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The 12th IEEE International Conference on Mobile Cloud Computing, Services and Engineering (IEEE Mobile Cloud 2024): Second Call for Papers
by Announce 16 Mar '24

16 Mar '24

*** Second Call for Papers *** IEEE Mobile Cloud 2024 The 12th IEEE International Conference on Mobile Cloud Computing, Services and Engineering July 15-18, 2024 | Shanghai, China https://ieeemobilecloud.com IEEE Mobile Cloud is a pioneering IEEE sponsored international conference devoted to the research in mobile, edge, and cloud computing. It covers all aspects of mobile, edge, and cloud computing from architectures, techniques, tools and methodologies to applications. This year's conference is scheduled to take place in Shanghai, China, from 15-18 July 2024. IEEE Mobile Cloud 2024 is part of the IEEE International Congress On Intelligent And Service- Oriented Systems Engineering offering a broad spectrum of international events, sharing renowned keynotes and fostering exchange among researchers and practitioners (see common homepage for all colocated events, https://ieee-cisose-congress.org). The fusion of mobile communications, computing, and intelligence is catalysing the emergence of innovative systems and applications that facilitate intelligent resource provisioning, process extensive data from mobile sensors and interconnected hardware platforms, and bolster the Internet of Things (IoT) through robust edge and cloud-based backend infrastructure. The pivotal role of current and forthcoming communication technologies, machine learning implementation, and mobile cloud infrastructures as facilitators for this convergence cannot be understated. These mobile intelligent applications are poised to revolutionise various facets of daily life, encompassing domains such as transportation, e-commerce, healthcare, smart homes, smart cities, social interaction, and more. Mobile intelligence serves as an inclusive platform for both academic and industrial researchers to share their latest research insights, experimental findings, and the latest advancements in industry technologies related to mobile systems, machine learning, edge and cloud computing, services, and engineering. Leveraging the synergy of mobile communications, machine intelligence, edge computing, and edge/cloud infrastructures, the future of Mobile Intelligence Systems is envisioned to provide a multitude of critical and personalised services across diverse application domains, ranging from education, transportation, to public health, safety, and security. Submissions will be evaluated on the criteria of originality, significance, clarity, relevance, and accuracy. TOPICS OF INTEREST They include but not limited to: Theory, Modelling, and Methodologies • Mobile cloud computing models, architectures, infrastructures, and platforms • Mobile intelligence theories, concepts, algorithms, and methodologies • Mobile cloud data management • Mobile cloud tools, middleware, and data centres • Mobile intelligence as a service • Mobile networking, protocols, and technologies • Quality of service (QoS) • Mobile intelligence security and privacy Applications and Industry Practice • Mobile intelligence for autonomous driving systems, V2X, intelligent transportation systems (ITS), telematics • Mobile intelligence for robotics, unmanned aerial vehicles (UAVs), and unmanned ground vehicles (UGVs) • Mobile intelligence for sensor networks, Industrial IoT, industrial 4.0, and industry 5.0 • Mobile intelligence for future wireless technologies, 5G/6G, WiFi, Satellite, etc. • Mobile intelligence for aviation, airports, and railway • Mobile intelligence for Augmented Reality/Virtual Reality (AR/VR) • Mobile intelligence for computer vision and video analytics • Mobile intelligence for surveillance and disaster management • Mobile intelligence for healthcare • Mobile intelligence for the metaverse • Mobile intelligence for smart city • Mobile intelligence for satellite • Mobile intelligence for mission-critical systems • Mobile intelligence for community services and social networking • Mobile intelligence computing for sustainable development PAPER SUBMISSION GUIDELINES Papers must be written in English. All papers must be prepared in the IEEE double column proceedings format. Please see the following link for details: https://www.ieee.org/conferences/publishing/templates.html . All accepted conference papers will be published by IEEE Computer Society and IEEE Explore digital library with EI-index. Selected papers will be recommended to SCI-index journals as special issue papers. The paper length should be up to 8 pages for regular conference papers and 6 pages for work-in-progress papers. Submitted papers should contain original work and not being submitted elsewhere. Each paper must be presented by an author at the conference. Presentations via teleconference are not permitted. Permissions to have the paper presented by a qualified substitute presented may be granted by the TCP Chairs under extraordinary circumstances, upon written request. Submissions should be made via Easy Chair using the following link: https://easychair.org/my/conference?conf=imc24 . IMPORTANT DATES • Abstract submission: March 31st, 2024 (AoE) • Paper submission: April 7th, 2024 (AoE) • Notification of acceptance: May 15th, 2024 • Final manuscript submission: May 22nd, 2024 • Author registration: May 22nd, 2024 • Conference: July 15th-18th, 2024 COMMITTEES General Chairs • Hiroyuki Sato, University of Tokyo, Japan • Yan Bai, University of Washington Tacoma, USA Program Chairs • Lan Zhang, Clemson University, USA • Sun Yao, The University of Glasgow, Scotland, UK • Tomoki Watanabe, Kanagawa Institute Technology, Japan • Fan Wu, Shanghai Jiao Tong University, China Publicity Chair George Angelos Papadopoulos, University of Cyprus, Cyprus Program Committee • Ouri Wolfson, University of illinois • Felix Beierle, University of Würzburg • Thomas Richter, Rhein-Waal University of Applied Sciences • Dan Grigoras, University College Cork • Sergio Ilarri, University of Zaragoza • Iulian Sandu Popa, University of Versailles Saint-Quentin & INRIA Saclay-Ile-de-France • Haiping Xu, University of Massachusetts Dartmouth • Prasad Calyam, University of Missouri • Dana Petcu, West University of Timisoara • Fabio Costa, Federal University of Goias • Cristian Borcea, New Jersey Institute of Technology • Lei Huang, Prairie View A&M University • Chunsheng Zhu, Southern University of Science and Technology • Xuyun Zhang, Macquarie University • Jia Zhao, Changchun Institute of Technology • Richard Han, University of Colorado Boulder CISOSE General Chairs • Jerry Gao, San Jose State University, USA • Iraklis Varlamis, Harokopio University of Athens, Greece CISOSE Steering Committee • Jerry Gao, San Jose State University, USA • Guido Wirtz, University of Bamberg, Germany • Huaimin Wang, NUDT, China • Jie Xu, University of Leeds, UK • Wei-Tek Tsai, Arizona State University, USA • Axel Kupper, TU Berlin, Germany • Hong Zhu, Oxford Brookes University, UK • Longbin Cao, University of Technology Sydney, Australia • Cristian Borcea, New Jersey Institute of Technology, USA • Sato Hiroyuki, University of Tokyo, Japan

