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Post-doctoral fellowship - Université de Lorraine
by Maxime Amblard 14 Jun '24

14 Jun '24

Project ANR SHERBET : Stemmatology for the HEbRew BiblE Transmission - Artificial Intelligence to understand the transmission of the Hebrew Bible 1st September 2024-31th August 2026 Description Before the appearance of the printing press, the only way of reproducing and spreading a text in written form was manual copying. During this process, accidents, errors and intentional modifications occurred, progressively modifying the text of each witness. The revised text, whether modified deliberately or accidentally, then served as a template for other copyists and the changes would thereby be propagated. For the philologist interested in the reconstruction of text history and the text’s genealogical relations (similar to a genealogical tree, called stemma codicum), it has been imperative to study these different variants and suggest methods for the objective construction of such trees (called stemmatology methods). Retrieving the genealogical lineage of the Hebrew manuscripts has been one of the major focuses of the laboratoire Écritures and the MSH at the University of Lorraine. In this project, we suggest to improve the manual work performed in the critical editions of the Hebrew Bible by applying the latest advances in applied mathematics and natural language processing to reconstruct the stemmas of the Hebrew manuscripts. This project takes place as a partnership between the centers of research MSH Lorraine (UL), Écriture (UL), LORIA (UL), LJK (UGA) and IECL (UL). In this context, we are looking for a two years fellow for a post-doctoral position, to fulfill the objective of building the genealogical lineage of the Hebrew Bible through computational stemmatology algorithms. Postdoc’s responsabilities Over the course of the project, the fellow will be asked to lead and innovate to complete the following objectives: Automatic Variant tagging for ancient language The candidate will have to design, train and test a Deep Learning model to automatically tag scribal variants between manuscripts. The model should will be trained on the different variants and their subsequent classification, as designed by the philology experts (orthographic, lexical, grammatical, etc.). The model will then be able to automatically suggest a variant classification given two different strings. While the main focus of the project is Hebrew, extension to Greek would be a possible supplement to the project. Textual embedding of ancient languages A major challenge of the project is the computation of a semantic-based distances between Hebrew words, in order to define the proximity between two variants, accounting for their meaning. The candidate will have to work on textual embeddings and textual representation of the Hebrew words using Neural Networks. Textual generation of Hebrew texts using adversarial Deep Learning models Current approaches within the project rely on probabilistic models to generate mock textual traditions to be used as ground truth, that resemble the variants observed on real traditions. Statistics describing scribal behavior are then fed into the model, that then rely on Markov chains to generate the corresponding tradition. One of the objectives of the project is to rely on Deep Learning models for this generation of mock traditions, by using generative adversarial networks. The networks should be able to generate new traditions representative of scribal behavior. Provide Open-Source results To ensure a reception as wide as possible for the project and to strive towards the goal of making science open to all, the candidate is expected to provide all the software developed over the course of the project as an Open-Source software, respecting all the quality constraints of modern software development. The generated datasets should also be made available to the public. All results will be published in high-impact journals and conferences. Required skills Mathematical and computer science skills The candidate must have a PhD in computer science and/or applied mathematics (artificial intelligence, natural language processing...). An experience in Deep Learning, especially applied to Natural Language Processing or modelization of complex systems is required. Technical skills The candidate should be very familiar with the Python ecosystem for Deep Learning, data manipulation and analysis: pandas, sklearn, tensorflow/ Keras/pytorch. The candidate should have previous experience in the development of Open-Source software and a good knowledge of current development standards, to ensure that the project reaches as many scholars as possible: CI/CD pipelines, containerization, automated deployments. They will also have to interact daily with REST API and SQL databases. A good understanding of XML TEI and collation tools would be a plus. Humanities skill Knowledge of Classical Greek and Ancient Hebrew. Knowledge and interest in textual criticism, philology and biblical studies would be a plus. The candidate is expected to have a good level in English. Knowledge of French would be a plus. Terms and tenure This two-years position will be based at the Loria, Campus Scientifique, BP 239 54506, Vandoeuvre-lès- Nancy & MSH Lorraine, Ile du Saulcy, 57000 Metz. The duration can not exceed 24 months. The target start date for the position is 1st September 2024, with some flexibility on the exact start date. How to apply Applicants are requested to submit the following materials: • A cover letter explaining their motivation for the position. • Full Curriculum Vitae and list of publications. • Academic transcripts (unofficial versions are fine) Deadline for application is June 17th 2024. All documents must be sent to frederique.rey(a)univ-lorraine.fr Job Location Nancy-Metz, Lorraine, France ---------------------- Maxime Amblard Université de Lorraine https://members.loria.fr/mamblard http://espoir-ul.fr Si vous lisez ce message en dehors de vos heures de travail, merci de ne le traiter qu’en cas d’urgence avérée.

