ Queen's University Belfast, UK
by Mohammed Hasanuzzaman 21 Jan '24

21 Jan '24

*Apologies for the multiple postings* I am looking for a PhD student in e-Health and/or Sign Language Translation at the School of School of Electronics, Electrical Engineering and Computer Science, Queen's University in Belfast, UK. The details of the project can be found below: https://www.qub.ac.uk/courses/postgraduate-research/phd-opportunities/causa… https://www.qub.ac.uk/courses/postgraduate-research/phd-opportunities/endto… Requirements: The successful candidate is expected to have a solid background in Machine Learning, Statistics, computer science or related discipline. The minimum academic requirement for admission to a research degree programme is normally an Upper Second Class Honours degree from a UK or ROI HE provider, or an equivalent qualification acceptable to the University. Refer to the official application process for details. Application Process: For enquiries, please send an email to Dr. Mohammed Hasanuzzaman at m.hasanuzzaman(a)qub.ac.uk with your CV and transcript as well as a brief description of your research interests. Unfortunately, due to a high volume of inquiries, I may not be able to respond to all emails. Submit your formal application through the following link. https://dap.qub.ac.uk/portal/user/u_login.php Your application should be clearly marked as EEECS/2024/MH1 and/or EEECS/2024/MH2 to ensure consideration for funding Application Deadline: 29 February, 2024 About Queen's: The Queen's University Belfast, founded almost two centuries ago, is one of the oldest universities in the United Kingdom. As a member of the prestigious Russell Group, Queen’s is one of the UK’s 24 leading research-intensive universities (ranked 13th in the UK for research intensity). Queen's has 15 subjects in the top 200 in the world (QS World University Rankings 2023). Five of those subjects are in the World Top 100 (QS World Rankings by subject 2023). For more details: https://www.qub.ac.uk/Study/Why-Study-at-Queens/rankings-and-reputation/ *International students are welcome to apply, but additional funding ( https://www.qub.ac.uk/Study/international-students/international-scholarshi…) or personal finances will be required to cover the difference between home (UK) and overseas fees. Best regards, Mohammed ------------------------------------------------------------------------------------------------------ *Dr. Mohammed HasanuzzamanLecturer/Assistant Professor**Queen's University Belfast <https://www.qub.ac.uk/>, UK * *&Munster Technological University <https://www.mtu.ie/>, Ireland* *Funded Investigator, ADAPT Centre- <https://www.adaptcentre.ie/> A <https://www.adaptcentre.ie/>* World-Leading SFI Research Centre <https://www.adaptcentre.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**Website: **https://mohammedhasanuzzaman.github.io/ <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…> 21/01/24, 13:19:43

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ReproNLP 2024 - First Call for Participation - Shared Task on Reproducibility of Evaluations in NLP
by Thomson, Craig 21 Jan '24