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Call for Abstracts: the 34th Meeting on Computational Linguistics in the Netherlands, Leiden University
by Wijnholds, G.J. (Gijs) 15 Mar '24

15 Mar '24

Dear colleague, We warmheartedly invite abstracts for 34th Meeting of Computational Linguistics in The Netherlands (CLIN34), that will take place in Leiden on Friday 30 August 2024. Abstracts describing work on any aspect of computational linguistics / natural language processing (finished or in progress), are welcome. Submissions must be written in English and must be submitted through this web form<https://docs.google.com/forms/d/1G2Ee1LUfQdmh2xQz8T46YcR1BXUMuB4q4iuAKq9sp8Q>. Please provide all information requested in the form. The submission deadline is May 15th 2023 and notifications of acceptance will be sent out on June 15th 2023. Authors of accepted abstracts will have the opportunity to submit a full paper after the conference to CLIN Journal. Please visit the CLIN34 website<https://clin34.leidenuniv.nl/> for more info on the event. We look forward to your abstract! The CLIN34 organizers Leiden University

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March 2024 Newsletter - LDC
by Penn LDC 15 Mar '24

15 Mar '24

In this newsletter: LDC data and commercial technology development New publications: RATS Low Speech Density<https://catalog.ldc.upenn.edu/LDC2024S03> BabyEars Affective Vocalizations<https://catalog.ldc.upenn.edu/LDC2024S04> ________________________________ LDC data and commercial technology development For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing<https://www.ldc.upenn.edu/data-management/using/licensing> page for further information. ________________________________ New publications: RATS Low Speech Density<https://catalog.ldc.upenn.edu/LDC2024S03> was developed by LDC and is comprised of 87 hours of English, Levantine Arabic, Farsi, Pashto, and Urdu speech, and non-speech samples. The recordings were assembled by concatenating a randomized selection of speech, communications systems sounds, and silence. This corpus was created to measure false alarm performance in RATS speech activity detection systems. The source audio was extracted from RATS development and progress sets and consists of conversational telephone speech recordings collected by LDC. Non-speech samples were selected from communications systems sounds, including telephone network special information tones, radio selective calling signals, HF/VHF/UHF digital mode radio traffic, radio network control channel signals, two-way radio traffic containing roger beeps, and short duration shift-key modulated handset data transmissions. The goal of the RATS (Robust Automatic Transcription of Speech) program was to develop human language technology systems capable of performing speech detection, language identification, speaker identification, and keyword spotting on the severely degraded audio signals that are typical of various radio communication channels, especially those employing various types of handheld portable transceiver systems. 2024 members can access this corpus through their LDC accounts. Non-members may license this data for a fee. * BabyEars Affective Vocalizations<https://catalog.ldc.upenn.edu/LDC2024S04> contains 22 minutes of spontaneous English speech by 12 adults interacting with their infant children, for a total of 509 infant-directed utterances and 185 adult-directed or neutral utterances. Speech data was collected in a quiet room during a one-hour session where each sparent was asked to play and otherwise interact normally with their infant (aged 10-18 months). A trained research assistant then extracted discrete utterances and classified them in three categories: approval, attention, and prohibition. 2024 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee. To unsubscribe from this newsletter, log in to your LDC account<https://catalog.ldc.upenn.edu/login> and uncheck the box next to "Receive Newsletter" under Account Options or contact LDC for assistance. Membership Coordinator Linguistic Data Consortium<ldc.upenn.edu> University of Pennsylvania T: +1-215-573-1275 E: ldc(a)ldc.upenn.edu<mailto:ldc@ldc.upenn.edu> M: 3600 Market St. Suite 810 Philadelphia, PA 19104

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[CFP] Workshop on Multimodal Semantic Representations
by Lucia Donatelli 15 Mar '24

15 Mar '24

FIRST CALL FOR PAPERS *Multimodal Semantic Representations (MMSR II)* Co-located with ECAI 2024 (https://www.ecai2024.eu/) 19-24 October, Santiago de Compostela, Spain (workshop on 19 or 20 October) *Workshop website*: https://mmsr-workshop.github.io/ *Description* The demand for more sophisticated natural human-computer and human-robot interactions is rapidly increasing as users become more accustomed to conversation-like interactions with AI and NLP systems. Such interactions require not only the robust recognition and generation of expressions through multiple modalities (language, gesture, vision, action, etc.), but also the encoding of situated meaning. When communications become multimodal, each modality in operation provides an orthogonal angle through which to probe the computational model of the other modalities, including the behaviors and communicative capabilities afforded by each. Multimodal interactions thus require a unified framework and control language through which systems interpret inputs and behaviors and generate informative outputs. This is vital for intelligent and often embodied systems to understand the situation and context that they inhabit, whether in the real world or in a mixed-reality environment shared with humans. Furthermore, multimodal large language models appear to offer the possibility for more dynamic and contextually rich interactions across various modalities, including facial expressions, gestures, actions, and language. We invite discussion on how representations and pipelines can potentially integrate such state-of-the-art language models. We solicit papers on multimodal semantic representation, including but not limited to the following topics: 1. Semantic frameworks for individual linguistic co-modalities (e.g. gaze, facial expression); 2. Formal representation of situated conversation and embodiment, including knowledge graphs, designed to represent epistemic state; 3. Design, annotation, and corpora of multimodal interaction and meaning representation; 4. Challenges (including cross-lingual and cross-cultural) in multimodal representation and/or processing; 5. Criteria or frameworks for evaluation of multimodal semantics; 6. Challenges in aligning co-modalities in formal representation and/or NLP tasks; 7. Design and implementation of neurosymbolic or fusion models for multimodal processing (with a representational component); 8. Methods for probing knowledge of multimodal (language and vision) models; 9. Virtual and situated agents that embody multimodal representations of common ground. *Submission Information* Two types of submissions are solicited: long papers and short papers. Long papers should describe original research and must not exceed 8 pages, excluding references. Short papers (typically system or project descriptions, or ongoing research) must not exceed 4 pages, excluding references. Accepted papers get an extra page in the camera-ready version. We strongly encourage students to submit to the workshop. *Important Dates* May 15, 2024: Submissions due June 1, 2024: Notification of acceptance decisions June 21, 2024: Camera-ready papers due Papers should be formatted using the ECAI style files, available at: https://www.ecai2024.eu/calls/main-track Papers will be submitted in PDF format via the chairing tool site, with a workshop link available soon: https://chairingtool.com/ Please do not hesitate to reach out with any questions. Best regards, Richard Brutti, Lucia Donatelli, Nikhil Krishnaswamy, Kenneth Lai, & James Pustejovsky (MMSR II organizers) Web page: https://mmsr-workshop.github.io/