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[CIKM-2024] Final Call for Industry Day Papers
by antonela.tommasel＠isistan.unicen.edu.ar 13 Jun '24

13 Jun '24

** Industry Day deadline June 20th ** ** A week to go ** =============== =============== * We apologize if you receive multiple copies of this CfP * * For the online version of this Call, visit: https://cikm2024.org/call-for-industry-day-papers/ =============== CIKM 2024: 33rd ACM International Conference on Information and Knowledge Management Boise, Idaho, USA October 21–25, 2024 =============== The Conference on Information and Knowledge Management (CIKM) provides an international forum for the presentation and discussion of research on information and knowledge management, as well as recent advances in data and knowledge bases. The purpose of the conference is to identify challenging problems facing the development of future knowledge and information systems, and to shape future directions of research by soliciting and reviewing high-quality, applied and theoretical research findings. We call for technical talks which will cover how topics of interest relevant to the broader CIKM community, including but not limited to knowledge management, information retrieval, efficient data processing, neural and large language models, evaluation, recommender systems, data mining, and others found in the CIKM ‘24 Call for Papers are used in an industrial setting. Possible topics include how machine learning is put to use in practical scenarios, how user behavior can be observed and interpreted, how to improve systems in practice, how industrial pipelines can be optimized, and how scale is a challenge in more ways than the obvious. We also encourage talk proposals from small companies, such as startups or spin-offs from either a university project or a large company. -------------------------- Key Dates -------------------------- * Submissions Due: June 20th, 2024 * Notifications: July 16, 2024 * Camera ready for abstracts: August 8, 2024 (All deadlines are at 11:59 pm AOE) The Industry Day of CIKM ’24 will be held on Monday 21st Oct 2024 in Boise, Idaho, USA. -------------------------- Topics of Interest -------------------------- Talks may address challenges, solutions, and case studies of interesting and innovative systems in areas including but not limited to: * Innovative approaches used in deployed systems and products * System design from industry practitioners which identify best practices and design principles for machine learning systems and their scalability aspects * Metrics and measurement techniques used to understand performance of production systems * Practical challenges such as data, privacy, integrity, scale, regulation, etc. * Domain specific challenges and niche focuses * Connections with academia to solve interesting problems, including talk proposals from academics spending time in industry, or vice-versa, covering insights for other practitioners We encourage talk proposals from small companies, such as startups or spin-offs from either a university project or a large company. -------------------------- Paper Submissions -------------------------- Proposals should be at most 2 pages and follow the ACM format. Formatting guidelines are available at the ACM Website (use the ˮsigconf” proceedings template). https://www.acm.org/publications/proceedings-template Submissions should include: * Title and abstract * Speaker's bio * Relevance to above themes and CIKM topics * CIKM is a technical conference, so preference will be given to talks describing applied research and technical challenges rather than product presentations. * Speakers will be asked to confirm their presence at the conference if their submission is accepted. Submissions are not anonymous and should contain speaker details. Proposals should be submitted electronically via EasyChair: https://easychair.org/conferences/?conf=cikm2024 The authors of accepted proposals will be invited to submit an abstract to be published in the conference proceedings. Each presentation will be 15-20 minutes long including Q&A. -------------------------- Chairs Contact Information -------------------------- For more information, contact the Industry Day chairs: cikm2024-industry [at] easychair [dot] org Ilaria Bordino, UniCredit, Italy Udayan Khurana, IBM Research, USA Marc Najork, Google DeepMind, USA

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Job: permanent engineer position at Structures Formelles du Langage (CNRS)
by Sarra El Ayari 13 Jun '24

