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Call for Papers – Special issue of Information Processing & Management on Large Language Models and Data Quality for Knowledge Graphs
by Stefano Marchesin 14 Apr '24

14 Apr '24

Apologies for crossposting. Call for Papers Information Processing & Management (IPM), Elsevier - CiteScore: 14.8 - Impact Factor: 8.6 Guest editors: - Omar Alonso, Applied Science, Amazon, Palo Alto, California, USA. E-mail: omralon(a)amazon.com - Stefano Marchesin, Department of Information Engineering, University of Padua, Padua, Italy. E-mail: stefano.marchesin(a)unipd.it - Gianmaria Silvello, Department of Information Engineering, University of Padua, Padua, Italy. E-mail: gianmaria.silvello(a)unipd.it Special Issue on “Large Language Models and Data Quality for Knowledge Graphs” In recent years, Knowledge Graphs (KGs), encompassing millions of relational facts, have emerged as central assets to support virtual assistants and search and recommendations on the web. Moreover, KGs are increasingly used by large companies and organizations to organize and comprehend their data, with industry-scale KGs fusing data from various sources for downstream applications. Building KGs involves data management and artificial intelligence areas, such as data integration, cleaning, named entity recognition and disambiguation, relation extraction, and active learning. However, the methods used to build these KGs involve automated components that could be better, resulting in KGs with high sparsity and incorporating several inaccuracies and wrong facts. As a result, evaluating the KG quality plays a significant role, as it serves multiple purposes – e.g., gaining insights into the quality of data, triggering the refinement of the KG construction process, and providing valuable information to downstream applications. In this regard, the information in the KG must be correct to ensure an engaging user experience for entity-oriented services like virtual assistants. Despite its importance, there is little research on data quality and evaluation for KGs at scale. In this context, the rise of Large Language Models (LLMs) opens up unprecedented opportunities – and challenges – to advance KG construction and evaluation, providing an intriguing intersection between human and machine capabilities. On the one hand, integrating LLMs within KG construction systems could trigger the development of more context-aware and adaptive AI systems. At the same time, however, LLMs are known to hallucinate and can thus generate mis/disinformation, which can affect the quality of the resulting KG. In this sense, reliability and credibility components are of paramount importance to manage the hallucinations produced by LLMs and avoid polluting the KG. On the other hand, investigating how to combine LLMs and quality evaluation has excellent potential, as shown by promising results from using LLMs to generate relevance judgments in information retrieval. Thus, this special issue promotes novel research on human-machine collaboration for KG construction and evaluation, fostering the intersection between KGs and LLMs. To this end, we encourage submissions related to using LLMs within KG construction systems, evaluating KG quality, and applying quality control systems to empower KG and LLM interactions on both research- and industrial-oriented scenarios. Topics include but are not limited to: - KG construction systems - Use of LLMs for KG generation - Efficient solutions to deploy LLMs on large-scale KGs - Quality control systems for KG construction - KG versioning and active learning - Human-in-the-loop architectures - Efficient KG quality assessment - Quality assessment over temporal and dynamic KGs - Redundancy and completeness issues - Error detection and correction mechanisms - Benchmarks and Evaluation - Domain-specific applications and challenges - Maintenance of industry-scale KGs - LLM validation via reliable/credible KG data Submission guidelines: Authors are invited to submit original and unpublished papers. All submissions will be peer-reviewed and judged on originality, significance, quality, and relevance to the special issue topics of interest. Submitted papers should not have appeared in or be under consideration for another journal. Papers can be submitted *up *to 1 September 2024. The estimated publication date for the special issue is 15 January 2025. Papers submission via IP&M electronic submission system: https://www.editorialmanager.com/IPM To submit your manuscript to the special issue, please choose the article type: "VSI: LLMs and Data Quality for KGs". More info here: https://www.sciencedirect.com/journal/information-processing-and-management… Instructions for authors: https://www.sciencedirect.com/journal/information-processing-and-management… Important dates: - Submissions close: 1 September 2024 - Publication date (estimated): 15 January 2025 References: Weikum G., Dong X.L., Razniewski S., et al. (2021) Machine knowledge: creation and curation of comprehensive knowledge bases. Found. Trends Databases, 10, 108–490. Hogan A., Blomqvist E., Cochez M. et al. (2021) Knowledge graphs. ACM Comput. Surv., 54, 71:1–71:37. B. Xue and L. Zou. 2023. Knowledge Graph Quality Management: A Comprehensive Survey. IEEE Trans. Knowl. Data Eng. 35, 5 (2023), 4969 – 4988 G. Faggioli, L. Dietz, C. L. A. Clarke, G. Demartini, M. Hagen, C. Hauff, N. Kando, E. Kanoulas, M. Potthast, B. Stein, and H. Wachsmuth. 2023. Perspectives on Large Language Models for Relevance Judgment. In Proc. of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2023, Taipei, Taiwan, 23 July 2023. ACM, 39 – 50. S. MacAvaney and L. Soldaini. 2023. One-Shot Labeling for Automatic Relevance Estimation. In Proc. of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23-27, 2023. ACM, 2230 – 2235. X. L. Dong. 2023. Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact. Proc. VLDB Endow. 16, 12 (2023), 4130 – 4137. S. Pan, L. Luo, Y. Wang, C. Chen, J. Wang, and X. Wu. 2023. Unifying Large Language Models and Knowledge Graphs: A Roadmap. CoRR abs/2306.08302 (2023). -- Stefano Marchesin, PhD Assistant Professor (RTD/a) Information Management Systems (IMS) Group Department of Information Engineering University of Padua Via Gradenigo 6/a, 35131 Padua, Italy Home page: http://www.dei.unipd.it/~marches1/