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Call application for female researchers at National Center of AI CHILE (CENIA)
by Felipe Bravo 15 Mar '24

15 Mar '24

The National Center for Artificial Intelligence (Cenia) invites female researchers interested in developing their postdoctoral research in AI topics to apply to be part of our center. By Cenia’s commitment to actively promote gender equity in artificial intelligence (AI) research, we have issued a call for applications for female researchers only. Researchers must have a PhD in Artificial Intelligence, Computer Science, Mathematics, Robotics, Computational Neuroscience, Physics, or related scientific areas. Applicants must have previous experience in AI, either working in AI or having knowledge of AI tools. A good level of English is highly recommended. The purpose of this position is to support the scientific activities of the center’s main research lines: *RL1 deep learning for vision and language:* new theories and methods to continue to unlock the potential of deep learning and create advanced cognitive systems focusing on vision and language. *RL2 neuro-symbolic AI:* integration of logic-probabilistic and deep learning-based AI, mutually invoking each other’s solutions, injecting and using semantics in deep learning. *RL3 AI inspired by brain:* bring together scientists from neuroscience, cognitive psychology, and AI to integrate knowledge about anatomical structures and cognitive operations of the brain to inspire AI research. *RL4 physics-based machine learning:* bring together mathematicians, physicists, and AI scientists to exploit knowledge from the physical sciences to develop machine learning models based on causal relationships. *RL5 Human-centered AI:* New technologies for a fair, safe and transparent use of AI in society, as well as methodologies to assess its impact on society. Promote new tools for interpretable and explainable AI. *Eligibility criteria:* Applicants must have a Ph.D. degree, research experience, and experience or expertise in the development or use of artificial intelligence tools. *Background information to be attached to the application:* 1. Complete updated CV. 2. Letter of interest (1 page): State the reasons for joining Cenia. 3. 2-year work proposal (maximum 2 pages): This proposal must be sponsored by a Cenia researcher of any category, i.e. Principal Investigator, Associate Researcher or Researcher of the center. The sponsor will support the applicant in his/her work. 4. Two letters of recommendation (free format). 5. Letter from the Sponsor (fixed format <https://docs.google.com/document/d/1YOtEH9bLhH3GZX_g__i2qqdCaiAYWS28/edit?r…> ). All the documentation required for the application must be sent to postdoc(a)cenia.cl, as well as any doubts or questions about the position that may arise at the time of application. The subject of the email should be: Postdoc application. *We invite you to apply until March 30, 2024.* *Estimated Process Periods* *Application Period:* - Starts: January 30. - Ends: March 30, 2024 until 23:59. *Evaluation of Applications:* - Document review: until April 20, 2024 *Request for Letters of Recommendation* - Deadline: April 22nd *Interviews with pre-selected candidates:* - Deadline: April 30 - Shortlisted candidates will be invited to interviews with the Review Committee to discuss in detail their research proposal and experience. *Announcement of Results:* - Deadline: May 15th *Start of employment*: - End of May or deadline to be agreed *The dates indicated are estimates and may change depending on the contingencies of the research center.* *Benefits:* - Full-time contract (44 hours/week) for one year extendable to a longer period. - Gross monthly salary of $2,482,000 CLP (~ equivalent to 2,700 USD). - Access to a stimulating research environment, excellent facilities and computing resources. - Full-time dedication to research development, with no teaching obligations. - Extra support and sponsorship when applying for complementary funding opportunities from the Chilean government. *Important information* These will be evaluated on a case-by-case basis for particular situations involving part-time. More details at: https://www.cenia.cl/en/2024/01/30/call-for-applications-for-female-postdoc/