13 Jun '24

Dear colleagues, The SFL Laboratory (Paris, France) is recruiting a Research Engineer (M/F) expert in psycholinguistics during the CNRS external competitions (permanent position). Details here: https://carrieres.cnrs.fr/en/concours-externes-des-ingenieurs-et-technicien… Best regards, S. El Ayari -- Sarra El Ayari Ingénieure de recherche en analyse de données linguistiques Laboratoire Structures Formelles du Langage UMR 7023 (CNRS & Université Paris 8) http://www.sfl.cnrs.fr/sarra-el-ayari

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CfP: Special Issue on “Human Linguistic Behaviour in Machine-Generated Environments” in the International Journal "Research Result. Theoretical and Applied Linguistics (RR.T&AL)"
by George Mikros 13 Jun '24

13 Jun '24

We are glad to announce the call for papers for the upcoming Special Issue on “Human Linguistic Behaviour in Machine-Generated Environments” in the International Journal "Research Result. Theoretical and Applied Linguistics (RR.T&AL)", scheduled for publication in December 2024. In conjunction with this Special Issue, a Research Paper Competition is being launched to promote impactful research and transparency in the field of Large Language Model (LLM) research. 𝐒𝐩𝐞𝐜𝐢𝐚𝐥 𝐈𝐬𝐬𝐮𝐞 𝐃𝐞𝐭𝐚𝐢𝐥𝐬: 𝐆𝐮𝐞𝐬𝐭 𝐄𝐝𝐢𝐭𝐨𝐫𝐬: • 𝐓𝐚𝐭𝐢𝐚𝐧𝐚 𝐀. 𝐋𝐢𝐭𝐯𝐢𝐧𝐨𝐯𝐚, Voronezh State Pedagogical University & Higher School of Economics • 𝐆𝐞𝐨𝐫𝐠𝐞 𝐊. 𝐌𝐢𝐤𝐫𝐨𝐬, Hamad Bin Khalifa University & University of Massachusetts Boston 𝐀𝐬𝐬𝐨𝐜𝐢𝐚𝐭𝐞 𝐄𝐝𝐢𝐭𝐨𝐫: • 𝐎𝐥𝐠𝐚 𝐀. 𝐌𝐢𝐭𝐫𝐨𝐟𝐚𝐧𝐨𝐯𝐚, St. Petersburg State University 𝐓𝐨𝐩𝐢𝐜𝐬: We welcome manuscripts offering new insights into topics such as: • Large language models and prompt engineering in the study of human language behaviour in machine-generated environments. • Experimental methods for studying human language behaviour in machine-generated environments (eye tracking, analysis of computer-mediated communication, virtual reality modelling). • The influence of individual and technological factors on the characteristics of human linguistic behaviour in machine-generated environments and methods for its research. • Corpus methods, models, and resources in studies of human linguistic behaviour in machine-generated environments. • Creation of specialised databases for studying human language behaviour in machine-generated environments. 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐃𝐚𝐭𝐞𝐬: • Title and Abstract Deadline: 𝟎𝟓 𝐉𝐮𝐥𝐲 𝟐𝟎𝟐𝟒 • Manuscript Submission Deadline: 𝟎𝟑 𝐒𝐞𝐩𝐭𝐞𝐦𝐛𝐞𝐫 𝟐𝟎𝟐𝟒 For submission guidelines and more details, visit: https://lnkd.in/dmSGjWxA All the manuscripts marked for Competition should be forwarded to e-mail: ovdekhnich(a)mail.ru<mailto:ovdekhnich@mail.ru> • See more details for the Special Issue here: https://bit.ly/3zb6FS4 • See more details for the Research Paper Competition here: https://bit.ly/3KG4c4D

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10 days left: 3-years PhD/PostDoc position on NLP for Social Good at Leibniz University Hannover (due June 23)
by h.wachsmuth＠ai.uni-hannover.de 13 Jun '24