21 Jan '24

ReproNLP 2024 First Call for Participation Background Across Natural Language Processing (NLP), a growing body of work is exploring the issue of reproducibility in machine learning contexts. The field is currently far from having a generally agreed toolbox of methods for defining and assessing reproducibility. Reproducibility of results of human evaluation experiments is particularly under-addressed which is of concern for areas of NLP where human evaluation is common including e.g. MT, text generation, and summarisation. More generally, human evaluations provide the benchmarks against which automatic evaluation methods are assessed across NLP. We previously organised the First ReproGen Shared Task on reproducibility of human evaluations in NLG as part of Generation Challenges (GenChal) at INLG’21, and the Second ReproGen Shared Task at INLG’22, where we extended the scope to encompass automatic evaluation methods as well as human. Last year we expanded the scope of the shared task series to encompass all NLP tasks, renaming it the ReproNLP Shared Task on Reproducibility of Evaluations in NLP (part of the HumEval workshop at RANLP’23). This year we are focussing on human evaluations, and the results session will be held at the 4th Workshop on Human Evaluation of NLP Systems (HumEval’24 at LREC-COLING’24). As with the previous shared tasks, our overall aim is (i) to shed light on the extent to which past NLP evaluations have been reproducible, and (ii) to draw conclusions regarding how NLP evaluations can be designed and reported to increase reproducibility. With this task being run over several years, we hope to be able to document an overall increase in levels of reproducibility over time. About ReproNLP ReproNLP has two tracks, one an ‘unshared task’ in which teams attempt to reproduce any prior evaluation results (Track A below), the other a standard shared task in which teams repeat existing evaluation studies with the aim of reproducing their results (Track B): A. Open Track: Reproduce previous evaluation results from any paper, and report what happened. Unshared task. B. ReproHum Track (papers see below): For a shared set of selected evaluation studies from the ReproHum Project, participants repeat one or more of the studies and attempt to reproduce their results, using the information provided by the ReproNLP organisers only, and following a common reproduction approach. Track B Papers The specific experiments listed and described below are currently the subject of reproduction studies in the ReproHum<https://reprohum.github.io/> project. The authors have provided very detailed information about the experiments. In some cases, we have introduced standardisations to the experimental design as noted in the detailed instructions to participants which will be shared upon registration. The papers and studies, with many thanks to the authors for supporting ReproHum and ReproNLP, are: Reif et al. (2022): A Recipe for Arbitrary Text Style Transfer with Large Language Models: https://aclanthology.org/2022.acl-short.94 * Absolute evaluation study; English; 3 quality criteria; 3 datasets; varies between 4 and 6 systems and between 200 and 300 evaluation items per dataset-criterion combination; crowdsourced. Vamvas & Sennrich (2022): As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning: https://aclanthology.org/2022.acl-short.53 * Absolute evaluation study; ZH to EN, EN to DE; 1 quality criterion; 1 dataset; 1 system and 757 evaluation items. Bai et al. (2021): Cross-Lingual Abstractive Summarization with Limited Parallel Resources: https://aclanthology.org/2021.acl-long.538 * Relative evaluation study; ZH to EN; 3 quality criteria; 1 dataset; 4 systems and 240 evaluation items per criterion. Puduppully & Lapata (2021): Data-to-text Generation with Macro Planning: https://aclanthology.org/2021.tacl-1.31/ * Absolute evaluation study; English; 2 quality criteria; 2 datasets; 5 systems and 400 evaluation items per dataset-criterion combination; crowdsourced. * Relative evaluation study; English; 3 quality criteria; 2 datasets; 5 systems and 200 evaluation items per dataset-criterion combination; crowdsourced. Liu et al. (2021): DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts: https://aclanthology.org/2021.acl-long.522 * Relative evaluation study; English; 3 quality criteria; 2 datasets; varies between 5 and 6 systems and between 960 and 1200 evaluation items per dataset-criterion combination; crowdsourced. Dwiastuti (2019): English-Indonesian Neural Machine Translation for Spoken Language Domains: https://aclanthology.org/P19-2043 * Relative evaluation study; Indonesian; 1 quality criterion; 1 dataset; 2 systems and 50 evaluation items. Hosking & Lapata (2021): Factorising Meaning and Form for Intent-Preserving Paraphrasing: https://aclanthology.org/2021.acl-long.112 * Relative evaluation study; English; 3 quality criteria; 1 dataset; 4 systems and 1200 evaluation items per criterion; crowdsourced. Atanasova et al. (2020): Generating Fact Checking Explanations: https://aclanthology.org/2020.acl-main.656 * Absolute evaluation study; English; 1 quality criterion; 1 dataset; 3 systems and 240 evaluation items. * Relative evaluation study; English; 4 quality criteria; 1 dataset; 3 systems and 40 evaluation items per criterion. August et al. (2022): Generating Scientific Definitions with Controllable Complexity: https://aclanthology.org/2022.acl-long.569 * Absolute evaluation study; English; 5 quality criteria; 2 datasets; 