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36th International Conference on Advanced Information Systems Engineering (CAiSE 2024): Last Mile for Paper Submission
by Announce 30 Nov '23

30 Nov '23

*** Last Mile for Paper Submission *** 36th International Conference on Advanced Information Systems Engineering (CAiSE'24) June 3-7, 2024, 5* St. Raphael Resort and Marina, Limassol, Cyprus https://cyprusconferences.org/caise2024/ (*** Submission Deadline: Abstract: December 1, 2023 AoE; Paper: December 8, 2023 AoE ***) The CAiSE’24 organization calls for full papers with a special emphasis on the theme of Information Systems in the Age of Artificial Intelligence. Artificial Intelligence (AI) has emerged as a transformative technology, revolutionizing various industries, and its significance in Information Systems cannot be overstated. AI-powered systems have the potential to streamline operations, enhance decision-making processes, and drive innovation across organizations. From data analysis to automated processes, AI is reshaping the way we leverage information in the digital age. The relevance of AI in IS extends beyond internal operations. AI-powered predictive analytics enables organizations to forecast trends, anticipate customer needs, and optimize resource allocation. This empowers businesses to adapt swiftly to changing market dynamics, gain a competitive edge, and make proactive decisions. AI algorithms can also detect anomalies and patterns that indicate potential security breaches, contributing to robust cybersecurity measures in information systems. However, while acknowledging the benefits, it is essential to consider the ethical implications of AI in information systems. Ensuring data privacy, addressing bias in algorithms, and maintaining transparency are vital aspects that need to be carefully managed and regulated to foster trust and accountability. In addition to offering an exciting scientific program, CAiSE’24 will feature a best paper award, a journal special issue, and a PhD-thesis award: • Best Paper Award‚ prize EUR 1000 (sponsored by Springer) • A small selection of best papers will be invited to submit enhanced versions for consideration in a special issue of Elsevier Information Systems journal dedicated to this conference. • PhD-Thesis Award • Best PhD thesis of a past CAiSE Doctoral Consortium author (co-sponsored by the CAiSE Steering Committee and Springer) Papers should be submitted in PDF format. Submissions must conform to Springer‚ LNCS format and should not exceed 15 pages, including all text, figures, references, and appendices. Submissions not conforming to the LNCS format, exceeding 15 pages, or being obviously out of the scope of the conference, will be rejected without review. See the guidelines here: https://www.springer.com/comp/lncs/authors.html . The results described must be unpublished and must not be under review elsewhere. Three to five keywords characterizing the paper should be listed at the end of the abstract. Each paper will be reviewed by at least two program committee members and, if positively evaluated, by one additional program board member. The selected papers will be discussed among the paper reviewers online and during the program board meeting. As the review process is not blind, please indicate your name and affiliation on your submission. Accepted papers will be presented at CAiSE’24 and published in the Springer Lecture Notes in Computer Science (LNCS) conference proceedings. We invite three types of original and scientific papers. The type of submission must be indicated in the submission system. Each contribution should explicitly address the engineering or the operation of information systems, clearly identify the information systems problem addressed, the expected impact of the contribution to information system engineering or operation, and the research method used. We strongly advise authors to clearly emphasize these aspects in their paper, including the abstract. Technical papers describe original solutions (theoretical, methodological or conceptual) in the field of IS Engineering. A technical paper should clearly describe the situation or problem tackled, the relevant state of the art, the position or solution suggested and its potential‚ as well as demonstrate the benefits of the contribution through a rigorous evaluation. Empirical papers evaluate existing problem situations including problems encountered in practice, or validate proposed solutions with scientific means, i.e., by empirical studies, experiments, case studies, experience reports, simulations, etc. Scientific reflection on problems and practices in industry also falls into this category. The topic of the evaluation presented in the paper as well as its causal or logical properties must be clearly stated. The research method must be sound and appropriate. Exploratory papers describe completely new research positions or approaches, in order to face a generic situation arising because of new ICT tools, new kinds of activities, or new IS challenges. They must precisely describe the situation and demonstrate why current methods, tools, ways of reasoning, or meta-models are inadequate. They must also rigorously present their approach and demonstrate its pertinence and correctness in addressing the identified situation. The topics of contribution include but are not limited to: • Novel Approaches to IS Engineering ◦ Artificial Intelligence and Machine Learning ◦ Robotic Process Automation (RPA) ◦ Big Data, Data Science and Analytics ◦ Blockchain applications in IS ◦ Simulation and Digital Twins  ◦ IS for collaboration and social computing  ◦ Virtual reality / Augmented Reality ◦ Context-aware, autonomous and adaptive IS • Models, Methods and Techniques in IS Engineering ◦ Ontologies and Ontology Engineering ◦ Conceptual modeling, languages and design ◦ Requirements engineering ◦ Process modeling, analysis and improvement ◦ Process automation, mining and monitoring ◦ Models and methods for evolution and reuse ◦ Domain and method engineering ◦ Product lines, variability and configuration management ◦ Compliance and alignment handling ◦ Active and interactive models ◦ Quality of IS models for analysis and design ◦ Visualization techniques in IS ◦ Decision models and business intelligence ◦ Knowledge graphs ◦ Human-centered techniques • Architectures and Platforms for IS Engineering ◦ Distributed, mobile and open architecture ◦ Big Data architectures ◦ Cloud- and edge-based IS engineering ◦ Service oriented and multi-agent IS engineering ◦ Multi-platform IS engineering ◦ Cyber-physical systems and Internet of Things (IoT) ◦ Workflow and Process Aware Information Systems (PAIS) ◦ Handling of real time data streams ◦ Content management and semantic Web ◦ Crowdsourcing platforms ◦ Conversational agents (chatbots) ◦ Microservices design and deployment • Domain-specific and Multi-aspect IS Engineering ◦ IT governance ◦ eGovernment ◦ Autonomous and smart systems (smart city management, smart vehicles, etc.) ◦ IS for healthcare ◦ Educational Systems and Learning Analytics ◦ Value and supply chain management ◦ Industry 4.0 ◦ Sustainability and social responsibility management ◦ Privacy, security, trust, and safety management ◦ IS in the post-COVID world Submit your paper using the Easy Chair link: https://easychair.org/conferences/?conf=caise2024 . IMPORTANT DATES • Abstract Submission: 1st December 2023 (AoE, extended and firm) • Paper Submission: 8th December 2023 (AoE, extended and firm) • Notification of Acceptance: 23rd February 2024 • Camera-ready Papers: 5th April 2024 • Author registration: 5th April 2024 ORGANISATION General Chairs • Haris Mouratidis, University of Essex, UK • Pnina Soffer, University of Haifa, Israel Local Organizing and Finance Chair • George A. Papadopoulos, University of Cyprus, Cyprus Program Chairs • Giancarlo Guizzardi, University of Twente, The Netherlands • Flavia Maria Santoro, University of the State of Rio de Janeiro, Brazil Other Committee Members https://cyprusconferences.org/caise2024/committees/

