October 2023 - Corpora

NLP4CALL 2023 Final call for papers
by David Alfter 18 Mar '24

18 Mar '24

== 12th NLP4CALL, Tórshavn, Faroe Islands== The workshop series on Natural Language Processing (NLP) for Computer-Assisted Language Learning (NLP4CALL) is a meeting place for researchers working on the integration of Natural Language Processing and Speech Technologies in CALL systems and exploring the theoretical and methodological issues arising in this connection. The latter includes, among others, insights from Second Language Acquisition (SLA) research, on the one hand, and promote development of “Computational SLA” through setting up Second Language research infrastructure(s), on the other. The intersection of Natural Language Processing (or Language Technology / Computational Linguistics) and Speech Technology with Computer-Assisted Language Learning (CALL) brings “understanding” of language to CALL tools, thus making CALL intelligent. This fact has given the name for this area of research – Intelligent CALL, ICALL. As the definition suggests, apart from having excellent knowledge of Natural Language Processing and/or Speech Technology, ICALL researchers need good insights into second language acquisition theories and practices, as well as knowledge of second language pedagogy and didactics. This workshop invites therefore a wide range of ICALL-relevant research, including studies where NLP-enriched tools are used for testing SLA and pedagogical theories, and vice versa, where SLA theories, pedagogical practices or empirical data are modeled in ICALL tools. The NLP4CALL workshop series is aimed at bringing together competences from these areas for sharing experiences and brainstorming around the future of the field. We welcome papers: - that describe research directly aimed at ICALL; - that demonstrate actual or discuss the potential use of existing Language and Speech Technologies or resources for language learning; - that describe the ongoing development of resources and tools with potential usage in ICALL, either directly in interactive applications, or indirectly in materials, application or curriculum development, e.g. learning material generation, assessment of learner texts and responses, individualized learning solutions, provision of feedback; - that discuss challenges and/or research agenda for ICALL - that describe empirical studies on language learner data. This year a special focus is given to work done on error detection/correction and feedback generation. We encourage paper presentations and software demonstrations describing the above- mentioned themes primarily, but not exclusively, for the Nordic languages. ==Shared task== NEW for this year is the MultiGED shared task on token-level error detection for L2 Czech, English, German, Italian and Swedish, organized by the Computational SLA working group. For more information, please see the Shared Task website: https://github.com/spraakbanken/multiged-2023 ==Invited speakers== This year, we have the pleasure to announce two invited talks. The first talk is given by Marije Michel from the University of Amsterdam. The second talk is given by Pierre Lison from the Norwegian Computing Center. ==Submission information== Authors are invited to submit long papers (8-12 pages) alternatively short papers (4-7 pages), page count not including references. We will be using the NLP4CALL template for the workshop this year. The author kit can be accessed here, alternatively on Overleaf: <https://spraakbanken.gu.se/sites/default/files/2023/NLP4CALL%20workshop%20t…> <https://spraakbanken.gu.se/sites/default/files/2023/nlp4call%20template.doc> <https://www.overleaf.com/latex/templates/nlp4call-workshop-template/qqqzqqy…> Submissions will be managed through the electronic conference management system EasyChair <https://easychair.org/conferences/?conf=nlp4call2023>. Papers must be submitted digitally through the conference management system, in PDF format. Final camera-ready versions of accepted papers will be given an additional page to address reviewer comments. Papers should describe original unpublished work or work-in-progress. Papers will be peer reviewed by at least two members of the program committee in a double-blind fashion. All accepted papers will be collected into a proceedings volume to be submitted for publication in the NEALT Proceeding Series (Linköping Electronic Conference Proceedings) and, additionally, double-published through the ACL anthology, following experiences from the previous NLP4CALL editions (<https://www.aclweb.org/anthology/venues/nlp4call/>). ==Important dates== 03 April 2023: paper submission deadline 21 April 2023: notification of acceptance 01 May 2023: camera-ready papers for publication 22 May 2023: workshop date ==Organizers== David Alfter (1), Elena Volodina (2), Thomas François (3), Arne Jönsson (4), Evelina Rennes (4) (1) Gothenburg Research Infrastructure for Digital Humanities, Department of Literature, History of Ideas, and Religion, University of Gothenburg, Sweden (2) Språkbanken, Department of Swedish, Multilingualism, Language Technology, University of Gothenburg, Sweden (3) CENTAL, Institute for Language and Communication, Université Catholique de Louvain, Belgium (4) Department of Computer and Information Science, Linköping University, Sweden ==Contact== For any questions, please contact David Alfter, david.alfter(a)gu.se For further information, see the workshop website <https://spraakbanken.gu.se/en/research/themes/icall/nlp4call-workshop-serie…> Follow us on Twitter @NLP4CALL <https://twitter.com/NLP4CALL/>