3 systems and 300 evaluation items per dataset-criterion combination; some crowdsourced. Hosking et al. (2022): Hierarchical Sketch Induction for Paraphrase Generation: https://aclanthology.org/2022.acl-long.178 * Relative evaluation study; English; 3 quality criteria; 1 dataset; 4 systems and 1800 evaluation items per criterion; crowdsourced. Yao et al. (2022): It is AI’s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children’s Story Books: https://aclanthology.org/2022.acl-long.54 * Absolute evaluation study; English; 3 quality criteria; 1 dataset; 3 systems and 361 evaluation items per criterion. Chakrabarty et al. (2022): It’s not Rocket Science: Interpreting Figurative Language in Narratives: https://aclanthology.org/2022.tacl-1.34/ * Absolute evaluation study; English; 1 quality criterion; 2 datasets; varies between 6 and 8 systems and between 150 and 200 evaluation items per dataset; crowdsourced. * Relative evaluation study; English; 1 quality criterion; 2 datasets; 3 systems and varies between 225 and 300 evaluation items per dataset; crowdsourced. Feng et al. (2021): Language Model as an Annotator: Exploring DialoGPT for Dialogue Summarization: https://aclanthology.org/2021.acl-long.117 * Absolute evaluation study; English; 3 quality criteria; 2 datasets; 7 systems and varies between 70 and 700 evaluation items per dataset-criterion combination. Lux & Vu (2022): Language-Agnostic Meta-Learning for Low-Resource Text-to-Speech with Articulatory Features: https://aclanthology.org/2022.acl-long.472 * Relative evaluation study; German; 1 quality criterion; 1 dataset; 2 systems and 12 evaluation items. Gu et al. (2022): MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes: https://aclanthology.org/2022.acl-long.450 * Relative evaluation study; English; 3 quality criteria; 1 dataset; 2 systems and varies between 63 and 67 evaluation items per criterion. Gabriel et al. (2022): Misinfo Reaction Frames: Reasoning about Readers’ Reactions to News Headlines: https://aclanthology.org/2022.acl-long.222 * Absolute evaluation study; English; 3 quality criteria; 1 dataset; 3 systems and 588 evaluation items per criterion; crowdsourced. Kasner & Dusek (2022): Neural Pipeline for Zero-Shot Data-to-Text Generation: https://aclanthology.org/2022.acl-long.271 * Absolute evaluation study; English; 5 quality criteria; 2 datasets; 6 systems and 600 evaluation items per dataset-criterion combination. Shardlow & Nawaz (2019): Neural Text Simplification of Clinical Letters with a Domain Specific Phrase Table: https://aclanthology.org/P19-1037 * Relative evaluation study; English; 1 quality criterion; 1 dataset; 4 systems and 100 evaluation items; crowdsourced. Castro Ferreira et al. (2018): NeuralREG: An end-to-end approach to referring expression generation: https://aclanthology.org/P18-1182 * Absolute evaluation study; English; 3 quality criteria; 1 dataset; 6 systems and 144 evaluation items per criterion; crowdsourced. Same et al. (2022): Non-neural Models Matter: a Re-evaluation of Neural Referring Expression Generation Systems: https://aclanthology.org/2022.acl-long.380 * Absolute evaluation study; English; 3 quality criteria; 2 datasets; varies between 6 and 8 systems and between 180 and 384 evaluation items per dataset-criterion combination; crowdsourced. Lin et al. (2022): Other Roles Matter! Enhancing Role-Oriented Dialogue Summarization via Role Interactions: https://aclanthology.org/2022.acl-long.182 * Absolute evaluation study; Chinese; 3 quality criteria; 1 dataset; 4 systems and 800 evaluation items per criterion. Track A and B Instructions Step 1. Fill in the registration form<https://docs.google.com/forms/d/e/1FAIpQLSetAzVp3BVkTaf8i0MZuya_sAKuP3ii6zC…>, indicating which of the above papers, or which other paper(s), you wish to carry out a reproduction study for. Step 2. After registration, the ReproNLP participants information will be made available to you, plus data, tools and other materials for each of the studies you have selected in the registration form. Step 3. Carry out the reproduction, and submit a report of up to 8 pages plus references and supplementary material including a completed ReproGen Human Evaluation Sheet (HEDS) for each reproduction study, by April 1st 2024. Step 4. The organisers will carry out light touch review of the evaluation reports according to the following criteria: * Evaluation sheet has been completed. * Exact repetition of study has been attempted and is described in the report. * Report gives full details of the reproduction study, in accordance with the reporting guidelines provided. * All tools and resources used in the study are publicly available. Step 5. Present paper at the results meeting. Reports will be included in the HumEval’24 proceedings, and results will be presented at the workshop in May 2024. Full details and instructions will be provided as part of the ReproNLP participants information. Important Dates Report submission deadline: 1st of April 2024 Acceptance notification: 9th of April 2024 Camera-ready reports due: 19th of April 2024 Presentation of results: 21st of May 2024 All deadlines are 23:59 UTC-12. Organisers Anya Belz, ADAPT/DCU, Ireland Craig Thomson, University of Aberdeen, UK Ehud Reiter, University of Aberdeen, UK Contact anya.belz(a)adaptcentre.ie, c.thomson(a)abdn.ac.uk https://repronlp.github.io The University of Aberdeen is a charity registered in Scotland, No SC013683. Tha Oilthigh Obar Dheathain na charthannas clàraichte ann an Alba, Àir. SC013683.