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SEPLN: Deadline extension from 1st to 15th December
by aitziber.atucha＠ehu.eus 29 Nov '23

29 Nov '23

[Spanish version below] Please consider contributing and/or forwarding to appropriate colleagues and groups. *******We apologize for the multiple copies of this e-mail****** SEPLN: CFP Deadline extension from 1st to 15th December for the issue 72 of the Journal Procesamiento del Lenguaje Natural http://www.sepln.org/en/journal http://www.sepln.org/en/journal/author-guidelines Introduction The aim of the journal Procesamiento del Lenguaje Natural is to provide a forum for the publication of scientific-technical articles in the field of Natural Language Processing (NLP), for both the national and international scientific community. The articles must be unpublished and cannot be simultaneously submitted for publication in other journals or conference proceedings. The journal also aims to promote the development of areas related to NLP, disseminate research carried out, identify future guidelines for basic research, and present software applications in this field. Every year the Sociedad Española de Procesamiento del Lenguaje Natural (SEPLN) (Spanish Society for the Natural Language Processing) publishes two issues of the journal, including original articles, presentations of R&D projects, book reviews and summaries of PhD theses. The scientific quality of the Journal is supported by the 2022 JCR index (JCI: 0.31, Q4-Linguistics - ESCI), the SCImago Journal Ranking (2022 SJR: 0.421, Q3-Computer Science Applications, Q1-Linguistics and Language), the Scopus Index (2022 CiteScore: 2.9, Q3-Computer Science Applications, Q1-Linguistics and Language) and the index SNIP (Source Normalized Impact per Paper) with 0.93 points. More information at: http://www.sepln.org/en/journal/quality. Topics Linguistic, mathematical and psycholinguistic models of language Machine learning in NLP Computational lexicography and terminology Corpus linguistics Development of linguistic resources and tools Grammars and formalisms for morphological and syntactic analysis Semantics, pragmatics and discourse Word sense disambiguation Monolingual and multilingual text generation Machine translation Knowledge and common sense Multimodality Speech synthesis and recognition Dialogue systems and interactive systems/ Conversational assistants Audio indexing and retrieval Monolingual and multilingual information extraction and retrieval Question answering systems Evaluation of NLP systems Automatic textual content analysis Sentiment analysis, opinion mining and argument mining Plagiarism detection Negation and speculation processing Text mining in blogosphere and social networks Text summarization Text simplification Image retrieval NLP in biomedical domain NLP-based generation of teaching resources NLP for languages with limited resources NLP industrial applications Low-resource NLP tasks, data augmentation Submission Information The proposal must be submitted by December 15th, 2023 and must meet certain format and style requirements. All submissions must be in PDF format and submitted electronically using the Myreview system available at: http://myreview.sepln.org/myreview-sepln72 Submitted papers will be subjected to a blind review by at least three members of the program committee. Categories of papers Regular papers with original contributions. Summary of PhD thesis. Information for Authors The proposals can be written in Spanish or English and should be at most 10 A4-size pages of content, plus unlimited pages for references, and 4 pages maximum for summaries of PhD theses. The papers must include the following sections: The title of the communication (in English and Spanish). An abstract in English and Spanish (maximum 150 words). A list of keywords or related topics (in English and Spanish). The documents must not include headers or footers. As reviewing will be blind, the paper should not include the authors’ names and affiliation. Furthermore, self-references that reveal the author’s identity should be avoided. The articles should only include the title, the abstract, the keywords and the proposal. We recommend using the LaTeX and Word templates that can be downloaded from the SEPLN web (author guidelines have been updated): http://www.sepln.org/index.php/en/journal/author-guidelines Note on camera ready The final version of the paper (camera ready) should be submitted together with a cover letter explaining how the suggestions of the reviewers were implemented in the final version. This cover letter will be considered in order to accept or finally reject the selected paper. Preprint policy The Journal allows the publication of preprints (non-refereed paper posted online, such as ArXiv) anytime, but during the review period the preprint must indicate that the paper it is “under review” in the Journal Procesamiento del Lenguaje Natural. Likewise, if the paper is accepted, the preprint must be updated with the DOI, name of the Journal and the bibliographic information of the paper. Important dates Submission deadline: 15th December 2023 Notification of acceptance: 5th February 2024 Camera ready: 12th February 2024 Publication: March 2024 Contact person: Aitziber Atutxa (aitziber.atucha(a)ehu.eus) Editorial Committee of the Procesamiento del Lenguaje Natural -------------------------------------------------------------------------------------------------------------------- ***********Disculpen si reciben varias copias de este mensaje ************ Por favor, si lo considera oportuno, distribuya este llamamiento entre sus