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1st CfP: Asia Pacific Journal of Corpus Research (APJCR) Vol. 4, No. 2 (Deadline: 15 October 2023)
by Prof CK Jung 21 Jan '24

21 Jan '24

[Apologies for cross-posting] Dear colleagues We are inviting submissions for the next issue of Asia Pacific Journal of Corpus Research, to appear on 31 December 2023. *ABOUT*The Asia Pacific Journal of Corpus Research (APJCR, e-ISSN 2733-8096, DOI: https://doi.org/10.22925/apjcr) is an international and interdisciplinary peer-reviewed journal intended to explore corpus research in the Asia Pacific region. APJCR addresses areas of methodological, applied and theoretical work in the field of corpus research. Examples of such include discourse analysis, lexical studies, grammatical studies, language acquisition, language learning, language education, lexicography, pragmatics, sociolinguistics, (machine) translation studies, (digital) literary studies, computational linguistics, speech, phonetics, deep learning and natural language understanding in conjunction with corpus. *NO ARTICLE PROCESS CHARGE*APJCR does not charge authors an Article Processing Fee (APF). *OPEN ACCESS POLICY*APJCR provides open access to its content under the principle in the academic field that making research freely available to the public supports a greater global exchange of knowledge. *SUBMISSION* Papers (in English or Korean) should be sent to *apjcreditor(a)icr.or.kr <apjcreditor(a)icr.or.kr>* *Full instruction can be found on http://icr.or.kr/apjcr <http://icr.or.kr/apjcr>* *IMPORTANT DATES*- Manuscript submission: 15 October 2023 - First decision (articles assessed by editors): October 2023 - Final decision: November 2023 - Production: December 2023 - Online publication: 31 December 2023 *APJCR ARCHIVE*- Google Scholar: https://scholar.google.co.kr/scholar?hl=ko&as_sdt=0%2C5&q=apjcr&btnG= - KoreaScience: http://koreascience.or.kr/journal/CPSOBX/v1n1.page *ENQUIRIES* help(a)icr.or.kr --- *CK Jung BEng(Hons) Birmingham MSc Warwick EdD Warwick Cert Oxford* Associate Professor | Department of English Language and Literature, Incheon National University, *South Korea* President | The Korea Association of Secondary English Education, *South Korea *(http://kasee.org) Vice President | The Korea Association of Primary English Education), *South Korea *(http://kapee.or.kr) Director | Institute for Corpus Research, Incheon National University, *South Korea* (http://icr.or.kr) Editor-in-Chief | Asia Pacific Journal of Corpus Research, ICR, *International* (http://icr.or.kr/apjcr) Editorial Board | Corpora, Edinburgh University Press, *UK* Editorial Board | English Today, Cambridge University Press, *UK* E: ckjung(a)inu.ac.kr / T: +82 (0)32 835 8129

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Asia Pacific Journal of Corpus Research (APJCR) Vol. 4, No. 1 is now available online
by Prof CK Jung 31 Dec '23