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Call for Papers: 9th Symposium on Corpus Approaches to Lexicogrammar (LxGr2024)
by Costas Gabrielatos 19 Jan '24

19 Jan '24

9th Symposium on Corpus Approaches to Lexicogrammar (LxGr2024) CALL FOR PAPERS Deadline for abstract submission: Friday 15 March 2024 The symposium will take place online on Friday 5 and Saturday 6 July 2024. Invited Speakers Lise Fontaine<http://www.uqtr.ca/PagePerso/Lise.Fontaine> (Université du Québec à Trois-Rivières): Reconciling (or not) lexis and grammar Ute Römer-Barron<http://alsl.gsu.edu/profile/ute-romer> (Georgia State University): Phraseology research in second language acquisition LxGr primarily welcomes papers reporting on corpus-based research on any aspect of the interaction of lexis and grammar - particularly studies that interrogate the system lexicogrammatically to get lexicogrammatical answers. However, position papers discussing theoretical or methodological issues are also welcome, as long as they are relevant to both lexicogrammar and corpus linguistics. If you would like to present, send an abstract of 500 words (excluding references) to lxgr(a)edgehill.ac.uk<mailto:lxgr@edgehill.ac.uk>. Make sure that the abstract clearly specifies the research focus (research questions or hypotheses), the corpus, the methodology (techniques and metrics), the theoretical orientation, and the main findings. Abstracts will be double-blind reviewed, and decisions will be communicated within four weeks. Full papers will be allocated 35 minutes (including 10 minutes for discussion). Work-in-progress reports will be allocated 20 minutes (including 5 minutes for discussion). There will be no parallel sessions. Participation is free. For details, visit the LxGr website: https://sites.edgehill.ac.uk/lxgr/lxgr2024 If you have any questions, contact lxgr(a)edgehill.ac.uk<mailto:lxgr@edgehill.ac.uk>. ________________________________ Edge Hill University<http://ehu.ac.uk/home/emailfooter> Modern University of the Year, The Times and Sunday Times Good University Guide 2022<http://ehu.ac.uk/tef/emailfooter> University of the Year, Educate North 2021/21 ________________________________ This message is private and confidential. If you have received this message in error, please notify the sender and remove it from your system. Any views or opinions presented are solely those of the author and do not necessarily represent those of Edge Hill or associated companies. Edge Hill University may monitor email traffic data and also the content of email for the purposes of security and business communications during staff absence.<http://ehu.ac.uk/itspolicies/emailfooter>

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[CFP] NLDB 2024 - The 29th International Conference on Natural Language & Information Systems
by Federico Torrielli 19 Jan '24