13 Jun '24

The Institute of Artificial Intelligence invites applications for the position of a DOCTORAL OR POSTDOCTORAL RESEARCHER (M/F/D) ON THE TOPIC OF NATURAL LANGUAGE PROCESSING (NLP) FOR SOCIAL GOOD (SALARY SCALE 13 TV-L, 100%) starting in September 2024 or soon afterwards. The position is limited to a period of three years with the possibility of extension. TASKS The goal of the offered position is to carry out innovative research on NLP, aiming for scientific publications at reputed international venues. The research should involve LARGE LANGUAGE MODELS (LLMs) related to NLP FOR SOCIAL GOOD. We support the development of own research directions in this broad context. The position also comes with a teaching duty of four hours per week; the candidate is expected to lead tutorials and/or programming labs as well as to support the supervision of bachelor's and master’s students. We are looking for highly motivated candidates with a passion for creativity and learning who seek to make a positive impact through open and independent research in a young team. YOUR PROFILE - Completed academic degree (Master or comparable) in computer science, computational linguistics, artificial intelligence, or related disciplines - Solid understanding of machine learning with hands-on experience, ideally in the context of NLP and LLMs - Proficient programming skills in Python - Good scientific writing skills (for example, shown by a very good master’s thesis) are expected - Strong communication skills in English, both in oral and in written form TEAM The position will be placed in the NLP Group at the Institute of Artificial Intelligence. We are a diverse and international team, studying how humans express their views and intentions in language, and how LLMs can understand and create such language in a fair, trustworthy, and explainable way. Our research tackles interdisciplinary questions from the humanities and social sciences, while building on state-of-the-art NLP techniques, such as instruction fine-tuning and contrastive learning. We seek to do cutting-edge research on artificial intelligence methods that have a positive impact on society and the world. OUR OFFER - Creative and innovative work in a diverse and international team - Possibility to obtain a Ph.D. degree or to shape your Postdoc profile - State-of-the-art research facilities, including top-notch computing clusters - Participation in international scientific events and research collaborations - Salary at the level of 100% of salary scale 13 according to the Collective Agreement for the Public Service of the Länder (TV-L) D&I Leibniz University Hannover considers itself a family-friendly university and therefore promotes a balance between work and family responsibilities. Part-time employment can be arranged upon request. The university aims to promote equality between women and men. For this purpose, the university strives to reduce under-representation in areas where a certain gender is under-represented. Women are under-represented in the salary scale of the advertised position. Therefore, qualified women are encouraged to apply. Moreover, we welcome applications from qualified men. Preference will be given to equally-qualified applicants with disabilities. QUESTIONS In case you have questions, please contact Maja Stahl (email: m.stahl(a)ai.uni-hannover.de). Further information about the NLP Group can be found at: https://www.ai.uni-hannover.de/en/institute/research-groups/nlp For information on the salary scales, see: https://oeffentlicher-dienst.info/c/t/rechner/tv-l/west?id=tv-l-2023&matrix… APPLICATION Please submit your application with supporting documents (including CV, full set of transcripts, a brief statement of at most 1 page of why you apply to the NLP Group, and possibly further qualifications) by June 23, 2024 as A SINGLE PDF FILE to Email: office(a)ai.uni-hannover.de (subject: “[ai-nlp] Application”) or alternatively by post to: Gottfried Wilhelm Leibniz Universität Hannover Institute of Artificial Intelligence Prof. Dr. Henning Wachsmuth Welfengarten 1, 30167 Hannover Germany http://www.uni-hannover.de/jobs Information on the collection of personal data according to article 13 GDPR can be found at https://www.uni-hannover.de/en/datenschutzhinweis-bewerbungen/.

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fulltime research position at University College Dublin
by Stephanie Dornschneider-Elkink 13 Jun '24

