November 2023 - Corpora

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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Workshop on the Scaling Behavior of Large Language Models
by Shay Cohen 24 Nov '23

24 Nov '23

(Apologies for cross-posting) Second Call for Papers for the WORKSHOP ON THE SCALING BEHAVIOR OF LARGE LANGUAGE MODELS (SCALE-LLM 2024) https://scale-llm-24.pages.dev/ [1] Submission deadline: December 18, 2023. The purpose of the SCALE-LLM workshop is to provide a venue to share and discuss results of investigations into the scaling behavior of Large Language Models (LLMs). We are particularly interested in results displaying "interesting" scaling curves (e.g., inverse, u-shaped, or inverse u-shaped scaling curves) for a variety of tasks. These results, where the performance of the LLMs decreases with increasing model size or follows a non-monotonic trend, deviating from the expected "the bigger, the better" positive scaling laws, are of great scientific interest as they can reveal intrinsic limitations of current LLM architectures and training paradigms and they provide novel research directions towards a better understanding of these models and of possible approaches to improve them. Recently, there has been an increasing interest in these phenomena from the research community, culminating in the Inverse Scaling Prize (McKenzie et al. 2023), which solicited tasks to be systematically evaluated according to a standardized protocol in order to perform a systematic study. The SCALE-LLM Workshop will expand these efforts. In contrast to the Inverse Scaling Prize, which focused on zero-shot tasks with a fixed format, we are also interested in, for example, few-shot and alternate prompting strategies (e.g. Chain-of-Thoughts), multi-step interactions (e.g. Tree-of-Thoughts, self-critique), hardening against prompt injection attacks (e.g. user input escaping, canary tokens), etc. MAIN TOPICS The workshop will provide focused discussions on multiple topics in the general field of Scaling behavior of Large Language Models, including, but not limited to the following: 1. Novel tasks that exhibit Inverse, U-shaped, Inverse U-shaped or other types of scaling; 2. Scaling behavior of fine-tuned or purpose-built models, in particular in-distribution (w.r.t. the fine-tuning dataset) vs. out-of-distribution; 3. Scaling with adaptive prompting strategies, e.g. allowing intermediate reasoning steps, model self-critique or use of external tools; 4. Scaling w.r.t. additional dimensions, such as the number of in-context/fine-tuning examples, the number of easoning steps, or the intrinsic task complexity; 5. Scaling on non-English language tasks, in particular low-resource languages, where models might exhibit tradeoffs as high-resource language training data overwhelms low-resource language capabilities; 6. Scaling w.r.t. qualitative characteristics: internal aspects (e.g. modularity, mechanistic interpretability), calibration, uncertainty, effectiveness of various techniques (pruning, defences against adversarial attacks, etc.). IMPORTANT DATES - Workshop paper submission deadline: December 18, 2023 - EACL rejected paper submission deadline (ARR pre-reviewed): January 17, 2024 - Notification of acceptance: January 20, 2024 - Camera-ready papers due: January 30 2024 - Workshop dates: March 21 or 22, 2024 SUBMISSION INSTRUCTIONS We solicit short and long paper submissions with no more than 4 and 8 pages, respectively, plus unlimited pages for references and appendices. Papers must contain "Limitations" and "Ethics Statement" sections which will not count towards the page limit. Upon acceptance, one additional page will be provided to address the reviewers' comments. Paper submissions must use the official ACL style templates (https://github.com/acl-org/acl-style-files [2]) and must follow the ACL formatting guidelines (https://acl-org.github.io/ACLPUB/formatting.html [3]). All submissions must be anonymous. De-anonymized versions of the submitted papers may be released on pre-print servers such as arXiv, however, we kindly ask the authors not discuss these papers on social media during the review period. Please, send your submissions to our OpenReview interface: https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/SCALE-LLM [4] We can also consider papers submitted via ACL Rolling Reviews (ARR) to EACL and rejected. A paper may not be simultaneously under review through ARR and SCALE-LLM. A paper that has or will receive reviews through ARR may not be submitted for review to SCALE-LLM. Keep in mind that ARR has stricter anonymity requirements regarding pre-print servers and social media, so make sure you do not de-anonymize papers submitted through ARR by posting them on arXiv or social media. Please refer to the ARR instructions for autors (https://aclrollingreview.org/authors [5]) for more information. STUDENT SCHOLARSHIP Thanks to our Platinum sponsor Google, we can offer financial support to a limited number of students from low-income countries or other disadvantaged financial situation who would like to participate to the SCALE-LLM workshop. We may able to cover the EACL virtual conference registration fee. We will prioritize students who are authors of one of the accepted papers. If you are interested in receiving financial support, please contact us before January 30 2024, explaning your situation. INVITED SPEAKERS Najoung Kim will give a keynote talk. Dr. Kim is an Assistant Professor at Boston University and a researcher at Google. She is one of the authors of the Inverse Scaling Prize paper as well as other foundational works in this field. Additional speakers will be announced at a later date. SCHEDULE To be decided. ORGANIZING COMMITTEE - Antonio Valerio Miceli-Barone, Research Associate, University of Edinburgh - Fazl Barez, Research fellow, University of Oxford - Shay Cohen, Reader, University of Edinburgh - Elena Voita, Research Scientist, Meta - Ulrich Germann, Senior Computing Officer (Research), University of Edinburgh - Michal Lukasik, Researcher, Google Research CONTACTS Workshop website: https://scale-llm-24.pages.dev/ [6] Email: amiceli [at] ed.ac.uk Best Regards, The SCALE-LLM organizers Antonio Valerio Miceli-Barone, Fazl Barez, Shay Cohen, Elena Voita, Ulrich Germann, Michal Lukasik Read more: https://www.aclweb.org/portal/content/workshop-scaling-behavior-large-langu… [1] https://scale-llm-24.pages.dev/ [2] https://github.com/acl-org/acl-style-files [3] https://acl-org.github.io/ACLPUB/formatting.html [4] https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/SCALE-LLM [5] https://aclrollingreview.org/authors [6] https://scale-llm-24.pages.dev/ The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336. Is e buidheann carthannais a th’ ann an Oilthigh Dhùn Èideann, clàraichte an Alba, àireamh clàraidh SC005336.