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CfP: Corpus Approaches to Lexicogrammar
by Costas Gabrielatos 13 Apr '24

13 Apr '24

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

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Job opening in Helsinki: University Lecturer in Humanities Data Science / Computational Humanities
by Tiedemann, Jörg 12 Apr '24

12 Apr '24

The Department of Digital Humanities, Faculty of Arts, University of Helsinki, invites applications for the position of UNIVERSITY LECTURER IN HUMANITIES DATA SCIENCE / COMPUTATIONAL HUMANITIES for a permanent appointment starting 1st of September 2024. https://jobs.helsinki.fi/job/Helsinki-University-Lecturer-in-Humanities-Dat… Due date: April 25, 2024 The position relates to the application of computational and/or statistical methods in the humanities. The application areas are to be interpreted broadly, from area studies to cognitive science, linguistics to history, phonetics to literature. Application, on the other hand, is to be understood primarily from the viewpoint of end-use across this plethora of humanistic research, e.g. through matching approaches to research questions and data, and not as a focus on methodological development itself. The lecturer will be attached to the Liberal Arts and Sciences bachelor’s programme currently under preparation at the university. —————————————— Jörg Tiedemann University of Helsinki https://blogs.helsinki.fi/language-technology/

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[CFP] 2024 SIGIR First Workshop on Large Language Models (LLMs) for Evaluation in Information Retrieval
by Guglielmo Faggioli 12 Apr '24