31 Dec '23

*Asia Pacific Journal of Corpus Research (APJCR) is now available online:* http://icr.or.kr/ejournals-apjcr *The Incredible Shrinking Noun Phrase: Ongoing Change in Japanese Word Formation*Kevin Heffernan, (Kwansei Gakuin University), JAPAN; Yusuke Imanishi (Kwansei Gakuin University), JAPAN DOI: https://doi.org/10.22925/apjcr.2023.4.1.1 ________________________________________ *Identifying Key Grammatical Errors of Japanese English as a Foreign Language Learners in a Learner Corpus: Toward Focused Grammar Instruction with Data-Driven Learning* Atsushi Mizumoto (Kansai University), JAPAN; Yoichi Watari (Chukyo University), JAPAN DOI: https://doi.org/10.22925/apjcr.2023.4.1.25 ________________________________________ *A Comparison of the Constructions Make / Take a Decision in Malaysian English with the Supervarieties * Christina Sook Beng Ong (Wawasan Open University), MALAYSIA DOI: https://doi.org/10.22925/apjcr.2023.4.1.43 ________________________________________ *Effects of Corpus Use on Error Identification in L2 Writing * Yoshiho Satake (Aoyama Gakuin University), JAPAN DOI: https://doi.org/10.22925/apjcr.2023.4.1.61 --- *CK Jung BEng(Hons) Birmingham MSc Warwick EdD Warwick Cert Oxford* Associate Professor | Department of English Language and Literature, Incheon National University, *South Korea* President | The Korea Association of Secondary English Education, *South Korea *(http://kasee.org) Vice President | The Korea Association of Primary English Education), *South Korea *(http://kapee.or.kr) Director | Institute for Corpus Research, Incheon National University, *South Korea* (http://icr.or.kr) Editor-in-Chief | Asia Pacific Journal of Corpus Research, ICR, *International* (http://icr.or.kr/apjcr) Editorial Board | Corpora, Edinburgh University Press, *UK* Editorial Board | English Today, Cambridge University Press, *UK* E: ckjung(a)inu.ac.kr / T: +82 (0)32 835 8129 H(EN): http://ckjung.org

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CfP: Workshop on Unpacking Efficient Communication
by Gemma Boleda 18 Dec '23