19 Jan '24

* We apologize if you receive multiple copies of this CFP * For the online version of this Call, visit: https://nldb2024.di.unito.it/submissions/ =============== NLDB 2024 The 29th International Conference on Natural Language & Information Systems 25-27 June 2024, University of Turin, Italy. Website: https://nldb2024.di.unito.it/ Submission deadline: 22 March, 2024 About NLDB The 29th International Conference on Natural Language & Information Systems will be held at the University of Turin, Italy, and will be a face to face event. Since 1995, the NLDB conference brings together researchers, industry practitioners, and potential users interested in various applications of Natural Language in the Database and Information Systems field. The term "Information Systems" has to be considered in the broader sense of Information and Communication Systems, including Big Data, Linked Data and Social Networks. The field of Natural Language Processing (NLP) has itself recently experienced several exciting developments. In research, these developments have been reflected in the emergence of Large Language Modelsand the importance of aspects such as transparency, bias and fairness, Large Multimodal Models and the connection of the NLP field with Computer Vision, chatbots and dialogue-based pipelines. Regarding applications, NLP systems have evolved to the point that they now offer real-life, tangible benefits to enterprises. Many of these NLP systems are now considered a de-facto offering in business intelligence suites, such as algorithms for recommender systems and opinion mining/sentiment analysis. Language models developed by the open-source community have become widespread and commonly used. Businesses are now readily adopting these technologies, thanks to the efforts of the open-source community. For example, fine-tuning a language model on a company’s own dataset is now easy and convenient, using modules created by thousands of academic researchers and industry experts. It is against this backdrop of recent innovations in NLP and its applications in information systems that the 29th edition of the NLDB conference takes place. We welcome research and industrial contributions, describing novel, previously unpublished works on NLP and its applications across a plethora of topics as described in the Call for Papers. Call for Papers: NLDB 2024 invites authors to submit papers on unpublished research that addresses theoretical aspects, algorithms, applications, architectures for applied and integrated NLP, resources for applied NLP, and other aspects of NLP, as well as survey and discussion papers. This year's edition of NLDB continues with the Industry Track to foster fruitful interaction between the industry and the research community. Topics of interest include but are not limited to: * Large Language Models: training, applications, transfer learning, interpretability of large language models. * Multimodal Models: Integration of text with other modalities like images, video, and audio; multimodal representation learning; applications of multimodal models. * AI Safety and ethics: Safe and ethical use of Generative AI and NLP; avoiding and mitigating biases in NLP models and systems; explainability and transparency in AI. * Natural Language Interfaces and Interaction: design and implementation of Natural Language Interfaces, user studies with human participants on Conversational User Interfaces, chatbots and LLM-based chatbots and their interaction with users. * Social Media and Web Analytics: Opinion mining/sentiment analysis, irony/sarcasm detection; detection of fake reviews and deceptive language; detection of harmful information: fake news and hate speech; sexism and misogyny; detection of mental health disorders; identification of stereotypes and social biases; robust NLP methods for sparse, ill-formed texts; recommendation systems. * Deep Learning and eXplainable Artificial Intelligence (XAI): Deep learning architectures, word embeddings, transparency, interpretability, fairness, debiasing, ethics. * Argumentation Mining and Applications: Automatic detection of argumentation components and relationships; creation of resource (e.g. annotated corpora, treebanks and parsers); Integration of NLP techniques with formal, abstract argumentation structures; Argumentation Mining from legal texts and scientific articles. * Question Answering (QA): Natural language interfaces to databases, QA using web data, multi-lingual QA, non-factoid QA(how/why/opinion questions, lists), geographical QA, QA corpora and training sets, QA over linked data (QALD). * Corpus Analysis: multi-lingual, multi-cultural and multi-modal corpora; machine translation, text analysis, text classification and clustering; language identification; plagiarism detection; information extraction: named entity, extraction of events, terms and semantic relationships. * Semantic Web, Open Linked Data, and Ontologies: Ontology learning and alignment, ontology population, ontology evaluation, querying ontologies and linked data, semantic tagging and classification, ontology-driven NLP, ontology-driven systems integration. * Natural Language in Conceptual Modelling: Analysis of natural language descriptions, NLP in requirement engineering, terminological ontologies, consistency checking, metadata creation and harvesting. * Natural Language and Ubiquitous Computing: Pervasive computing, embedded, robotic and mobile applications; conversational agents; NLP techniques for Internet of Things (IoT); NLP techniques for ambient intelligence * Big Data and Business Intelligence: Identity detection, semantic data cleaning, summarisation, reporting, and data to text. Important Dates: Full paper submission: 22 March, 2024 Paper notification: 19 April, 2024 Camera-ready deadline: 26 April, 2024 Conference: 25-27 June 2024 Submission Guidelines: Authors should follow the LNCS format (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu… ) and submit their manuscripts in pdf via Easychair (submission will open on 1 February, 2024) Papers can be submitted to either the main conference or the industry track. Submissions can be full papers (up to 15 pages including references and appendices), short papers (up to 11 pages including references and appendices) or papers for a poster presentation or system demonstration (6 pages including references). The programme committee may decide to accept some full papers as short papers or poster papers. All questions about submissions should be emailed to federico.torrielli(a)unito.it (Web & Publicity Chair) General Chairs: Luigi Di Caro, University of Turin Farid Meziane, University of Derby Amon Rapp, University of Turin Vijayan Sugumaran, Oakland University

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Invito: UCREL seminar: Wednesday 24th @ 13:00 - Ar... - ven 19 gen 2024 3:30PM - 4:30PM (CET) (corpora@list.elra.info)
by Marica Belmonte 19 Jan '24

19 Jan '24

[Corpora-List] UCREL seminar: Wednesday 24th @ 13:00 - Are rule-based approaches a thing of the past? The case of anaphora resolution. venerdì 19 gen 2024 ⋅ 3:30PM – 4:30PM Ora dell’Europa centrale - Amsterdam Partecipa con Google Meet https://meet.google.com/eft-bkah-zuc?hs=224 At the UCREL / NLP group (https://ucrel.lancs.ac.uk/) we’re excited to have Prof. Ruslan Mitkov with us on Wednesday 24th January 13:00 – 14:00 (UTC/GMT) in our next UCREL corpus research seminar which you can join online via the Teams link below. Ruslan will present an extended version of his recent talk from ICON2023: Are rule-based approaches a thing of the past? The case of anaphora resolution. Ruslan Mitkov https://wp.lancs.ac.uk/mitkov/ Abstract: In this talk I shall present the results of a study which evaluates and compares new variants of a popular rule-based anaphora resolution algorithm (Mitkov 1998, 2002) with the original version. We seek to establish whether configurations that benefit from Deep Learning, LLMs and eye-tracking data (always) outperform the original... Organizzatore Marica Belmonte marica.belmonte(a)gmail.com Invitati Marica Belmonte - organizzatore corpora(a)list.elra.info Visualizza le informazioni di tutti gli invitati https://calendar.google.com/calendar/event?action=VIEW&eid=NTRjc2I1MDJrMXZy… Rispondi per corpora(a)list.elra.info e visualizza ulteriori dettagli https://calendar.google.com/calendar/event?action=VIEW&eid=NTRjc2I1MDJrMXZy… La tua presenza è facoltativa. ~~//~~ Invito da Google Calendar: https://calendar.google.com/calendar/ Hai ricevuto questa email perché partecipi all'evento. Per disattivare la ricezione di aggiornamenti futuri per questo evento, rifiuta l'evento. Se inoltri questo invito potresti consentire al destinatario di inviare una risposta all'organizzatore, di essere aggiunto all'elenco degli invitati oppure di invitare altre persone indipendentemente dallo stato dell'invito o ancora di modificare la tua risposta. Scopri di più https://support.google.com/calendar/answer/37135#forwarding