colegas. SEPLN: Extensión de entrega del 1 al 15 de Diciembre de artículos para la revista Procesamiento del Lenguaje Natural nº 72. http://www.sepln.org/la-revista http://www.sepln.org/la-revista/informacion-para-autores Objetivos de la revista La revista Procesamiento del Lenguaje Natural es un foro de publicación de artículos científico-técnicos en el ámbito del Procesamiento del Lenguaje Natural (PLN), tanto para la comunidad científica nacional como internacional. Los artículos tienen que ser inéditos y no haber sido postulados para ser publicados simultáneamente en otras revistas o actas de congresos. La revista quiere potenciar el desarrollo de las diferentes áreas relacionadas con el PLN, mejorar la divulgación de las investigaciones que se llevan a cabo, identificar las futuras directrices de la investigación básica y mostrar las posibilidades reales de aplicación en este campo. Anualmente la SEPLN (Sociedad Española para el Procesamiento del Lenguaje Natural) publica dos números de la revista, que incluyen artículos originales, presentaciones de proyectos, reseñas bibliográficas y resúmenes de tesis doctorales. La calidad científica de la Revista está respaldada por el índice del JCR 2022 (JCI: 0,31, Q4-Linguistics - ESCI), el índice SCImago Journal Ranking (SJR: 0,421, Q3-Computer Science Applications, Q1-Linguistics and Language), el índice de Scopus (CiteScore: 2,9, Q3-Computer Science Applications, Q1-Linguistics and Language) y el índice SNIP (Source Normalized Impact per Paper) con 0,93 puntos. Más información en http://www.sepln.org/la-revista/calidad. Áreas temáticas Modelos de lenguaje matemáticos y psicolingüísticos Aprendizaje automático en PLN Lexicografía y terminología computacional Lingüística de corpus Desarrollo de recursos y herramientas lingüísticas Gramáticas y formalismos para análisis morfológico y sintáctico Semántica, pragmática y discurso Resolución de ambigüedad léxico-semántica Generación de texto monolingüe y multilingüe Traducción automática Multimodalidad Reconocimiento y síntesis de habla Sistemas de diálogo/ asistentes conversacionales Auto-indexación Recuperación y extracción de información monolingüe y multilingüe Sistemas de búsqueda de respuestas Evaluación de sistemas de PLN Análisis automático de contenido textual Análisis de sentimiento y minería de opiniones Detección de plagio Procesamiento de la negación y la especulación Minería de texto en la blogosfera y las redes sociales Resumen automático de texto Simplificación de texto Recuperación de imágenes Conocimiento y sentido común PLN en el ámbito biomédico Generación de recursos didácticos basada en PLN PLN para lenguas con recursos limitados Aplicaciones industriales del PLN Tratamiento del Lenguaje Hablado Envío de trabajos Las propuestas de trabajos (artículos y resúmenes de tesis) podrán ser enviadas hasta la fecha límite del 15 de diciembre de 2023. El envío y la revisión de las propuestas se realizarán exclusivamente en formato PDF y se gestionarán a través del sistema Myreview: http://myreview.sepln.org/myreview-sepln72. La evaluación de los trabajos pasará por un proceso de revisión ciego realizado como mínimo por tres miembros del consejo asesor de la SEPLN. Tipos de trabajos Artículos sobre contribuciones originales. Reseñas de tesis doctorales. Instrucciones para los Autores Los trabajos pueden estar escritos en español o en inglés y su longitud máxima será de 10 páginas de contenido más un número ilimitado de páginas de referencias para los artículos científicos, y de un máximo de 4 páginas para los resúmenes de tesis. Las propuestas deben contener los siguientes apartados: El título del artículo (en español e inglés). Un resumen en español y un abstract en inglés de un máximo de 150 palabras. Un listado de temas relacionados o palabras clave (en español e inglés). Los documentos no podrán incluir cabeceras ni pies de página. Como la fase de revisión de los trabajos es ciega, en los artículos que se envíen no se debe incluir ninguna referencia a los autores ni referencias propias que revelen la identidad de los mismos. Todas las contribuciones deben contener únicamente el título, el resumen, las palabras claves y la propuesta. En el caso de los resúmenes de tesis, el anonimato no es necesario. Los trabajos deben seguir el formato de las revistas de la SEPLN disponible en la siguiente dirección: http://www.sepln.org/la-revista/informacion-para-autores Las guías se han actualizado, por favor, utilicen las que están disponibles en la página web de la revista. Nota sobre la versión final La versión final del trabajo (camera ready) debe enviarse con un documento en el que se explique cómo se han implementado las sugerencias de los revisores. Dicho documento se tendrá en cuenta para aceptar o rechazar el trabajo en cuestión. Política de prepublicación La revista permite publicar una versión no revisada de los artículos en plataformas de prepublicación (plataformas de artículos no evaluados como ArXiv). Sin embargo, durante el periodo de revisión se debe indicar que el artículo está “en revisión” en la revista Procesamiento del Lenguaje Natural. Si el artículo es aceptado, se debe actualizar la publicación en la plataforma de prepublicación con el DOI, nombre de la revista y la información bibliográfica del artículo. Fechas importantes Envío de trabajos: 15 de diciembre de 2023 Notificación de aceptación o rechazo: 5 de febrero de 2024 Versión final: 12 de febrero de 2024 Publicación: Marzo de 2024 Persona de contacto:Aitziber Atutxa (aitziber.atucha(a)ehu.eus) Consejo de redacción de la revista Procesamiento del Lenguaje Natural.