18 Dec '23

Call for Papers 2024 CORE Project Workshop Unpacking Efficient Communication: The Roles of Cognitive Bias and Extralinguistic Context in Referring Expression Choice When: April 18-19, 2024 Where: Universitat Pompeu Fabra, Barcelona Language offers a rich set of lexical and syntactic options for reference, reflecting the different ways we can choose to identify, describe, categorize, and differentiate the entities and events we talk about. For example, in any given context, a speaker can choose between a more or less specific expression (the dog, the spotted dog, the Dalmatian), or between expressions that convey complementary information about the referent (the woman, the skier). A well-established line of research highlights the role of efficiency in referring expression choice. But what makes a referring expression “efficient”? Efficiency in communication has been frequently characterized in terms of an informativity/effort trade-off, with informativity operationalized in terms of inference, and effort, in terms of cognitive or physical cost (Horn 1984, Levshina 2021). However, there is also evidence that other factors such as the salience of visual features (e.g., color, Rubio-Fernández 2016) or the prototypicality of an entity as an exemplar of a category (see, e.g., Degen, et al. 2020) can lead speakers to use expressions that are, strictly speaking, overinformative in the narrowest sense of the term. Efficiency can also be examined at the level of the whole system; for instance, Brochhagen and Boleda (2022) argue that the informativity/effort trade-off helps explain cross-linguistic patterns in colexification, or how meanings are organized in the lexicon. The goal of this workshop, supported by the Spanish AEI-funded CORE project (“COntextual effects in the choice of Referring Expressions for visually presented entities”, PID2020-112602GB-I00), is to dig deeper into what makes a linguistic expression “efficient”, considering factors such as: - Cognitive biases that influence the potential for rapid/efficient discrimination. - Potential for exploiting inferences due to choice of one expression vs. another. - Information load a referring expression has to bear given extralinguistic sources of information in the context, especially visual information. - Lexical/constructional frequency effects and association strength between RE options and the referent in question. The workshop aims to give a forum to new and especially exploratory research in this area. The workshop will include a combination of invited talks, presentations of ongoing research by project members, and presentations and/or posters selected in this open call. We invite submissions on topics including, but not limited to: - The general principles that intervene in efficient communication, especially alternatives to or refined definitions of notions such as “efficiency”, “effort”, and “informativity”. - Which features of entities or events are more likely to be used for discrimination. - The role of the visual context and/or distractor entities in influencing RE choice; more generally, the role of multi-modal aspects. - The role of the implicit semantic organization of RE alternatives and the conventionalized division of labor between them, especially organization based on implicative semantic relations (e.g. hyponymy, troponymy). - The factors influencing the choice among alternative cross-classifications of a target referent (e.g. the choice between “taxonomic” descriptions such as woman vs. role-based descriptions such as skier). - The dynamics between reference and the linguistic system, that is, how efficient communication is enabled by and at the same time transforms a given language. We take a methodologically pluralistic approach and thus welcome presentations on experimental studies, analysis of corpus data, computational modeling, critiques or analyses of published research, as well as position papers. Invited speakers: Lilia Rissman, University of Wisconsin - Madison Paula Rubio-Fernández, Max Planck Institute for Psycholinguistics Sina Zarrieß, University of Bielefeld Abstract guidelines: Abstracts should not exceed 2 pages in length (A4 or letter-size), in 12 pt. font, with 1-inch/2,5-cm margins; a third page can be used for references, data, and figures. Please indicate whether you want the submission to be considered for a paper, a poster, or either. Abstracts should be submitted to EasyChair at the following link: https://easychair.org/conferences/?conf=core2024. Important dates: Deadline for abstract submission: December 20, 2023 Notification of acceptance: January 15, 2024 Workshop dates: April 18-19, 2024 Organizers: Louise McNally, Gemma Boleda, Jialing Liang, Marina Bolea. References: Degen, J., Hawkins, R. D., Graf, C., Kreiss, E., & Goodman, N. D. (2020). When redundancy is useful: A Bayesian approach to “overinformative” referring expressions. Psychological Review, 127(4), 591–621. Gualdoni, E., T. Brochhagen, A. Mädebach, G. Boleda. 2023. What's in a name? A large-scale computational study on how competition between names affects naming variation. Journal of Memory and Language, 133, 104459. Brochhagen, T., G. Boleda. 2022. When do languages use the same word for different meanings? The Goldilocks Principle in colexification. Cognition, 226, 105179. Horn, L.R. (1984). Towards a new taxonomy for pragmatic inference: Q-based and R-based implicature. In Schiffrin, D. (ed.), Meaning, Form, and Use in Context: Linguistic Applications, 11-42. Georgetown University Press, Washington, DC. Levshina, N. (2023). Communicative efficiency: Language structure and use. Cambridge: Cambridge University Press. Rissman, L., & Lupyan, G. (2022). A Dissociation Between Conceptual Prominence and Explicit Category Learning: Evidence From Agent and Patient Event Roles. Journal of Experimental Psychology: General, 151(7):1707-1732. Rubio-Fernandez, P., Mollica, F., & Jara-Ettinger, J. (2021). Speakers and listeners exploit word order for communicative efficiency: A cross-linguistic investigation. Journal of Experimental Psychology: General, 150(3), 583–594. Schüz, S., Han, T., Zarrieß, S. (2021) Diversity as a By-Product: Goal-oriented Language Generation Leads to Linguistic Variation. Proceedings of the 22nd Annual SIGdial Meeting on Discourse and Dialogue. Association for Computational Linguistics.