12 Apr '24

The first workshop on evaluating IR systems with Large Language Models (LLMs) is accepting submissions that describe original research findings, preliminary research results, proposals for new work, and recent relevant studies already published in high-quality venues. Topics of interest We welcome both full papers and extended abstract submissions on the following topics, including but not limited to: - LLM-based evaluation metrics for traditional IR and generative IR. - Agreement between human and LLM labels. - Effectiveness and/or efficiency of LLMs to produce robust relevance labels. - Investigating LLM-based relevance estimators for potential systemic biases. - Automated evaluation of text generation systems. - End-to-end evaluation of Retrieval Augmented Generation systems. - Trustworthiness in the world of LLMs evaluation. - Prompt engineering in LLMs evaluation. - Effectiveness and/or efficiency of LLMs as ranking models. - LLMs in specific IR tasks such as personalized search, conversational search, and multimodal retrieval. - Challenges and future directions in LLM-based IR evaluation. Submission guidelines We welcome the following submissions: - Previously unpublished manuscripts will be accepted as extended abstracts and full papers (any length between 1 - 9 pages) with unlimited references, formatted according to the latest ACM SIG proceedings template available at http://www.acm.org/publications/proceedings-template. - Published manuscripts can be submitted in their original format. All submissions should be made through Easychair: https://easychair.org/conferences/?conf=llm4eval All papers will be peer-reviewed (single-blind) by the program committee and judged by their relevance to the workshop, especially to the main themes identified above, and their potential to generate discussion. For already published studies, the paper can be submitted in the original format. These submissions will be reviewed for their relevance to this workshop. All submissions must be in English (PDF format). All accepted papers will have a poster presentation with a few selected for spotlight talks. Accepted papers may be uploaded to arXiv.org, allowing submission elsewhere as they will be considered non-archival. The workshop’s website will maintain a link to the arXiv versions of the papers. Important Dates - Submission Deadline: April 25th, 2024 (AoE time) - Acceptance Notifications: May 31st, 2024 (AoE time) - Workshop date: July 18, 2024 Website For more information, visit the workshop website: https://llm4eval.github.io/ Contact For any questions about paper submission, you may contact the workshop organizers at llm4eval(a)easychair.org

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PhD Position on Resource-efficient Foundation Models for Automatic Translation at Fondazione Bruno Kessler - Application deadline: *7th of May 2024*
by Matteo Negri 12 Apr '24

12 Apr '24

-- Apologies for cross-posting. -- Have you recently completed or expect very soon an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering, or a related area? Are you interested in carrying out research on automatic translation during the next few years? Are you excited to spend a part of your life in a pleasant city in the heart of the Italian Alps? WE ARE LOOKING FOR YOU!!! The Machine Translation <https://mt.fbk.eu/> (MT) group at Fondazione Bruno Kessler (Trento, Italy) in conjunction with the ICT International Doctorate School of the University of Trento <https://iecs.unitn.it/> is pleased to announce the availability of the following fully-funded PhD position: TITLE: Resource-efficient Foundation Models for Automatic Translation DESCRIPTION: The advent of foundation models has led to impressive advancements in all areas of natural language processing. However, their huge size poses limitations due to the significant computational costs associated with their use or adaptation. When applying them to specific tasks, fundamental questions arise: do we actually need all the architectural complexity of large and - by design - general-purpose foundation models? Can we optimize them to achieve higher efficiency? These questions spark interest in research aimed at reducing models’ size, or deploying efficient decoding strategies, so as to accomplish the same tasks while maintaining or even improving performance. Success in this direction would lead to significant practical and economic benefits (e.g., lower adaptation costs, the possibility of local deployment on small-sized hardware devices), as well as advantages from an environmental impact perspective towards sustainable AI. Focusing on automatic translation, this PhD aims to understand the functioning dynamics of general-purpose massive foundation models and explore possibilities to streamline them for specific tasks. Possible areas of interest range from textual and speech translation (e.g., how to streamline a massively multilingual model to best handle a subset of languages?) to scenarios where the latency is a critical factor, such as in simultaneous/streaming translation (e.g., how to streamline the model to reduce latency?), to automatic subtitling of audiovisual content (e.g., how to streamline the model without losing its ability to generate compact outputs suitable for subtitling?). CONTACTS: Matteo Negri (negri(a)fbk.eu), Luisa Bentivogli (bentivo(a)fbk.eu) COMPLETE DETAILS AVAILABLE AT: https://iecs.unitn.it/education/admission/call-for-application IMPORTANT DATES: The deadline for application is May 7th, 2024, hrs. 04:00 PM (CEST) Prospective candidates are strongly invited to contact us in advance for preliminary interviews. Precedence for interviews will be given to short-listed candidates that will send us a complete CV via email ( negri(a)fbk.eu, bentivo(a)fbk.eu) by April 22, 2024. Candidate profile The ideal candidate must have recently completed or expect very soon an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering, or a closely related area. In addition, the applicant should: - Have an interest in Machine and Speech Translation - Have experience in deep learning and machine learning, in general - Have good programming skills in Python and experience in PyTorch - Enjoy working with real-world problems and large data sets - Have good knowledge of written and spoken English - Enjoy working in a closely collaborating team Working Environment The doctoral student will be employed at the MT group at Fondazione Bruno Kessler, Trento, Italy. The group (about 10 people including staff and students) has a long tradition in research on machine and speech translation and is currently involved in several projects. Former students are nowadays employed in leading IT companies in the world. Benefits Fondazione Bruno Kessler offers an attractive benefits package, including a flexible work week, full reimbursement for conferences and summer schools, a competitive salary, an excellent team of supervisors and mentors, help with housing, full health insurance, the possibility of Italian courses, and sporting facilities. Further Information For preliminary interviews, and should you need further information about the position, please contact Matteo Negri (negri(a)fbk.eu) and Luisa Bentivogli (bentivo(a)fbk.eu). Best Regards, Matteo Negri -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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Digital lexicography and lexical computing workshop, Málaga, Spain
by Ondřej Matuška 12 Apr '24