13 Jun '24

Dear Colleagues, I am recruiting for a one-year fully funded research assistant position involving NLP/ quantitative methods in text analysis. I would be really grateful if you could share this ad with anyone interested. I am available for any questions potential applicants might have. Thanks a lot! Kind regards, Stephanie *One-year fulltime research assistant position at University College Dublin* *Start Date* 1st October 2024 *Duration* 12 months *Deadline* 15 July, noon IST *Full ad* https://my.corehr.com/pls/coreportal_ucdp/apply?id=017399 University College Dublin is currently recruiting a researcher to implement natural language processing (NLP) tools to interviews, speeches, and newspaper articles. The research assistant will support the development of tools to identify and analyse so-called cognitive maps (Axelrod 1976). Dornschneider and Henderson (2016, 2023) and Dornschneider (2019) have developed tools for the computational analysis of cognitive maps. What is needed is a set of tools to infer cognitive maps from natural language. This Irish Research Council funded project investigates the role of women in Muslim resistance movements. The cognitive mapping analysis has several main objectives: 1- to show typical behavioral decisions (e.g. to join a resistance a movement) described by the interviewees; 2- to identify common reasoning processes related to these decisions; and 3- to trace the role of religious beliefs in these reasoning processes. The research assistant will work with the Principal Investigator, Dr. Stephanie Dornschneider-Elkink, to deliver the research objectives of the project. Tasks will include but are not limited to POS tagging, sequence analysis, word embeddings, and visualization. Principal duties • Work under the supervision of the Principal Investigator to implement the objectives of the IRC project • Apply quantitative text analysis to interviews, speeches, and newspaper articles • Help generate and analyse cognitive maps • Web scraping Mandatory requirements • Some undergraduate or graduate-level training in quantitative research methods, data science, or quantitative text analysis/NLP • Preferably a political science, data science, and/ or computer science background • Experience with programming in R and/ or Python • Ability to work independently and take the initiative to implement the outlined tasks • Report to the team and PI on a regular basis • Candidates must demonstrate an awareness of equality, diversity and inclusion agenda. *References* Axelrod, R. (ed.). 1976. Structure of decision: The cognitive maps of political elites. Princeton: Princeton university press. Dornschneider-Elkink, S. and Henderson, N., 2023. Repression and Dissent: How Tit-for-Tat Leads to Violent and Nonviolent Resistance. Journal of Conflict Resolution, p.00220027231179102. https://doi.org/10.1177/0022002714540473 Dornschneider, S., 2019. High‐Stakes Decision‐Making Within Complex Social Environments: A Computational Model of Belief Systems in the Arab Spring. Cognitive Science, 43(7), p.e12762. https://doi.org/10.1111/cogs.12762 Dornschneider, S. and Henderson, N., 2016. A computational model of cognitive maps: Analyzing violent and nonviolent activity in Egypt and Germany. Journal of Conflict Resolution, 60(2), pp.368-399. -- Dr Stephanie Dornschneider-Elkink Assistant Professor, School of Politics & International Relations (SPIRe) University College Dublin Newman Building, F316, Belfield, Dublin 4, Ireland http://www.dornschneider.net/

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Call for Abstracts - Conference on Rational Approaches in Language Science (RAILS)
by Stefania Degaetano-Ortlieb 13 Jun '24

13 Jun '24

Dear all, We are delighted to announce the upcoming 2nd edition of the conference on "Rational Approaches in Language Science" (RAILS), which will be organized by the Collaborative Research Center (CRC) 1102 "Information Density and Linguistic Encoding“ (https://sfb1102.uni-saarland.de/). The central theme of this conference is (bounded) rational communication, i.e. the idea that language users continuously strive to optimize their means of communication to effectively convey their intended messages. Thus, rational communication has consequences on how recipients encode and remember information, and it also impacts language variation and change. RAILS will bring together researchers from various fields investigating how information dynamics, rational communication and memory interact with language use, variation, and change. We welcome contributions on (1) how interlocutors process and update information in diverse situational contexts; (2) how language use is adapted to certain contexts and intended referents and (3) how linguistic and conceptual information is stored and maintained in short- and long-term memory. Ultimately, the goal of the conference is to gain deeper insights into the complexities of language use and its dynamic nature in different settings. We invite submissions from researchers across the language sciences – including speech science, theoretical linguistics, empirical linguistics, psycholinguistics and neuroscience, computational linguistics, as well as language development, change and evolution – who apply rational probabilistic explanations to linguistic phenomena, or bring novel experimental findings to bear on such accounts. Submission We accept submissions for posters and/or talks. Talks are slated for 20 minutes plus 10 minutes for questions. Abstracts should be no more than 500 words (Times New Roman size 12, with one additional page for example, tables, figures and (selected) references). Titles should be centered at the top of the page, in bold and upper case. Please ensure the abstract is fully anonymous: authors’ names or affiliations should not be indicated anywhere in the document or in the metadata. Important dates Submissions open: July 8th 2024 Submissions due: Sept 16th 2024 Notification of acceptance: Nov 4th 2024 Registration period: 11th Nov – 16th Dec 2024 Final abstract submission: Dec 2nd 2024 PD Stefania Degaetano-Ortlieb Assistant Professor / Akademische Rätin Universität des Saarlandes Language Science and Technology Campus A2.2, 1.06 66123 Saarbrücken Tel.: ++49 681 302 70077 E-Mail: s.degaetano(a)mx.uni-saarland.de www.stefaniadegaetano.com