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First CfP: MOOMIN @ EACL 2024 - the first workshop on Modular and Open Multilingual NLP
by Tiedemann, Jörg 17 Dec '23

17 Dec '23

First Call for papers: MOOMIN (the first workshop on Modular and Open Multilingual NLP) collocated with EACL 2024, March 21 or 22, 2024 Website: https://moomin-workshop.github.io/ Submission website: https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/MOOMIN We invite submissions to the first edition of the MOOMIN workshop on Modular and Open Multilingual NLP, to be held at EACL 2024 on March 21 or 22, 2024. [Important Dates] * Workshop paper due: December 18, 2023 * Resubmission deadline (for pre-reviewed ARR & main conference submissions): January 17, 2024 * Notification of acceptance: January 20, 2024 * Camera-ready papers due: January 30 2024 * Workshop dates: March 21-22, 2024 [Introduction] NLP in the age of monolithic large language models starts to hit the limits in terms of size and information that can be handled. The trend goes to modularization, a necessary step into the direction of designing smaller sub-networks and components with specialized functionality. This allows researchers to design scalable, wide-coverage, efficient and reusable models. Multilingual NLP is today faced with a number of difficult challenges. Scaling a multilingual model to a high number of languages is prone to suffer from negative interference, also known as the curse of multilinguality, leading to degradation in per-language performance, while earlier approaches to improving model capacity have hit the ceiling in terms of hardware, data and training algorithms. At the same time, we as a community wish to foster the development of open components that can be shared, deployed and widely integrated within the broader research community without incurring computational costs that add to the overall carbon footprint of NLP engineering. Modularity is a practical solution to answer all of these challenges and more, as it offers a very promising set of tools towards increased multilinguality of larger foundation models, either during their pretraining or in a post-hoc post-pretraining manner. [Topics of Interest] With this in mind, the MOOMIN workshop invites contributions related but not limited to the following topics: * mixture of expert models and gated routing * modular pre-training of multilingual language and translation models * effective transfer with modular architectures such as adapters and hypernetworks * efficient parallelization and distribution of modular model training * modular frameworks and architecture implementations * massively multilingual models with large language coverage * subnet selection and pruning * modular distillation * modular extensions of existing NLP models systems, especially in low-resource settings and for low-resource languages * evaluation of modular systems in terms of performance, efficiency, and computational costs * platforms for distributing, sharing, and integrating NLP components [Submission Guidelines] Authors are invited to submit original and unpublished research papers in the following categories: * Full papers (up to 8 pages) for substantial contributions. * Short papers (up to 4 pages) for ongoing or preliminary work. All submissions must be in PDF format, submitted electronically via OpenReview (https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/MOOMIN) and should follow the EACL 2024 formatting guidelines (following the ARR CfP<https://aclrollingreview.org/cfp>: use the official ACL style templates, which are available here<https://github.com/acl-org/acl-style-files>). We also intend to invite papers accepted to Findings to reach out to the organizing committee of MOOMIN to present their papers at the workshop, if in line with the topics as described above. [Workshop Organizers] * Timothee Mickus, University of Helsinki * Jörg Tiedemann, University of Helsinki * Ahmet Üstün, Cohere For AI * Raúl Vázquez, University of Helsinki * Ivan Vulić, University of Cambridge & PolyAI [Program Committee] A list of program committee members will be available on the workshop website. [Contact] For inquiries, please contact moomin.nlp.workshop(a)gmail.com<mailto:moomin.nlp.workshop@gmail.com>

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First call for papers: The 9th Workshop on Noisy and User-generated Text (WNUT 2024)
by Rob van der Goot 22 Nov '23