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Postdoctoral Position at National Center of AI CHILE (CENIA)
by Felipe Bravo 15 Mar '24

15 Mar '24

The National Center for Artificial Intelligence (Cenia), as part of its development plan 2024, invites applications for the position of Postdoc in AI and related areas. The applicant must have a PhD in topics related to Artificial Intelligence, Computer Science, Cognitive Robotics, Physics, Mathematics, Neuroscience, Data Science or related scientific areas. It is mandatory that applicants have previous experience in AI, either working in AI or having knowledge of AI tools. A good level of English is highly recommended. The purpose of this position is to support the scientific activities of the center’s main research lines: *RL1 deep learning for vision and language:* new theories and methods to continue to unlock the potential of deep learning and create advanced cognitive systems focusing on vision and language. *RL2 neuro-symbolic AI:* integration of logic-probabilistic and deep learning-based AI, mutually invoking each other’s solutions, injecting and using semantics in deep learning. *RL3 AI inspired by brain:* bring together scientists from neuroscience, cognitive psychology, and AI to integrate knowledge about anatomical structures and cognitive operations of the brain to inspire AI research. *RL4 physics-based machine learning:* bring together mathematicians, physicists, and AI scientists to exploit knowledge from the physical sciences to develop machine learning models based on causal relationships. *RL5 Human-centered AI:* New technologies for a fair, safe and transparent use of AI in society, as well as methodologies to assess its impact on society. Promote new tools for interpretable and explainable AI. *Eligibility criteria:* Applicants must have a Ph.D. degree, research experience, and experience or expertise in the development or use of artificial intelligence tools. *Background information to be attached to the application:* 1. Complete updated CV. 2. Letter of interest (1 page): State the reasons for joining Cenia. 3. 2-year work proposal (maximum 2 pages): This proposal must be sponsored by a Cenia researcher of any category, i.e. Principal Investigator, Associate Researcher or Researcher of the center. The sponsor will support the applicant in his/her work. 4. Two letters of recommendation (free format). 5. Letter from the Sponsor (fixed format <https://docs.google.com/document/d/1YOtEH9bLhH3GZX_g__i2qqdCaiAYWS28/edit?r…> ). All the documentation required for the application must be sent to postdoc(a)cenia.cl, as well as any doubts or questions about the position that may arise at the time of application. The subject of the email should be: Postdoc application. *Estimated process periods* *Application Period:* - Starts: February 22 - Ends: March 30, 2024 until 23:59. *Evaluation of Applications:* - Document review: until April 20, 2024 *Request for Letters of Recommendation* - Deadline: April 22nd *Interviews with pre-selected candidates:* - Deadline: April 30 - Shortlisted candidates will be invited to interviews with the Review Committee to discuss in detail their research proposal and experience. *Announcement of Results:* - Deadline: May 15th *Start of employment*: - End of May or deadline to be agreed *The dates indicated are estimates and may change depending on the contingencies of the research center.* *Benefits:* - Full-time contract (44 hours/week) for one year extendable to a longer period. - Gross monthly salary of $2,482,000 CLP (~ equivalent to 2,700 USD). - Access to a stimulating research environment, excellent facilities and computing resources. - Full-time dedication to research development, with no teaching obligations. - Extra support and sponsorship when applying for complementary funding opportunities from the Chilean government. *We invite you to apply until March 30, 2024.* More details at: https://www.cenia.cl/en/2024/02/23/call-for-application-artificial-intellig…

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AIRiAL 2024 Call for Proposals
by Voss, Erik 15 Mar '24