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36th International Conference on Advanced Information Systems Engineering (CAiSE 2024): Final Call for Papers
by Announce 24 Nov '23

24 Nov '23

*** Final Call for Papers *** 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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Call for Participation - ArabicNLP 2023
by Salam Khalifa 23 Nov '23

23 Nov '23

Hello All, **Apologies for cross-posting** We are happy to invite you to the first ArabicNLP 2023 conference, the successor of the long-standing Workshop of Arabic Natural Language Processing (WANLP). The conference will take place in Singapore on the 7th of December 2023, co-located with EMNLP 2023. For this year’s edition of ArabicNLP, we received a total of 80 main conference submissions and accepted 38 papers (32 long and 6 short), which brings us to an acceptance rate of 47.5%. ArabicNLP 2023 included five shared tasks with 48 submissions in total: (i) The Nuanced Arabic Dialect Identification (NADI), (ii) ArAIEval (Persuasion Techniques and Disinformation Detection in Arabic Text), (iii) Qur’an QA, (iv) WojoodNER, and (v) Arabic Reverse Dictionary. ArabicNLP 2023 will also include a panel discussing the hot topic “Arabic LLMs: Challenges and Opportunities” by leaders in the field, like Areeb Alowisheq, Kareem Darwish, and Preslav Nakov, moderated by Mona Diab. To view the program and the full list of accepted papers, visit: https://arabicnlp2023.sigarab.org/program. The ArabicNLP 2023 conference is held in hybrid mode, and we look forward to seeing you soon! For registration information, visit: https://arabicnlp2023.sigarab.org/registration Lastly, we thank all our sponsors: King Salman Global Academy for Arabic Language, aiXplain, Lisan.ai, SCAI, Majarra, and Big IR, for their generous support and help building up the Arabic NLP community. Best Regards, ArabicNLP 2023's publicity chairs -- Salam Khalifa PhD Student at Stony Brook Linguistics <https://www.linguistics.stonybrook.edu/>.

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Postdoc position in L3i La Rochelle - Emotion detection in comics speech balloons
by Antoine Doucet 23 Nov '23

23 Nov '23

--------------------------------------------------------------------------------------------------------------------------- *-- Post-doctoral research position - L3i - La Rochelle France* --------------------------------------------------------------------------------------------------------------------------- *Title :*Emotion detection by semantic analysis of the text in comics speech balloons The L3i laboratory has one open post-doc position in computer science, in the specific field of natural language processing in the context of digitised documents. *Duration*: 12 months (an extension of 12 months will be possible) *Position available from*: as soon as possible *Salary*: approximately 2100 € / month (net) *Place*: L3i lab, University of La Rochelle, France *Specialty*: Computer Science/ Document Analysis/ Natural Language Processing *Contact*: Jean-Christophe BURIE (jcburie [at] univ-lr.fr) / Antoine Doucet (antoine.doucet [at] univ-lr.fr) ** *Position Description* The L3i is a research lab of the University of La Rochelle. La Rochelle is a city in the south west of France on the Atlantic coast and is one of the most attractive and dynamic cities in France. The L3i works since several years on document analysis and has developed a well-known expertise in ‘Bande dessinée”, manga and comics analysis, indexing and understanding. The work done by the post-doc will take part in the context of *SAiL* (Sequential Art Image Laboratory) a joint laboratory involving L3i and a private company. The objective is to create innovative tools to index and interact with digitised comics. The work will be done in a team of 10 researchers and engineers. The team has developed different methods to extract and recognise the text of the speech balloons. The specific task of the recruited researcher will be to use Natural Language Processing strategies to analyse the text in order to identify emotions expressed by a character (reacting to the utterance of another speaking character) or caused by it (talking to another character). The datasets will be collections of comics in French and English. *Qualifications* Candidates must have a completed PhD and a research experience *in natural language processing*. Some knowledge and experience in deep learning is also recommended. *General Qualifications* • Good programming skills mastering at least one programming language like Python, Java, C/C++ • Good teamwork skills • Good writing skills and proficiency in written and spoken English or French *Applications* Candidates should send a CV and a motivation letter to jcburie [at] univ-lr.fr and antoine.doucet [at] univ-lr.fr.

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