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NBME Summer Internships in Psychometrics and Data Science
by Christopher Runyon 28 Nov '23

28 Nov '23

NBME (National Board of Medical Examiners) Summer 2024 Internships in Psychometrics and Data Science June 3 - July 26, 2024 NBME invites applications for multiple full-time internship positions, all fully remote, for the Summer of 2024 (June 3 - July 26, 2024). Interns will interact with NBME staff and other graduate students and present completed projects or work-in-progress to NBME staff. The expected deliverables from the summer internship project are an internal research presentation, a conference submission/presentation (ACL, AERA, NCME, AAMC, etc.), and/or a paper submitted for publication. The application deadline is Wednesday, January 31, 2024, at midnight PST. More details can be found here: https://nbme.applicantpro.com/jobs/3142558<https://urldefense.com/v3/__https:/nbme.applicantpro.com/jobs/3142558__;!!P…>. Compensation The pay is $45 an hour. Total stipend for full-time interns (35 hours per week) is $12,600. In addition, NBME will provide up to $1000 toward attending a conference for interns; this is not conditional on presenting at the conference. If you have any questions or need additional information, please contact Chris Runyon: CRunyon(a)nbme.org<mailto:CRunyon@nbme.org> This email message and any attachments may contain privileged and/or confidential business information and are for the sole use of the intended recipient(s). Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please notify the sender immediately by reply email and destroy all copies of the original message and any attachments.

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Reader (~Associate Professor) in AI at the University of Wolverhampton
by Ingo Frommholz 28 Nov '23

28 Nov '23

The University of Wolverhampton (UOW) in the UK is hiring a Reader (Associate Professor equivalent) in Artificial Intelligence (AI). An exciting opportunity has arisen to join UOW as a Reader in Artificial Intelligence. The School of Engineering, Computing and Mathematical Sciences is a large interdisciplinary centre for education, research, and enterprise. We are looking for an experienced researcher to help lead, drive, and advance research and knowledge exchange activities in Artificial Intelligence. This job is a permanent position. Further information and the application form can be found at https://jobs.wlv.ac.uk/vacancy/reader-in-artificial-intelligence-541125.html. -- Ingo Frommholz (he/him), PhD, FBCS, FHEA Reader (~Associate Professor) in Data Science ACM CIKM 2023 General Chair Head of Data, AI, Interaction, Retrieval and Language Group http://dairel.org Deputy Head Digital Innovations and Solutions Centre (DISC) University of Wolverhampton, UK Adjunct Professor, Bern University of Applied Sciences, Switzerland Web: http://www.frommholz.org/ | Email: ifrommholz(a)acm.org Twitter: @iFromm | Mastodon: @ingo@idf.social PGP/GPG fingerprint: B74E A422 C7B2 A5BB 2BC2 523B 2790 216E F8F8 D166 http://pgp.mit.edu:11371/pks/lookup?op=get&search=0x2790216EF8F8D166