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UCREL seminar: Wednesday 24th @ 13:00 - Are rule-based approaches a thing of the past? The case of anaphora resolution.
by Rayson, Paul 19 Jan '24

19 Jan '24

At the UCREL / NLP group (https://ucrel.lancs.ac.uk/) we’re excited to have Prof. Ruslan Mitkov<https://wp.lancs.ac.uk/mitkov/> with us on Wednesday 24th January 13:00 – 14:00 (UTC/GMT) in our next UCREL corpus research seminar which you can join online via the Teams link below. Ruslan will present an extended version of his recent talk from ICON2023: Are rule-based approaches a thing of the past? The case of anaphora resolution. Ruslan Mitkov https://wp.lancs.ac.uk/mitkov/ Abstract: In this talk I shall present the results of a study which evaluates and compares new variants of a popular rule-based anaphora resolution algorithm (Mitkov 1998, 2002) with the original version. We seek to establish whether configurations that benefit from Deep Learning, LLMs and eye-tracking data (always) outperform the original rule-based algorithm. The results of this study suggest that while algorithms based in Deep Learning and LLMs usually perform better than rule-based ones, this is not always the case, and we argue that rule-based approaches still have a place in today’s research. Join us online via this link, no registration required: https://teams.microsoft.com/l/meetup-join/19%3ameeting_YzU5MGFmM2MtMzlkMi00… -- Paul Rayson Director of UCREL and Professor of Natural Language Processing SCC Data Theme Lead School of Computing and Communications, InfoLab21, Lancaster University, Lancaster, LA1 4WA, UK. Web: https://www.research.lancs.ac.uk/portal/en/people/Paul-Rayson/ Tel: +44 1524 510357 Contact me on Teams<https://teams.microsoft.com/l/chat/0/0?users=p.rayson@lancaster.ac.uk>

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Call for Papers and Shared Task Proposals: TRAC 2024 @ COLING 2024
by Ritesh Kumar 19 Jan '24

19 Jan '24

Fourth Workshop on Threat, Aggression and Cyberbullying May 20, 2024 Lingotto Conference Centre - Torino (Italia) @ LREC-COLING 2024 *Website:* https://sites.google.com/view/trac2024 *Submission Link:* https://softconf.com/lrec-coling2024/trac2024/ ==================================== Call for Papers and Shared Task Proposals =================================== We are happy to announce that the Fourth Workshop on Threat, Aggression and Cyberbullying will be co-located with LREC-COLING 2024 on May 20, 2024. We invite papers/proposals under the following categories on any of the following themes from academic researchers, industry and any other group/team working in the area- - Long papers describing a substantial, completed original research (8 pages + unlimited reference) - Short papers describing a small but interesting research (4 pages + unlimited references) - Position papers and opinion pieces (5 - 20 pages + unlimited references) - Demo of the tools (2 pages + unlimited references) - Non-archival submissions (including already-presented work, project plans or recently started projects) - Proposal to organise a shared task as part of the workshop (the shared task will be completely managed and organised by the task organisers). Linguistic Theories, Analysis and Models ================================= Theories and models of aggression and conflict in language. Grammar of hate, impoliteness and aggression incl phonological and morphosyntactic properties Pragmatic and Discourse Analysis of impolite, aggressive and hateful language Sociolinguistic analysis of impolite, aggressive and hateful language Corpus-based analysis of impolite, aggressive and hateful language Cognitive and Psycholinguistic Studies of hate and aggression. Online Aggression and Physical Harm Cyberbullying, threatening, hateful, aggressive and abusive language on the web. Multilingualism and aggression. Multimodality and aggression Resource Development and Computational Modelling =========================================== Resource Development - Corpora, Annotation Guidelines, Standards and Best Practices for threat and aggression detection. Detection of threats and bullying on the web - data collection methodologies and approaches. Crowdsourcing and resource development for threatening, aggressive and hateful language. Replicability and Reproducibility of resources for aggression, hate speech and offensive language detection. Inter-annotator agreement, Perspectivist Datasets and Issues with traditional methods of annotation. Annotation Tools and Infrastructure for working on threatening, aggressive and hateful language. Computational Models and Methods for aggression, hate speech and offensive language detection in text and speech. Aggressive and Offensive Language Detection in and through Large Language Models (LLMs). Methods of building diverse, multilingual and multimodal resources and models with a focus on under-resourced languages. Evaluating and benchmarking resources and models for aggression, hate speech and offensive language detection Automatic censorship and moderation: ethical, legal and technological issues and challenges. Important Dates ============== For workshop papers Submission Deadline: February 25, 2024 Notification of acceptance: April 5, 2024 Camera-ready due: April 15, 2024 All deadlines are Anywhere on Earth For Shared Tasks Proposals Due: January 29, 2024 Notification of acceptance: February 5, 2024 Training Set Release: February 7, 2024 Test Set Release: March 10, 2024 Submission due: March 13, 2024 System Description Papers due: March 31, 2024 Reviews for papers: April 7, 2024 Camera-ready due: April 15, 2024