12 Apr '24

*<Lexicom/>* a workshop in digital lexicography and lexical computing *Registration open* *Málaga, Spain*16 – 20 September 2024 Your 5 days to get up-to-date with the latest developments in *corpus-driven lexicography* and to activate and enhance your *corpus building and corpus query skills* with some of the top experts in the field. For the programme, lecturers, invited speakers, fees and registration, visit this website *lexicom.courses <https://lexicom.courses/lexicom-2024-malaga-spain-lexicography-workshop/>* I hope to meet you in Málaga in September! Ondřej *Ondřej Matuška* Brno, CZ | Brighton, UK sketchengine.eu <http://www.sketchengine.eu> | Facebook <https://www.facebook.com/SketchEngine/> | LinkedIn <https://www.linkedin.com/in/ondrejmatuska> | Twitter <https://twitter.com/SketchEngine> Become a Sketch Engine *expert*! Check our training options» <https://mailchi.mp/sketchengine/learn-with-sketch-engine>

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Lectures on Computational Linguistics, June 19-21 2024, BARI (IT)
by Elisabetta Jezek 12 Apr '24

12 Apr '24

Dear Colleagues, We are pleased to announce that the 2024 edition of the *Lectures on Computational Linguistics*, a series of lectures dedicated to central topics in Computational Linguistics and Natural Language Processing, will be held in Bari from June 19 to 21. The programme and all information are available on this <https://www.ai-lc.it/en/lectures-2/lectures-2024/> site. The 2024 edition is organized by the Italian Association of Computational Linguistics/Associazione Italiana di Linguistica Computazionale (AILC) with the Department of Computer Science and the Department of Humanistic Research and Innovation of the University of Bari 'Aldo Moro'. The interdisciplinary nature of the school crosses several areas, particularly the Humanities, Computer Science and Artificial Intelligence. The program includes tutorials, labs, evening lectures, and two student presentation sessions. The 2024 edition features a four-hour tutorial dedicated to introducing Large Language Models to a broad audience. *Programme* *Wednesday, June 19, 2024* 9:00–9:30: Welcome and opening 9.30 – 11.30: Tutorial 1 (part 1) – Introduction to Large Language Models – Andrey Kutuzov, Language Technology Group, University of Oslo 11.30 – 12.00: BREAK 12:00 – 13:30: Student session 1.30pm – 3.00pm: LUNCH 3.00pm – 5.00pm: Tutorial 1 (part 2) – Introduction to Large Language Models – Andrey Kutuzov, Language Technology Group, University of Oslo 5.00pm – 5.30pm: BREAK 5.30pm – 6.30pm: Evening lecture 7.30pm: Welcome drink *Thursday, June 20, 2024* 9:00 – 11:00: Tutorial 2 – Computational methods for lexical semantic change detection – Nina Tahmasebi, University of Gothenburg 11:00 – 11:30: BREAK 11.30 – 13.30: Lab. 1 (part 1) – Hands-on Large Language Models – Marco Polignano & Lucia Siciliani, University of Bari Aldo Moro 1.30pm – 3.00pm: LUNCH 3.00pm – 5.00pm: Lab. 1 (part 2) – Hands-on Large Language Models – Marco Polignano & Lucia Siciliani, University of Bari Aldo Moro 5.00pm – 5.30pm: BREAK 5.30pm – 