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Senior Scientist position in Digital Humanities at the University of Vienna
by benjamin.roth＠univie.ac.at 28 Nov '23

28 Nov '23

The University of Vienna is looking to fill the position of a Senior Scientist in the area of Digital Humanities. Please find the full job posting here: English: https://jobs.univie.ac.at/job/Senior-Scientist-at-the-Institute-for-Europea… German: https://jobs.univie.ac.at/job/Senior-Scientist-am-Institut-f%C3%BCr-Europ%C… For further inquiries, please contact Benjamin Roth (benjamin.roth(a)univie.ac.at) -- Univ.-Prof. Dr. Benjamin Roth Digitale Textwissenschaften Universität Wien Kolingasse 14 Raum 5.17 1090 Wien email: benjamin.roth(a)univie.ac.at tel: +43 14277 79513 virtual coffee (Tuesday 2pm CEST): https://www.benjaminroth.net/virtual_coffee video call: https://univienna.zoom.us/j/93796507934?pwd=VFg5dW9JbStPUml6WFVtOWJXV3phQT09 web: https://dm.cs.univie.ac.at/team/person/112089/

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CFP - NLDB 2024 - The 29th International Conference on Natural Language & Information Systems
by federico.torrielli＠unito.it 27 Nov '23

27 Nov '23

* 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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Internship offers for M2: Robust Dialogue State Tracking for Dialog Management in Conversational AI and Data Augmentation for Low Resource Slot Filling and Intent Classification
by Tulika Bose 27 Nov '23