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AthNLP 2024 - 2nd ATHENS NLP SUMMER SCHOOL
by A. Vlachos 12 Jun '24

12 Jun '24

2nd Call for Participation AthNLP 2024 - 2nd ATHENS NLP SUMMER SCHOOL ============================================================== ** Application Deadline: June 20, 2024 ** Preliminary schedule: https://athnlp.github.io/2024/schedule.html ** CFP webpage: https://athnlp.github.io/2024/cfp.html <https://athnlp.github.io/2024/cfp.html> ** Info for sponsors: see here<https://drive.google.com/file/d/1MuSzi7hvT7AwE_8bwhbIymh-ZWNq3noR/view?usp=…> We invite everyone interested in Natural Language Processing and Machine Learning to attend the 2nd Athens Natural Language Processing Summer School - AthNLP 2024: https://athnlp.github.io/2024/ Important Dates --------------- * Application Deadline: June 20, 2024 * Decision: June 30, 2024 * Early Registration: July 30, 2024 * Late Registration: September 15, 2024 * Summer School: September 19-25, 2024 Description --------------- Following on from the success of the 1st AthNLP in 2019, AthNLP 2024 will take place at the campus of NCSR “Demokritos" in Athens and is organised jointly by NCSR "Demokritos", the Athens University of Economics and Business, RC "Athena", and Heriot-Watt University. AthNLP cooperates closely with the organisers of LxMLS, taking place in Lisbon, in July 11-17. The school will cover a range of NLP topics focusing on machine learning (ML) methods. There will be morning lectures focusing on theoretical aspects, afternoon lab sessions focusing on implementation and experimentation, and evening talks on research topics and perspectives, as well as demos and posters from the participants and industry research labs. The lectures and the evening talks will be given by internationally recognized researchers from academic and industrial research labs. The topics to be covered include: classification, sequence prediction, linear models, neural networks, encoder-decoder architectures, machine translation, large language models, and multimodality. Our target audience is: * Researchers and students in the fields of NLP and Computational Linguistics; * Computer scientists who have interests in natural language processing and machine learning; * Industry practitioners who desire a more in-depth understanding of these subjects. While previous experience with the topics will be helpful, the school assumes no previous knowledge of natural language processing and machine learning. The only background required is basic mathematics and Python programming. Features of AthNLP: * Attendance at the Social Event, daily lunch as well as morning and afternoon coffee breaks are included in the application fee. * Lecturers are leading researchers in machine learning and natural language processing. * Students will be able to (optionally) show their current work in poster sessions during coffee breaks. * In the demo day, students will be able to interact with technical companies and research institutions working in machine learning. Confirmed Speakers --------------- * Antonis Anastasopoulos, George Mason Computer Science * Raquel Fernández, University of Amsterdam * Ferenc Huszár, University of Cambridge * Martin Krallinger, Barcelona Supercomputing Center * Mirella Lapata, University of Edinburgh * Ryan McDonald, ASAPP * Aida Nematzadeh, Google DeepMind * Vlad Niculae, University of Amsterdam * Barbara Plank, Ludwig Maximilian University of Munich * Anna Rogers, IT University of Copenhagen Participation ----------------- To apply, please fill the form here<https://openreview.net/group?id=demokritos.gr/NCSR_Demokritos/Athens_NLP/20…> on OpenReview. The fees are the following: 300 EUR for students 400 EUR for university professors or researchers at a public institute 500 EUR for everyone else Any questions should be directed to: athnlp2024(a)athenarc.gr<mailto:athnlp2024@athenarc.gr> We are looking forward to your participation! -- The organisers of AthNLP 2024