6.30pm: Evening lecture 7.00pm: Tour of the Old Town and dinner with typical food *Friday, June 21, 2024* 9:00 – 11:00: Tutorial 3 – Dissociating language and thought in Large Language Models – Anna Ivanova, School of Psychology, Georgia Tech 11:00 – 11:30: BREAK 11.30am – 1.00pm: Student session 1.00pm – 2.00pm: LUNCH 2.00pm – 4.00pm: Lab 2 – Lab. Computational methods for lexical semantic change detection – Pierluigi Cassotti, University of Gothenburg *Registration* The school is mainly aimed at Doctoral and Master's degree students, although a minimum qualification is not required for access. Participation is free but subject to registration, and places are limited to 200. Students wishing to present aspects of their work in the "Student Presentations" sessions are asked to send a 500-word abstract to ailc.lectures(a)gmail.com by May 10, 2024. Notifications of acceptance will be sent by May 31. Scientific Committee Pierpaolo Basile (University of Bari Aldo Moro) Raffaella Bernardi (University of Trento) Tommaso Caselli (University of Groningen) Felice Dell'Orletta (Institute of Computational Linguistics CNR – Pisa) Elisabetta Jezek (University of Pavia) Local Organizing Committee Pierpaolo Basile (Department of Computer Science, University of Bari Aldo Moro) Marco de Gemmis (Department of Computer Science, University of Bari Aldo Moro) Maristella Gatto (Department of Humanistic Research and Innovation, University of Bari Aldo Moro) Olimpia Imperio (Coordinator of the Doctorate in Letters, Languages and Arts, Department of Humanistic Research and Innovation, University of Bari Aldo Moro) Secretariat Lucia Siciliani (Department of Computer Science, University of Bari Aldo Moro) Contacts: ailc.lectures(a)gmail.com -- *Linguistica computazionale. Introduzione all'analisi automatica dei testi <https://www.mulino.it/isbn/9788815290359>.* Bologna, Il Mulino, in libreria dal 3 marzo 2023 -- [image: LOGO-UNIPV] Elisabetta Jezek Dipartimento di Studi Umanistici Professore Associato di Glottologia e Linguistica Corso Strada Nuova 65 - 27100 Pavia (Italia) <http://maps.google.com/?q=Corso+Strada+Nuova+65+27100+Pavia+%28Italia%29> T. 0382984391 https://studiumanistici.unipv.it/?pagina=docenti&id=13 <https://studiumanistici.unipv.it/?pagina=docenti&id=135>5 Elisabetta Jezek's Personal Meeting Room https://us02web.zoom.us/j/7814331810 -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material. <http://lettere.unipv.it/diplinguistica/docenti.php> -- [image: LOGO-UNIPV] PhD ELISABETTA JEZEK Dipartimento di Studi Umanistici PROFESSORE ASSOCIATO IN LINGUISTICA E GLOTTOLOGIA Presidente del corso di laurea magistrale internazionale in European Languages, Cultures and Societies in Contact Membro del Consiglio Direttivo dell'Associazione Italiana di Linguistica Computazionale <https://firmamail.unipv.it/index.php/firme/genera> https://unipv.unifind.cineca.it/resource/person/659960 Elisabetta Jezek's Personal Meeting Room https://us02web.zoom.us/j/7814331810 -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material. <http://lettere.unipv.it/diplinguistica/docenti.php>