27 Nov '23

Dear Colleagues, Please find below the description of two internship positions for 2nd year Masters (M2) students at the voice technology startup Vivoka located in Metz, France. The typical duration of the internship is around 5-6 months starting from March 2024. *About Vivoka* Founded in 2015 and awarded two CES Innovation Awards, Vivoka <https://vivoka.com/en/> has created and sells the Voice Development Kit (VDK), the very first solution allowing a company to design a voice interface in a simple, autonomous, and quick way. Moreover, this interface is embedded: it can be deployed on devices without an Internet connection and fully preserves privacy. Accelerated by the COVID-19 health crisis and the need for "no-touch" interfaces, Vivoka is now optimizing this technology by developing its own speech and language processing solutions that are able to compete with the most efficient current technologies. The internship would be carried out as part of Vivoka's R&D team. The interns will benefit from the startup spirit of Vivoka, where they will interact with the researchers and Ph.D. students of the R&D team, and the engineers responsible for integrating their results into the VDK. Internship Requirements: - M2 in Computer Science with a specialization in Machine Learning (ML) or Natural Language Processing (NLP) - Prior knowledge and/or experience with ML/NLP. - Experience with Python programming and frameworks like PyTorch. *1. Robust Dialogue State Tracking for Dialog Management in Conversational AI * Context Conversational systems improve user experience by steering interactions to understand users’ needs and respond by providing informed answers, assistance, invoking services, etc. Unlike non-task-oriented dialogue systems that focus on open-domain conversations, such as chit-chats, task-oriented conversational systems enable users to accomplish certain tasks using the information provided during conversations. One of the critical aspects of conversational systems is the design of dialogue management that allows robust, intelligent, engaging conversations [1, 2, 3]. The focus of this internship is dialogue management in task-oriented conversational systems. In task-oriented dialogue systems, the dialogue state is the component of a dialogue manager that serves as a summary of the entire conversation up to the present turn. It maintains all the essential information that the system needs to give informed responses to the user’s queries. This information comprises mainly the user’s intents (e.g. flight_booking), slots, i.e. information needed to fulfill the intent (e.g. departure and arrival cities), and dialogue acts, i.e. hidden actions in user utterances to indicate their specific communicative function (e.g. request, statement, etc.) [3]. The dialogue states are estimated and tracked by the Dialogue State Tracking (DST) model [4]. Based on the dialogue states, the conversational agent generates subsequent actions to sustain the ongoing conversation. In real-world conversations, the range of potential values for slots is often dynamic and unbounded, such as movie_titles or usernames. Consequently, in recent years, there has been an active focus on open-vocabulary approaches to DST [3]. These approaches involve estimating the possible values for slots from the ongoing conversation and language understanding results, without relying on a predefined set of categories. This research area represents a critical advancement toward DST with zero-shot generalization, which means that adding new intents and slots can be achieved without the need for collecting new data or extensive retraining. This internship aims to explore dialogue management in conversational systems with a particular focus on robust DST approaches that can achieve few-shot or zero-shot generalization. In real use cases, the disfluent nature of spontaneous conversations poses an additional set of challenges for Dialogue Management. The internship will focus on the challenges that are encountered while building robust task-oriented DST approaches meant for real-world applications of conversational systems. Objectives and Expected Outcomes: - Perform a literature review of Dialogue Management - Implement a state-of-the-art Dialogue State Tracking approach in PyTorch - Improve the implemented DST approach to perform few/zero-shot generalization - Perform experiments to examine the challenges with real-world conversations for dialogue management - Perform experiments to examine the generalizability of the implemented DST approach *References:* 1. M. McTear, Z. Callejas, and D. Griol, “The Conversational Interface: Talking to Smart Devices <https://link.springer.com/book/10.1007/978-3-319-32967-3>”, 1st ed. Springer Publishing Company, Incorporated, 2016. 2. Z. Zhang, M. Huang, Z. Zhao, F. Ji, H. Chen, and X. Zhu, “Memory- augmented dialogue management for task-oriented dialogue systems <https://dl.acm.org/doi/abs/10.1145/3317612>,” ACM Transactions on Information Systems (TOIS), 2019. 3. H. Brabra, M. Báez, B. Benatallah, W. Gaaloul, S. Bouguelia and S. Zamanirad, “Dialogue Management in Conversational Systems: A Review of Approaches, Challenges, and Opportunities <https://ieeexplore.ieee.org/document/9447005>,” in IEEE Transactions on Cognitive and Developmental Systems, vol. 14, no. 3, pp. 783-798, 2022 4. Jason Williams, Antoine Raux, Deepak Ramachandran, and Alan Black. 2013. “The Dialog State Tracking Challenge <https://aclanthology.org/W13-4065/>”. In Proceedings of the SIGDIAL 2013 Conference, pages 404–413, Association for Computational Linguistics, 2013. *2.* *Data Augmentation for Low Resource Slot Filling and Intent Classification* Context: Neural-based models have achieved outstanding performance on slot and intent classification when fairly large in-domain training data is available. However, as new domains are frequently added, creating sizable data is expensive. Some approaches [1, 2] suggest a set of augmentation methods involving word span and sentence level operations, alleviating data scarcity problems. We target more complex state-of-the-art augmentation approaches that allow models to achieve competitive performance on small (English and French) data. Furthermore, we will investigate the exploitation of pretrained Large Language Models such as [3] for data augmentation, and how it can affect slot filling and intent classification performance for those languages. Objectives and Expected Outcomes: - Experiments on low and large resource data - Implement different approaches to augment data for slot filling and intent classification - Evaluate the quality of the generated data - Evaluate the effect of data augmentation on slot filling and intent classification - Integrate the tool into our NLU system - Develop a Python module for Data Augmentation dedicated to the task - Evaluate the module on several real use cases. References: 1. Jason W. Wei and Kai Zou. 2019. "EDA: easy data augmentation techniques for boosting performance on text classification tasks <https://aclanthology.org/D19-1670/>". In Kentaro Inui, Jing Jiang, Vincent Ng, and Xiaojun Wan, editors, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019, pages 6381–6387. Association for Computational Linguistics 2. Marzieh Fadaee, Arianna Bisazza, and Christof Monz. 2017. "Data augmentation for low-resource neural machine translation <https://aclanthology.org/P17-2090/>". In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 567–573, Vancouver, Canada, July. Association for Computational Linguistic 3. Ray, Partha Pratim. "ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. <https://www.sciencedirect.com/science/article/pii/S266734522300024X>" Internet of Things and Cyber-Physical Systems (2023). Please submit your applications to tulika.bose(a)vivoka.com or firas.hmida(a)vivoka.com. Please feel free to share this call for applications with any interested students. Best Regards, Tulika Bose AI Researcher Vivoka

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CAiSE'24 Forum: First Call for Papers and Tool Demonstrations
by Announce 26 Nov '23