15 Mar '24

**Apologies for cross-posting** *CALL FOR PROPOSALS* 2nd Annual Artificial Intelligence Research in Applied Linguistics (AIRiAL) Conference *Theme* AI in Education: Empowering Learners & Preparing Educators *Location* Teachers College, Columbia University *Dates* September 27-28, 2024 *Call for Proposals and submission site*: *https://n9.cl/airial24_cfp <https://n9.cl/airial24_cfp>* Submission deadline: *April 30, 2024* The AL & TESOL Language and Technology Research Group <https://sites.google.com/tc.columbia.edu/al-tesol-language-technology/home> in the Applied Linguistics & TESOL program at Teachers College will host the second annual Conference on Artificial Intelligence Research in Applied Linguistics (AIRiAL). The theme of this conference emphasizes the transformative role of artificial intelligence (AI) in education and language teaching focusing on AI literacy among learners and the preparedness of educators for the AI-driven future. We are interested in contributions that showcase AI technologies prioritizing human values, ethics, and the enhancement of human capabilities in the context of applied linguistics. Submissions may cover a wide array of topics within the scope AI literacy and applied linguistics, including but not limited to: - AI-driven language learning platforms - Adaptive language teaching methodologies - AI in language assessment and feedback - Ethical considerations in AI-driven language education - Personalized language learning experiences with AI - Integrating AI in language curriculum development - Teacher training for AI-enhanced language teaching - Innovative applications of AI in language education - Future directions of AI in language learning and teaching *Presentation Types* - Papers - Posters - Colloquia - Technology Demonstrations *Student Paper Award * An award will be presented to the best student paper presentation at the conference. All authors on student papers must be actively-enrolled graduate students at the time of the conference. -- Erik Voss, Ph.D. Assistant Professor, Applied Linguistics & TESOL program Language & Technology Specialization Department of Arts & Humanities Teachers College, Columbia University TC Faculty Profile <https://www.tc.columbia.edu/faculty/ev2449/>, Linkedin Profile <https://www.linkedin.com/in/erik-voss-ph-d-941a3ab9>, Google Scholar <https://scholar.google.com/citations?user=FMnVdjcAAAAJ&hl=en> ALTESOL Language & Technology Research Group <https://sites.google.com/tc.columbia.edu/al-tesol-language-technology/home> *Latest Publications* Voss, E. (2023). Proctoring remote language assessments <https://www.routledge.com/Fundamental-Considerations-in-Technology-Mediated…>. (Ch. 12) Routledge. TC Interview: How New Artificial Intelligence Tools Will Keep Changing Education <https://youtu.be/Zh1RB7DLRMI?si=vDIvowSnzrWy480P>(7:28 mins.) Voss, E. et al. (2023). The use of assistive technologies including generative AI by test takers in language assessment: A debate of theory and practice. <https://doi.org/10.1080/15434303.2023.2288256> LAQ Journal

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[CFP] Deadline Extension - NLDB 2024 - The 29th International Conference on Natural Language & Information Systems [CFP]
by Federico Torrielli 15 Mar '24

15 Mar '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/ =============== SUBMISSIONS ARE OPEN AT https://easychair.org/conferences/?conf=nldb2024 =============== 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*5 April, 2024 (Extended)* 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 Models and 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. *Student Registration*: We are committed to fostering the participation of young researchers and students in the NLDB 2024 conference. To accommodate as many young minds as possible, we have reduced the student registration fees. We believe that this will provide an excellent opportunity for students to engage with the latest research and industrial applications of Natural Language Processing across information systems. Important Dates: *Full paper submission: *22 March*5 April, 2024 (Extended)* Paper notification: 3 May, 2024 Camera-ready deadline: 10 May, 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 (https://easychair.org/conferences/?conf=nldb2024) 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 program 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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[CFP] Joint Workshop of the 8th Financial Technology and Natural Language Processing (FinNLP) and the 1st Agent AI for Scenario Planning (AgentScen)
by CHUNG-CHI CHEN 15 Mar '24