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2nd CfP for CMCL at ACL 2024: Workshop on Cognitive Modeling and Computational Linguistics
by Ece Takmaz 11 Apr '24

11 Apr '24

*** CMCL – 2nd Call for Papers*** The 13th edition of the Workshop on Cognitive Modeling and Computational Linguistics (CMCL 2024) will be co-located with the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024). Webpage: https://cmclorg.github.io/ Direct submission page: https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/CMCL ARR commitment page: https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/CMCL_ARR_Commi… *Workshop Description* CMCL 2024 is a one-day workshop held in conjunction with ACL 2024. CMCL invites papers on cognitive modeling, cognitively-inspired natural language processing, and, more broadly, the alignment of language models with human cognition/perception. The 2024 workshop follows in the tradition of earlier meetings at ACL 2010, ACL 2011, NAACL-HLT 2012, ACL 2013, ACL 2014, NAACL 2015, EACL 2017, LSA 2018, NAACL 2019, EMNLP 2020, NAACL 2021, and ACL 2022. *Scope and Topics* The research interests/questions include, but are not limited to: - Human-like language acquisition/learning: How is language acquisition of language models (LMs) (dis)similar to humans, and why? - Contrasting/aligning NLP models with human behavior data: What do humans compute during language comprehension/production, and how/why? - Linguistic probing of NLP models: How well do current language models understand/represent/generalize language behaviorally/internally? - Linguistically-motivated data modeling/analysis: How can one quantify a particular aspect of language? - Emergent communication/language: What are the sufficient conditions for the emergence of language? A more formal description of the workshop scope is: - Stochastic models of factors influencing a speaker's production or comprehension decisions. - Models of semantic interpretation, including psychologically realistic notions of word and phrase meaning and composition. - Incremental parsers for diverse grammar formalisms and their psychological plausibility. - Models of speaker-specific linguistic adaptation and/or generalization. - Models of first and second language acquisition and bilingual language processing. - Behavioral tasks for better understanding neural models of linguistic representation. - Models and empirical analysis of the relationship between mechanistic psycholinguistic principles and pragmatics or semantics. - Models of lexical acquisition, including phonology, morphology, and semantics. - Psychologically motivated models of grammar induction. - Psychologically plausible models of lexical or conceptual representations. - Models of language disorders, such as aphasia, dyslexia, or dysgraphia. - Behavioral datasets or resources for modeling language processing or production in languages other than English. - Models of language comprehension difficulty. - Models of language learning and generalization. - Models of linguistic information propagation and language evolution in communities. - Cognitively-motivated models of discourse and dialogue. *Invited Speakers* Aida Nematzadeh (Google DeepMind) Frank Keller (University of Edinburgh) *Important Dates* - May 17, 2024: Paper submission/commitment deadline (cf. May 15, 2024: notification of ACL 2024) - June 17, 2024: Notification of acceptance - July 1, 2024: Camera-ready paper due - August 15, 2024: Workshop dates Deadlines are at 11:59 pm AOE. *Workshop submissions* CMCL accepts direct submissions through the OpenReview site: https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/CMCL We also receive papers already reviewed in ACL Rolling Review (ARR) February or earlier: https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/CMCL_ARR_Commi… There is no need that the CMCL is mentioned as a preferred venue in the original ARR submission. Detiailed submission flow/schedule is shown in our workshop webpage: https://cmclorg.github.io/ *Submission types* We invite three types of submissions: (1) Archival regular workshop submissions that present original research in either long (8 pages + references) or short (4 pages + references) paper format. (2) Non-archival submissions of extended abstracts that present preliminary results (from 2 to 4 pages + references). (3) Non-archival cross-submission of long/short papers that present relevant research submitted/published elsewhere (including ACL "Findings of..." papers). - Only regular workshop papers submitted via (1) will be included in the proceedings, but all types of papers will have a presentation opportunity in the workshop. - Submissions must be formatted using the ACL style template (https://github.com/acl-org/acl-style-files) and be submitted as a PDF file. - We adhere to the ACL anonymity policy: https://www.aclweb.org/adminwiki/index.php/ACL_Anonymity_Policy - This year, we don't host a shared task. *Workshop Organizers* Tatsuki Kuribayashi (MBZUAI, tatsuki.kuribayashi(a)mbzuai.ac.ae) Giulia Rambelli (University of Bologna, giulia.rambelli4(a)unibo.it) Ece Takmaz (University of Amsterdam, ece.takmaz(a)uva.nl) Philipp Wicke (Ludwig Maximilian University LMU, pwicke(a)cis.lmu.de) Yohei Oseki (University of Tokyo, oseki(a)g.ecc.u-tokyo.ac.jp) *Program Committee* Abdellah Fourtassi (Aix-Marseille University) Adina Williams (FAIR) Afra Alishahi (Tilburg University) Aniello De Santo (University of Utah) Carina Kauf (MIT) Cassandra Jacobs (University of Buffalo) Christos Christodoulopoulos (Amazon) Cory Shain (MIT) Ethan Wilcox (ETH Zurich) Frances Yung (Saarland University) Fred Mailhot (Dialpad) Gianluca Lebani (University Ca' Foscari Venezia) James Michaelov (The University of California San Diego) John Hale (University of Georgia) Laurent Prévot (Aix-Marseille University) Lisa Beinborn (VU Amsterdam) Ludovica Pannitto (University of Trento) Micha Elsner (Ohio State University) Nora Hollenstein (University of Copenhagen) Rachel Ryskin (University of California Merced) Raquel Garrido Alhama (Tilburg University) Richard Futrell (UC Irvine Language Science) Robert Frank (Yale University) Ryo Yoshida (The University of Tokyo) Samar Husain (IIT Delhi) Sandra Kuebler (Indiana University) Tal Linzen (New York University) Ted Briscoe (MBZUAI) Tiago Pimentel (ETH Zurich) Tim Hunter (UCLA) Vera Demberg (Saarland University) William Schuler (Ohio State University) Yao Yao (Hong Kong Polytechnic University) *Website* https://cmclorg.github.io/ *Sponsoring Institutions* Japan Society for the Promotion of Science *Contact* cmclorganizers2024(a)gmail.com