26 Nov '23

*** CAiSE'24 Forum: First Call for Papers and Tool Demonstrations *** 36th International Conference on Advanced Information Systems Engineering (CAiSE'24) June 3-7, 2024, 5* St. Raphael Resort and Marina, Limassol, Cyprus https://cyprusconferences.org/caise2024/ (*** Submission Deadline: March 4, 2024 AoE ***) The CAiSE Forum is a space within the CAiSE conference to present and discuss the new exciting ideas and tools related to Information Systems Engineering. The Forum intends to serve as an interactive platform, encourage potential authors to present emerging topics and controversial positions, and demonstrate innovative systems, tools, and applications. The Forum sessions at the CAiSE conference will facilitate the interaction, discussion, and exchange of ideas among presenters and participants. Contributions to the CAiSE'24 Forum are welcome to address any of the CAiSE'24 conference topics and, particularly, this year's theme—Information Systems in the Age of Artificial Intelligence. We invite two types of submissions: • Visionary papers present innovative research projects, which are still at a relatively early stage and do not necessarily include a full-scale validation. Visionary papers will be presented as posters in the Forum. • Demo papers describe innovative tools and prototypes that implement the results of research efforts. The tools and prototypes will be presented as demos in the Forum, accompanied by a poster. Both visionary papers and demo papers must not exceed 8 pages in LNCS format. See authors' guidelines at the Springer site: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu… . Papers should be submitted in PDF format through the conference management system available at Easy Chair (https://easychair.org/my/conference?conf=caise2024) and select the Forum option. The submitted papers must be unpublished and must not be under review elsewhere. PUBLICATION AND PRESENTATIONS Accepted papers will be published by Springer in a CAISE Forum proceedings volume within the Lecture Notes in Business Information Processing (LNBIP) series (https://www.springer.com/series/7911). Authors should consult Springer's authors guidelines and use their LaTeX or Word proceedings templates for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each paper, acting on behalf of all of the authors of that paper, must complete and sign a Consent-to-Publish form. The corresponding author signing the copyright form should match the corresponding author marked on the paper. Once the files have been sent to Springer, changes relating to the authorship of the papers cannot be made. It is expected that at least one of the authors attends CAiSE'24, presents the poster/delivers the demo, and interacts with the Forum participants. We also envision a short oral presentation for all papers to attract participants to the posters. IMPORTANT DATES • Paper Submission Deadline: 4th March, 2024 (AoE) • Notification of Acceptance: 1st April, 2024 • Camera-ready Deadline: 8th April, 2024 • Author Registration Deadline: 8th April, 2024 FORUM CHAIRS • Shareeful Islam, Anglia Ruskin University, United Kingdom • Arnon Sturm, Ben-Gurion University of the Negev, Israel FORUM COMMITTEE • Steven Alter, University of San Francisco • Abel Armas Cervantes, The University of Melbourne • Giuseppe Berio, Université de Bretagne Sud and IRISA UMR 6074 • Drazen Brdjanin, University of Banja Luka • Corentin Burnay, University of Namur • Cinzia Cappiello, Politecnico di Milano • Suphamit Chittayasothorn, King Mongkut's Institute of Technology Ladkrabang • Maya Daneva, University of Twente • Sergio de Cesare, University of Westminster • Johannes De Smedt, KU Leuven • Marne de Vries, University of Pretoria • Michael Fellmann, University of Rostock • Christophe Feltus, Luxembourg Institute of Science and Technology • Hans-Georg Fill, University of Fribourg • Janis Grabis, Riga Technical University • Sergio Guerreiro, INESC-ID / Instituto Superior Técnico • Martin Henkel, Stockholm University • Jennifer Horkoff, Chalmers University of Technology • Shareeful Islam, Anglia Ruskin University • Janis Kampars, RTU • Evangelia Kavakli, University of the Aegean • Marite Kirikova, Riga Technical University • Janne J. Korhonen, Aalto University • Elena Kornyshova, CNAM • Agnes Koschmider, University of Bayreuth • Chung Lawrence, University of Texas at Dallas • Henrik Leopold, Kühne Logistics University • Tong Li, Beijing University of Technology • Beatriz Marín, Universidad Politecnica de Valencia • Andrea Marrella, Sapienza University of Rome • Raimundas Matulevicius, University of Tartu • Jose Ignacio Panach Navarrete, Universitat de València • Oscar Pastor, Universidad Politécnica de Valencia • Francisca Pérez, Universidad San Jorge • Pierluigi Plebani, Politecnico di Milano • Manuel Resinas, University of Seville • Genaina Rodrigues, University of Brasilia • Ben Roelens , Open Universiteit, Ghent University • Mattia Salnitri, Politecnico di Milano • Stefan Strecker, University of Hagen • Arnon Sturm, Ben-Gurion University of the Negev • Irene Vanderfeesten, Katholieke Universiteit Leuven • Yves Wautelet, Katholieke Universiteit Leuven • Hans Weigand, Tilburg University • Manuel Wimmer, Johannes Kepler University Linz • Anna Zamansky, University of Haifa

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TOC: Journal of Language Modelling 11(1)
by Adam Przepiórkowski 26 Nov '23