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Invitation for Bids to Host the Global Wordnet Conference 2025
by Begoña ALTUNA 19 Jan '24

19 Jan '24

== Apologies for cross-posting == The Global Wordnet Association welcomes bids from potential organizers of the 13th Global Wordnet Conference in January 2025. The deadline for submitting a proposal is March 31th, 2024. Bids will be considered by the GWA Board and a decision will be announced April 30th, 2022. Proposals must consider and, where appropriate, address the following criteria: * Expected size: 50-100 people * Logistics – Convenient and reasonably priced international flight connections – Inexpensive lodging for participants on small budgets * Date – Projected date: January 2025 – Conference length of 4 days * Participants/Content – We encourage efforts to expand participation beyond the current wordnet community – We encourage co-located tutorials, workshops, panels, hackathons, shared tasks and other events * Proceedings – Local organizers are the main editors of the proceedings – Proceedings must get an ISBN number and must be freely downloadable from the GWA website – Proceedings should be registered in the ACL Anthology (the GWA board will help with this). * Budget and Fees (this is a model; variations can be proposed and discussed) – Fee structure: – Aim to keep to 200 EUROs maximum for regular participants – Reduced fee for students and participants from countries with little funding – Fees include GWA membership to be transferred to GWA (see below)– Participants fees also cover: – proceedings (electronic & ISBN) – coffee breaks – lunches (depending on local costs), – Fees do not necessarily cover: – accommodation – dinners – local transport from hotel pick-up points to conference – Optional additional fee to cover: – banquet – excursion * Costs to be borne by the local organizer: – meeting rooms and equipment rental – local support staff * Sponsorship: the organizer is encouraged to find sponsors – Invited speaker(s) from the international community, to be selected by the organizers in consultation with the GWA board. * Board and the local organizers: – Number of speakers determined by the availability of financial support. – Local organizers may additionally invite and sponsor one or more local speakers, in consultation with the GWA Board. * Financial responsibility: – The GWA cannot contribute financially or assume any financial responsibility – Financial responsibility rests entirely with the local organizer – Early registration to reduce risk is encouraged – Enforce policy of inclusion of papers in proceedings after early registration of at least one author * Program committee: – GWA Board – Chairs: German Rigau and Francis Bond – The reviewing will include a best paper award – Program Committee to be composed before Call for Papers Please send your bids to German Rigau <german.rigau(a)ehu.eus> and Francis Bond <bond(a)ieee.org<mailto:bond@ieee.org>>

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[PhD-Position] Muiltimodal Fake-News and Disinformation Detection incl. xAI in DFKI Berlin - final reminder
by Tim Polzehl 19 Jan '24