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PhD position on AI/NLP/IR at the University of Amsterdam
by Jaap Kamps 10 Apr '24

10 Apr '24

The University of Amsterdam has a fully funded PhD position on AI/NLP/IR for information access. We seek an ambitious PhD student with a background in artificial intelligence, natural language processing and information retrieval. Your focus will be on large language models (LLMs) for information access. How can we search specific collections, including full text, metadata, and multimodal content? How can we support complex search tasks and practices, such as scholarly research on cultural data, and the research and workflow of investigative journalism? The PhD position is part of four PhD vacancies as part of digital Humanities, Artificial Intelligence, Cultural Heritage (HAICu) project, a large national science agenda project funded by the Netherlands Organization for Scientific Research. We are one of the best European and global places to study AI, and you will work together with other AI and Digital Humanities researchers, and a range of external partners on scientific breakthroughs. HAICu deploys artificial intelligence (AI) to make digital heritage collections more accessible, and the extraordinary challenges of cultural heritage provide a unique opportunity to push the boundaries of AI. The PhD position is fully funded and you will be employed by the University of Amsterdam for four years (full-time, with all employment benefits) and are expected to complete a PhD thesis within this period. Are you interested? Strong candidates with an AI/NLP/IR background are encouraged to apply by May 15. Details are in: https://vacatures.uva.nl/UvA/job/4PhDs/792167402/ (Project #1). Feel free to reach out with questions or comments! Jaap Kamps

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Second CfP: The First Workshop on Data Contamination (CONDA) @ ACL 2024
by Eneko Agirre 10 Apr '24