26 Nov '23

It is our pleasure to announce the publication of issue 11(1) of the Journal of Language Modelling (JLM), a free open-access peer-reviewed journal aiming to bridge the gap between theoretical, formal and computational linguistics: http://jlm.ipipan.waw.pl/ (see “CURRENT” or “ALL ISSUES”). The direct persistent link to this issue is: http://jlm.ipipan.waw.pl/index.php/JLM/issue/view/29. JLM is indexed by SCOPUS, ERIH PLUS, DBLP, DOAJ, etc., and it is a member of OASPA. TABLE OF CONTENTS: “On regular copying languages” Yang Wang, Tim Hunter 1–66 “Evaluating syntactic proposals using minimalist grammars and minimum description length” Marina Ermolaeva 67–119 “An algebraic approach to translating Japanese” Valentin Boboc 121–146 “We thought the eyes of coreference were shut to multiword expressions and they mostly are” Agata Savary, Jianying Liu, Anaëlle Pierredon, Jean-Yves Antoine, Loïc Grobol 147–187 The current make-up of the JLM Editorial Board is enclosed below. Best regards, Adam Przepiórkowski (JLM Editor-in-Chief) ====================================================================== EDITORIAL BOARD: Steven Abney, University of Michigan, USA Ash Asudeh, University of Rochester, USA Chris Biemann, Universität Hamburg, GERMANY Igor Boguslavsky, Technical University of Madrid, SPAIN; Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, RUSSIA António Branco, University of Lisbon, PORTUGAL David Chiang, University of Southern California, Los Angeles, USA Greville Corbett, University of Surrey, UNITED KINGDOM Dan Cristea, University of Iași, ROMANIA Jan Daciuk, Gdańsk University of Technology, POLAND Mary Dalrymple, University of Oxford, UNITED KINGDOM Darja Fišer, University of Ljubljana, SLOVENIA Anette Frank, Universität Heidelberg, GERMANY Claire Gardent, CNRS/LORIA, Nancy, FRANCE Jonathan Ginzburg, Université Paris-Diderot, FRANCE Stefan Th. Gries, University of California, Santa Barbara, USA Heiki-Jaan Kaalep, University of Tartu, ESTONIA Laura Kallmeyer, Heinrich-Heine-Universität Düsseldorf, GERMANY Jong-Bok Kim, Kyung Hee University, Seoul, KOREA Kimmo Koskenniemi, University of Helsinki, FINLAND Jonas Kuhn, Universität Stuttgart, GERMANY Alessandro Lenci, University of Pisa, ITALY Ján Mačutek, Comenius University in Bratislava, SLOVAKIA Igor Mel’čuk, University of Montreal, CANADA Glyn Morrill, Technical University of Catalonia, Barcelona, SPAIN Stefan Müller, Humboldt Universität zu Berlin, GERMANY Mark-Jan Nederhof, University of St Andrews, UNITED KINGDOM Petya Osenova, Sofia University, BULGARIA David Pesetsky, Massachusetts Institute of Technology, USA Maciej Piasecki, Wrocław University of Technology, POLAND Christopher Potts, Stanford University, USA Louisa Sadler, University of Essex, UNITED KINGDOM Agata Savary, Université François Rabelais Tours, FRANCE Sabine Schulte im Walde, Universität Stuttgart, GERMANY Stuart M. Shieber, Harvard University, USA Mark Steedman, University of Edinburgh, UNITED KINGDOM Stan Szpakowicz, School of Electrical Engineering and Computer Science, University of Ottawa, CANADA Shravan Vasishth, Universität Potsdam, GERMANY Zygmunt Vetulani, Adam Mickiewicz University, Poznań, POLAND Aline Villavicencio, Federal University of Rio Grande do Sul, Porto Alegre, BRAZIL Veronika Vincze, University of Szeged, HUNGARY Shuly Wintner, University of Haifa, ISRAEL Zdeněk Žabokrtský, Charles University in Prague, CZECH REPUBLIC ====================================================================== Adam Przepiórkowski ˈadam ˌpʃɛpjurˈkɔfskʲi http://clip.ipipan.waw.pl/ ____ Computational Linguistics in Poland http://jlm.ipipan.waw.pl/ ___________ Journal of Language Modelling http://zil.ipipan.waw.pl/ ____________ Linguistic Engineering Group http://nkjp.pl/ _________________________ National Corpus of Polish

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Submission Deadline Extended | AAAI Workshop on Responsible Language Models (ReML) | December 1, 2023
by faizakhankhattak＠gmail.com 25 Nov '23

25 Nov '23

Dear colleagues, ******Due to several requests, the submission deadline has been extended until December 1, 2023.*********** AAAI Workshop on Responsible Language Model (ReLM) 2024 organizers invite you to submit your research. **Submission deadline: December 1, 2023** More info can be found on the Workshop website: https://sites.google.com/vectorinstitute.ai/relm2024/home The Responsible Language Models (ReLM) workshop focuses on both the theoretical and practical challenges related to the design and deployment of responsible Language Models (LMs) and will have strong multidisciplinary components, promoting dialogue and collaboration in order to develop more trustworthy and inclusive technology. We invite discussions and research on key topics such as bias identification & quantification, bias mitigation, transparency, privacy & security issues, hallucination, uncertainty quantification, and various other risks in LMs. Topics: We are interested, but not limited to the following topics: explainability and interpretability techniques for different LLMs training paradigms; privacy, security, data protection and consent issues for LLMs; bias and fairness quantification, identification, mitigation and trade-offs for LLMs; robustness, generalization and shortcut learning analysis and mitigation for LLMs; uncertainty quantification and benchmarks for LLMs; ethical AI principles, guidelines, dilemmas and governance for responsible LLM development and deployment. ReLM 2024 | 26 February 2024 | Vancouver, Canada Looking forward to your submissions, Organizing committee of ReLM 2024 relm.aaai2024(a)gmail.com

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