15 Mar '24

Dear Colleagues, We are excited to announce that the upcoming FinNLP event will be held in conjunction with IJCAI-2024 in Jeju, South Korea, from August 3rd to 9th. This year, we host a Joint Workshop of the 8th Financial Technology and Natural Language Processing (FinNLP) and the 1st Agent AI for Scenario Planning (AgentScen). For our main track, we are inviting submissions for both long and short papers, as well as demonstrations. The submission deadline is April 26th, 2024. Additionally, this year, we are featuring three shared tasks: 1. Multiple Question Generation from Presentation Transcripts (MQG), 2. Forward-Looking Document Comment Generation (DCG), 3. LLM Evaluation in the Financial Sector (FinLLM). For more information and updates, kindly visit our website at https://sites.google.com/nlg.csie.ntu.edu.tw/finnlp-agentscen/home Looking forward to your contributions and participation. Warm regards, Chung-Chi Chen, Tatsuya Ishigaki, Hiroya Takamura, Akihiko Murai, Ryoko Nishino, Hen-Hsen Huang, Hsin-Hsi Chen FinNLP-AgentScen Organizers ----- We understand that some of you may be subscribed to multiple lists and could receive this message more than once. We apologize for any inconvenience this may cause and appreciate your understanding as we strive to keep our community well-informed.

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100 open positions for doctoral researchers in AI at Finnish Universities
by Tiedemann, Jörg 14 Mar '24