10 Apr '24

We invite you to participate and submit your work to the First Workshop on Data Contamination (CONDA) co-located with ACL 2024 in Bangkok, Thailand. Data contamination, where evaluation data is inadvertently included in pre-training corpora of large scale models, and language models (LMs) in particular, has become a concern in recent times. The growing scale of both models and data, coupled with massive web crawling, has led to the inclusion of segments from evaluation benchmarks in the pre-training data of LMs. The scale of internet data makes it difficult to prevent this contamination from happening, or even detect when it has happened. Crucially, when evaluation data becomes part of pre-training data, it introduces biases and can artificially inflate the performance of LMs on specific tasks or benchmarks. This poses a challenge for fair and unbiased evaluation of models, as their performance may not accurately reflect their generalization capabilities. Although a growing number of papers and state-of-the-art models mention issues of data contamination, there is no agreed-upon definition or standard methodology to ensure that a model does not report results on contaminated benchmarks. Addressing data contamination is a shared responsibility among researchers, developers, and the broader community. By adopting best practices, increasing transparency, documenting vulnerabilities, and conducting thorough evaluations, we can work towards minimizing the impact of data contamination and ensuring fair and reliable evaluations. We welcome paper submissions on all topics related to data contamination, including but not limited to: * Definitions, taxonomies, and gradings of contamination * Contamination detection (both manual and automatic) * Community efforts to discover, report, and organize contamination events * Documentation frameworks for datasets or models * Methods to avoid data contamination * Methods to forget contaminated data * Scaling laws and contamination * Memorization and contamination * Policies to avoid impact of contamination in publication venues and open source communities * Reproducing and attributing results from previous work to data contamination * Survey work on data contamination research * Data contamination in other modalities *Submission Instructions* We welcome two types of papers: regular workshop papers and non-archival submissions. Regular workshop papers will be included in the workshop proceedings. All submissions must be in PDF format and made through OpenReview. * Regular workshop papers: Authors can submit papers up to 8 pages, with unlimited pages for references. Authors may submit up to 100 MB of supplementary materials separately and their code for reproducibility. All submissions undergo a double-blind single-track review. Best Paper Award(s) will be given based on nomination by the reviewers. Accepted papers will be presented as posters with the possibility of oral presentations. * Non-archival submissions: Cross-submissions are welcome. Accepted papers will be presented at the workshop but not included in the workshop proceedings. Papers must be in PDF format and will be reviewed in a double-blind fashion by workshop reviewers. We also welcome extended abstracts (up to 2 pages) of papers that are work in progress, under review or to be submitted to other venues. Papers in this category need to follow the ACL format. In addition to papers submitted directly to the workshop, which will be reviewed by our Programme Committee. We also accept papers reviewed through ACL Rolling Review and committed to the workshop. Please, check the relevant dates for each type of submission. *Important dates* * Relevant deadlines to consider when submitting your paper are: * Paper submission deadline: May 17 (Friday), 2024 * ARR pre-reviewed commitment deadline: TBD, 2024 * Notification of acceptance: June 17 (Monday), 2024 * Camera-ready paper due: July 1 (Monday), 2024 * Workshop date: August 16, 2024 *Sponsors* * AWS AI and Amazon Bedrock * HuggingFace * Google *Contact* * Website: https://conda-workshop.github.io/ * Email: conda-workshop(a)googlegroups.com *Organizers* Oscar Sainz, University of the Basque Country (UPV/EHU) Iker García Ferrero, University of the Basque Country (UPV/EHU) Eneko Agirre, University of the Basque Country (UPV/EHU) Jon Ander Campos, Cohere Alon Jacovi, Bar Ilan University Yanai Elazar, Allen Institute for Artificial Intelligence and University of Washington Yoav Goldberg, Bar Ilan University and Allen Institute for Artificial Intelligence -- Eneko Agirre HiTZ Hizkuntza Teknologiako Zentroa - Ixa Taldea Centro Vasco de Tecnología de la Lengua - Grupo Ixa Basque Center for Language Technology - Ixa NLP Group University of the Basque Country (UPV/EHU) hitz.ehu.eus/eneko <https://hitz.ehu.eus/eneko>

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2026

2025

2024

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2022