22 Nov '23

The WNUT Workshop will be collocated with EACL 2024 (Malta). The website for the workshop is at: http://noisy-text.github.io/ The WNUT workshop focuses on core NLP tasks (e.g., POS/NER tagging and translation; not computational social science) over user-generated text, such as that found on social media, web forums, online reviews, digital health records, or language learner essays. We seek submissions of long and short papers on original and unpublished work (same format and page limit as EACL main conference). All accepted submissions will be presented as posters. Additionally, selected submissions will be presented orally. There will be best paper awards for both short and long papers. Topics of interest include but are not limited to: * NLP of noisy text, e.g. POS, NER tagging, Parsing * Text normalization and error correction * Paraphrase identification and semantic similarity of short text or noisy text * Extracting user demographics, profiles, and major life events * Machine translation and Multilingual NLP over noisy text * Information extraction from noisy text, global and regional trend detection, and event extraction * Colloquial language, e.g. idiom detection * Domain adaptation to user-generated text * Detecting rumors, contradictory information, sarcasm and humor on social media * Sentiment analysis * Temporal aspects of user-generated content (resolving time expressions, concept drift, etc...) * Representing and mining language variation in user-generated content * Processing of automatically generated data * Robustness to Noise, both Natural and Adversarial [IMPORTANT DATES] * Submission Deadline: December 18, 2023 (anytime on earth; dual-submission allowed) * Acceptance Notification: January 20, 2024 * Camera-Ready Deadline: january 30, 2024 * Workshop Day: March 21/22, 2024 [INVITED SPEAKERS] * Su Lin Blodgett * Jennifer Foster [ORGANIZERS] * Tim Baldwin (University of Melbourne) * Wei Xu (Georgia Institute of Technology) * Alan Ritter (Georgia Institute of Technology) * Rob van der Goot (IT University of Copenhagen) * Max Müller-Eberstein (IT University of Copenhagen) [SUBMISSION] Submissions should conform to the ACL style guidelines. Long and short paper submissions must be anonymized. Please submit your papers via OpenReview: https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/WNUT

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Postdoc position -- multimodal coreference
by Sharid Loáiciga 14 Nov '23

14 Nov '23

We're hiring a postdoc to work on multimodal coreference resolution. The position is at CLASP, University of Gothenburg, Sweden, for 2 years with possibility of 1 year extension. I'm happy to answer questions if you're interested. https://web103.reachmee.com/ext/I005/1035/job?site=7&lang=UK&validator=9b89… Sharid

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3-year PhD position in Automatic Argumentation Mining in French Legal Decisions (Inria Lille, University of Lille, and LexisNexis France)
by Pascal Denis 10 Nov '23

10 Nov '23

Hi there, Could you please distribute the following job offer? Thanks. Best, Pascal ------------------------------------------------------------------------------------- We invite applications for a 3-year PhD position co-funded by Inria, the French national research institute in Computer Science and Applied Mathematics, and LexisNexis France, leader of legal information in France and subsidiary of the RELX Group. The overall objective of this project is to develop an automated system for detecting argumentation structures in French legal decisions, using recent machine learning-based approaches (i.e. deep learning approaches). In the general case, these structures take the form of a directed labeled graph, whose nodes are the elements of the text (propositions or groups of propositions, not necessarily contiguous) which serve as components of the argument, and edges are relations that signal the argumentative connection between them (e.g., support, offensive). By revealing the argumentation structure behind legal decisions, such a system will provide a crucial milestone towards their detailed understanding, their use by legal professionals, and above all contributes to greater transparency of justice. The main challenges and milestones of this project start with the creation and release of a large-scale dataset of French legal decisions annotated with argumentation structures. To minimize the manual annotation effort, we will resort to semi-supervised and transfer learning techniques to leverage existing argument mining corpora, such as the European Court of Human Rights (ECHR) corpus, as well as annotations already started by LexisNexis. Another promising research direction, which is likely to improve over state-of-the-art approaches, is to better model the dependencies between the different sub-tasks (argument span detection, argument typing, etc.) instead of learning these tasks independently. A third research avenue is to find innovative ways to inject the domain knowledge (in particular the rich legal ontology developed by LexisNexis) to enrich enrich the representations used in these models. Finally, we would like to take advantage of other discourse structures, such as coreference and rhetorical relations, conceived as auxiliary tasks in a multi-tasking architecture. The successful candidate holds a Master's degree in computational linguistics, natural language processing, machine learning, ideally with prior experience in legal document processing and discourse processing. Furthermore, the candidate will provide strong programming skills, expertise in machine learning approaches and is eager to work at the interplay between academia and industry. The position is affiliated with the MAGNET [1], a research group at Inria, Lille, which has expertise in Machine Learning and Natural Language Processing, in particular Discourse Processing. The PhD student will also work in close collaboration with the R&D team at LexisNexis France, who will provide their expertise in the legal domain and the data they have collected. Applications will be considered until the position is filled. However, you are encouraged to apply early as we shall start processing the applications as and when they are received. Applications, written in English or French, should include a brief cover letter with research interests and vision, a CV (including your contact address, work experience, publications), and contact information for at least 2 referees. Applications (and questions) should be sent to Pascal Denis (pascal.denis(a)inria.fr). The starting date of the position is 1 November 2022 or soon thereafter, for a total of 3 full years. Best regards, Pascal Denis [1] https://team.inria.fr/magnet/ [2] https://www.lexisnexis.fr/ -- Pascal ---- Pour une évaluation indépendante, transparente et rigoureuse ! Je soutiens la Commission d'Évaluation de l'Inria. ---- +++++++++++++++++++++++++++++++++++++++++++++++ Pascal Denis Equipe MAGNET, INRIA Lille Nord Europe Bâtiment B, Avenue Heloïse Parc scientifique de la Haute Borne 59650 Villeneuve d'Ascq Tel: ++33 3 59 35 87 24 Url: http://researchers.lille.inria.fr/~pdenis/ +++++++++++++++++++++++++++++++++++++++++++++++