14 Mar '24

Call for Doctoral Students in Artificial Intelligence The Finnish Doctoral Program Network in Artificial Intelligence is looking for 100 new PhD students to work in fundamental AI and machine learning research and in five application areas. Come do a PhD tackling challenging research questions in a network that fosters industry and multidisciplinary collaboration! * Call website: https://fcai.fi/doctoral-program * Deadline: April 2, 2024 JOB DETAILS The positions are based at one of the ten universities<https://fcai.fi/doctoral-program#offer> that are part of the Finnish Doctoral Program Network in Artificial Intelligence. The recruiting university will be the same as that of the primary supervisor. The matching of the candidates with supervisors will be done during the review process and the candidates will have a chance to prioritise the supervising professor they want to work with (see details in FAQ<https://fcai.fi/doctoral-program#faq>). All positions are fully-funded. PhD student contracts will be made for three years. The terms of employment and the salaries are based on the General Collective Agreement for Universities<https://www.sivista.fi/wp-content/uploads/2023/08/Yo-tes-1.4.2023-31.5.2025…>. The contract includes occupational healthcare. We are looking for 100 new PhD students in two calls (in spring and fall 2024). The accepted candidates of the spring call are expected to start in August 2024, and the applicants from the fall call in January 2025. HOW TO APPLY We are looking for 100 new PhD students to join the Finnish Doctoral Program Network in Artificial Intelligence in two calls: the first one is open March 11–April 2, 2024 and the second will open in fall 2024. Candidates will apply to all universities and application areas with the same joint application. In the application form, you are able to indicate which specific research areas and supervisors you are interested in. Note: Candidates who apply to supervisors based at the University of Helsinki, will have to submit a parallel application to the university’s own recruitment system. Please note that the application needs to be submitted to both of the recruitment systems to ensure a proper review. See further details<https://www.helsinki.fi/en/research/doctoral-school/doctoral-education-pilot>. The deadline for applications in the ongoing call is April 2, 2024. Please submit your application in our online recruitment system<https://aalto.wd3.myworkdayjobs.com/aalto/login?redirect=%2Faalto%2Fjob%2FO…> with the required attachments (detailed below). Required attachments: 1. Motivation letter (1–2 pages). Please specify the research area(s) and preferably the supervisors with whom you want to work. 2. CV 3. List of publications (if relevant; please do not attach full copies of publications) 4. A transcript of master’s/bachelor’s studies and the degree certificate of your latest degree. If you don’t have a Master's degree, a plan of completion must be submitted. In the application form, you are also asked to provide contact details of two senior academics who can provide references. All materials should be submitted in English in a PDF format. Note: You can upload max. five files to the recruitment system, each max. 5MB. RESEARCH AREAS FUNDAMENTAL AI Fundamental AI methods are the core of the FCAI research activities and the cornerstone in all application areas. Fundamental AI encompasses probabilistic AI for verifiable and uncertainty-aware model building, simulation-based inference for efficient and interpretable reasoning capabilities, data-efficient deep learning, privacy-preserving and secure AI, interactive AI for collaborative AI tools, autonomous AI, statistics, and decision-making. Widely applicable goals of the fundamental AI are AI-assisted decision-making, design and modeling. Keywords: Artificial Intelligence, Causal Inference, Collaborative AI and human modeling, Machine Learning, Statistics AI IN LANGUAGE AND SPEECH TECHNOLOGY The area covers all aspects of natural language processing (NLP), a field of research dealing with computational analysis and generation of human language. NLP is a broad field which spans from highly technical research on machine learning techniques for written and spoken language data, through the myriad of individual tasks such as machine translation and information retrieval, to digital linguistics. The field is reliant on