19 Jan '24

Job offer: Researcher for Multimodal Fake-News and Disinformation Detection at DFKI Berlin Final reminder: Application deadline: Jan 23, 2024. The German Research Center for Artificial Intelligence (DFKI) has operated as a non-profit, Public-Private-Partnership (PPP) since 1988. DFKI combines scientific excellence and commercially-oriented value creation with social awareness and is recognized as a major "Center of Excellence" by the international scientific community. In the field of artificial intelligence, DFKI as Germany’s biggest public and independent organisation dedicated to AI research and development, has focused on the goal of human-centric AI for more than 30 years. Research is committed to essential, future-oriented areas of application and socially relevant topics. We are looking for a highly motivated research assistant to join our existing team and work on a project focused on fake-news and disinformation detection from speech and multimedia data. Content authenticity verification of speech combined with other modalities like text, visuals or meta-data will be a center part. In any case, xAI and bias analysis are aspects of high relevance to the position as well. The successful candidate will work closely with high-impact partners in this field, e.g. Technical University of Berlin, RBB (Berlin TV and news broadcaster), Deutsche Welle (Germany's broadcaster abroad), and 5 other partners. Responsibilities will include developing and testing different AI/NLP models and techniques, analyzing the performance of machine learning models in the context of applicable fake-news and disinformation fighting for journalists, and communicating project progress and results to relevant stakeholders. The position offers opportunities for pursuing a doctorate and publishing research results in scientific journals and conferences. Qualified candidates will have a completed university degree in (technical) computer science or computational linguistics, excellent programming skills in Python, and a strong background in machine learning/AI and signal processing or NLP. Previous experience in the field of fake-news or spoofing / authenticity detection of multimedia data is an advantage. DFKI offers an agile and lively international and interdisciplinary environment for working in a self-determined manner. If you are interested in contributing to cutting-edge research and working with a dynamic team, please apply! More details and link: https://jobs.dfki.de/en/vacancy/researcher-m-f-d-547585.html Application deadline: Jan 23, 2024. In terms of questions please don’t hesitate to contact tim.polzehl(a)dfki.de -- Dr.-Ing. Tim Polzehl Senior Researcher Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) German Research Center for Artificial Intelligence Speech & Language Technology Associate Senior Researcher Technische Universität Berlin Quality and Usability Lab DFKI Labor Berlin Alt-Moabit 91c, D-10559 Berlin, Germany Tel.: +49.30.238951863 Fax: +49 30 23895 1810 E-Mail tim.polzehl(a)dfki.de<mailto:tim.polzehl@dfki.de> ------------------------------------------------------------- Deutsches Forschungszentrum für Künstliche Intelligenz GmbH Trippstadter Straße 122, 67663 Kaiserslautern, Germany Geschäftsführung: Prof. Dr. Antonio Krüger (Vorsitzender) Helmut Ditzer Vorsitzender des Aufsichtsrats: Dr. Ferri Abolhassan Amtsgericht Kaiserslautern, HRB 2313 -------------------------------------------------------------

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Special issue: Chinese Natural Language Processing for Digital Humanities (CNLP4DH)
by Nicolas Nicolas 19 Jan '24

19 Jan '24

Journal of Data Mining and Digital Humanities (JDMDH) organizes a special issue about the topic Chinese Natural Language Processing for Digital Humanities (CNLP4DH) As a reminder JDMDH is an international-based journal managed by French national research institutions and green open access (no charge for readers and authors). This special issue is dedicated to natural language processing for digital humanities involving the documents written in Chinese, including Modern, Ancient and dialectal Chinese. Mandarin, which is the national official and main common language, can be accepted and research on texts written in other languages, such as Tibet, Inner Mongolia, etc., is also welcome. A list of suitable topics includes but are not limited to: - Text analysis and processing related to humanities using computational methods - Dataset creation and curation for NLP (e.g. digitization, datafication, and data preservation). - Research on cultural heritage collections such as national archives and libraries using NLP - NLP for error detection, correction, normalization and denoising data - Generation and analysis of literary works such as poetry and novels - Analysis and detection of text genres - Word segmentation, part-of-speech tagging of Ancient Chinese - Large Language Models (LLM) for Chinese in Digital Humanities - Cross modal Models (text-speech-video-image) for Chinese in Digital Humanities - Visualization of text analytics - Ontology models for natural language text - Applications in Chinese Literature, Traditional Chinese medicine, Learning Chinese language as second language, Sentiment Analysis in Chinese Social Media, China Cultural Heritage, Chinese History, Ancient Chinese language submission guideline: https://jdmdh.episciences.org/page/submissions Paper submission : https://jdmdh.episciences.org/submit Website and more details: https://jdmdh.episciences. org/page/chinese-natural-language-processing-for-digital-humanities-cnlp4dh# Email: jdmdh(a)episciences.org Guest Editors: Dr. Wenhe FENG (Guangdong University of Foreign Studies, Laboratory of Language Engineering and Computing) Dr. Bin LI (Nanjing Normal University, School of Chinese Language and Literature, Center of Linguistic Big Data and Computational Humanities) Dr. Nicolas TURENNE (Guangdong University of Foreign Studies, School of Information Science and Technology) Dr. Tong WEI (Beijing University, Digital Humanities Center) ************************************************************ ************************

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