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Call for Papers: Special Issue of AI Communications on "Human-Aware AI"
by Loizos Michael 08 Nov '23

08 Nov '23

Dear colleagues, We are inviting contributions to the Special Issue of AI Communications on "Human-Aware AI". Contributions are sought that report on mature and highly interdisciplinary research with a focus on the human involvement in the development of meaningful paradigms of AI-enabled human-human interactions, human-AI interactions, and human-centered AI-AI interactions. An indicative list of disciplines and sub-disciplines that we expect to be relevant are: Autonomous Agents and Multi-Agent Systems, Ethics, Human-Computer Interaction, Knowledge Representation and Reasoning, Machine Learning, Ontologies, Privacy, Social Computing, Social Psychology, Social Sciences. Any contribution relating to the general theme is welcome. The following is a non-exhaustive list of suggested topics: • Models of human diversity and human awareness • Models of AI diversity and human-aware AI • Perception of diversity versus models of diversity • Models of diverse human-AI societies and interactions • Experimental studies on human and social diversity • Experimental studies on hybrid human-AI diversity • Representation and visualization of diversity • Incentive models for Human-AI collaboration • Human-aware machine learning technologies • Interpretability and explainability of human-aware machine learning • Diversification and unbiasing of machine learning • Metrics for diversity-aware machine learning • Diversity-aware and diversity-preserving inference and reasoning • Ethical and privacy considerations on diversity • Ethical and legal considerations on diversity-misuse scenarios • Data economics, business models, and/or non-profit use • Insights from Critical Diversity Studies • Diversity-sensitive communication • Content moderation for diversity-aware social interaction More information about the Special Issue can be found here: https://www.iospress.com/sites/default/files/media/files/2023-09/AIC_Human-… The submission deadline is November 30, 2023. However, we would appreciate it if you could register your interest to submit a paper by completing the following form at your earliest convenience: https://forms.gle/vsVjJrCwXE8Nh9YU6 We look forward to your contributions! Regards, Loizos

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Announcing CreoleVal
by Johannes Bjerva 31 Oct '23

31 Oct '23

We are proud to announce the release of CreoleVal - a collection of benchmarks for 28 Creole languages. The collection of datasets span tasks such as relation classification, machine comprehension, machine translation, named entity recognition, and use cases such as language modeling. We cover Haitian Creole, Bislama, Chavacano, Pitkern, Singlish, Tok Pisin, Papiamento, and others. We hope the NLP community will include this collection of datasets in ongoing & future evaluations of methods directed at low-resource languages. Not only that, we also hypothesise that CreoleVal will open the door for controlled experimentation with transfer learning methodology. This resource has been long in the making, and was made possible by a long list of collaborators. For a pre-print, see: https://arxiv.org/abs/2310.19567 For code and data, see: https://github.com/hclent/CreoleVal (Repository under construction)

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