very large datasets and high performance computing, offering exciting software engineering and algorithmic challenges. Finland has a long tradition of top-notch NLP research, especially in the multilingual setting and, recently, large language model development. Keywords: Foundation models, Human language technology, Natural Language Processing, NLP, Large language models, Speech recognition, Speech generation, Machine translation, Crosslingual models AI IN COMMUNICATIONS AND SIGNAL PROCESSING The area covers a wide range of advanced methods in communications and distributed intelligence technologies, statistical methods in signal processing, and analysis of images, video, speech, audio and array signals. The methodologies can be applied in various layers of communications systems from applications to the radio connectivity with distributed intelligence that is an integral part of next generation communication and computing systems targeting to solve issues related to ultra densification of infrastructure, devices and people, and to guarantee secure, low latency and reliable use of ICT resources using advanced AI methods. This research area also includes acquiring, processing, analyzing and understanding digital images, video sequences, views from multiple cameras, multi-dimensional data from a 3D scanner, 3D point clouds from LiDaR sensors, or medical scanning devices, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions, using models constructed with the aid of geometry, physics, statistics, and learning theory. Keywords: Array signal processing, Computer vision, Edge intelligence, Perception, Sensors, Wireless communications AI IN HEALTH The health and wellbeing field holds high potential to profit from advances in AI. Applications range from personalized care and precision medicine to preventive care and to process optimization. Increasing availability of large amounts of multi-source data combined with novel AI paradigms give huge opportunities. Challenges are how to extract valid actionable knowledge from all that data, how to develop AI-based solutions that are trustworthy, fit into healthcare processes, and that have an actual impact. Keywords: Biomedical Image and Signal analysis; Multi-modal Health Data Analysis; Predictive, Preventive, Personalized, Participatory Healthcare, Trustworthy AI, Healthcare Processes AI IN ENGINEERING Industries are currently employing AI methods in numerous research and development tasks. Examples include product design, predictive maintenance, and combining physical models with data-based methods. There is a great potential also in replacing laboratory development and experiments with virtual laboratory-type approaches. Research topics include: * AI methods in industrial research and development, including: * AI for product design and optimization, combining physic-based and data-driven models. * AI for improving industrial operations: cyber security, anomaly detection in industrial time series and predictive maintenance. * Methods supporting AI in industrial deployments, including on-device learning and federated learning on edge devices. * Virtual laboratories for experimentation and cost-effective product design and validation. * AI methods for autonomous functions in land, sea, air and space vehicles and machines. These range from pilot assistance, collision avoidance and navigation systems to full-mission autopilots. Keywords: Autonomous systems, Energy systems, Machine automation, Manufacturing, Materials, Mechanical engineering, Robotics AI IN SOCIETY AND BUSINESS The area examines the societal, ethical, and economic dimensions of AI, including trustworthy and societally acceptable AI as well as the consequences of the uses of AI. It brings together AI research with social sciences and humanities to gain in-depth understanding of AI’s role in organizations, society, business, and the economy. It includes uses of AI in education and education about AI. The area fosters interdisciplinarity to reinforce cross-cutting themes such as sustainability, ethics, equity, trust, and social responsibility. Keywords: AI in business operations, AI in society, AI and Education, AI Ethics -- ***************************************************************** Jörg Tiedemann Language Technology https://blogs.helsinki.fi/language-technology/ University of Helsinki

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