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T
by Md. Mamun Hossain 12 Jun '24

12 Jun '24

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[POST DOCTORAL POSITION] Contextual Information Inference for Argument Mining
by Anaïs Ollagnier UNICA 12 Jun '24

12 Jun '24

*Bonjour,* * (english announcement follows) Dans le cadre du projet CIIAM (Contextual Information Inference for Argument Mining) financé par l’Académie d’Excellence Réseaux, Information et Société Numérique, visant à renforcer la robustesse des techniques de fouille d'arguments par la synthétisation d’informations contextuelles relevant des aspects multimodaux de la communication. Nous invitons les doctorant(e)s en fin de thèse et les jeunes docteur(e)s à candidater à un postdoctorat sur "l'Amélioration de la fouille d’argument par la synthétisation d’information contextuelle" (12 mois). -------- Contexte -------- Parvenir à appréhender les structures argumentatives dans les entrées en langage naturel constitue une étape clé pour de nombreuses tâches relevant du domaine du Traitement Automatique des Langues (TAL), telles que le résumé automatique ou l'analyse de débats politiques. Bien que des progrès significatifs aient été réalisés grâce à l'avènement des modèles de langue pré-entraînés, ils ne saisissent pas toujours l'ensemble des connaissances linguistiques nécessaires pour une compréhension contextuelle fine et l'établissement d'inférences pertinentes. Face à ces limitations, notre projet vise à explorer l'inclusion de la dimension d'analyse linguistique liée à la pragmatique. Cette approche se veut particulièrement novatrice, car la pragmatique, en raison de sa complexité à être formalisée, est très peu étudiée d'un point de vue computationnel. C’est à travers l'utilisation des dernières techniques de pointe en matière de "prompting" que nous souhaitons pallier les écueils des méthodes existantes, tels que la variabilité culturelle et l’implicite. --------------- Pour candidater --------------- Sujet détaillé : https://aollagnier.github.io/publications/CIIAM%20PostDoc%20DETAILS.pdf Début du contrat : Octobre 2024, au plus tard Durée du contrat : 12 mois Les candidatures comprenant un CV scientifique, une lettre de motivation et des lettres de recommandation doivent être envoyées à Anaïs Ollagnier (ollagnier(a)i3s.unice.fr) Date limite : 14 Juin 2024 Laboratoire d'accueil : I3S, Sophia-Antipolis, France Au plaisir de vous lire. ------------------------------------------------------------------------------------------------ In the context of the CIIAM project (Contextual Information Inference for Argument Mining), funded through the France 2030 investment plan managed by the National Research Agency (ANR), as part of the Initiative of Excellence Université Côte d’Azur, aiming to enhance the robustness of argument mining techniques through the synthesis of contextual information relevant to multimodal aspects of communication. We invite doctoral candidates nearing completion of their thesis and young PhD graduates to apply for a postdoctoral position on "Improving Argument Mining through the Synthesis of Contextual Information" (12 months). -------- Context -------- Understanding argumentative structures in natural language inputs is a key step for many tasks in the field of Natural Language Processing (NLP), such as automatic summarization or analysis of political debates. Although significant progress has been made with the advent of pre-trained language models, they do not always grasp all the linguistic knowledge necessary for fine contextual understanding and the establishment of relevant inferences. Faced with these limitations, our project aims to explore the inclusion of linguistic analysis dimension related to pragmatics. This approach is particularly innovative because pragmatics, due to its complexity in formalization, has been scarcely studied from a computational perspective. It is through the use of the latest cutting-edge prompting techniques that we aim to overcome the pitfalls of existing methods, such as cultural variability and implicit knowledge. --------------- To Apply --------------- Detailed subject: https://aollagnier.github.io/publications/CIIAM%20PostDoc%20DETAILS.pdf Contract start: October 2024, at the latest Contract duration: 12 months Applications including a scientific CV, a motivation letter, and recommendation letters should be sent to Anaïs Ollagnier (ollagnier(a)i3s.unice.fr) Deadline: June 14, 2024 Hosting laboratory: I3S, Sophia-Antipolis, France * -- Anaïs OLLAGNIER Junior Fellow in AI 3IA Université Côte d'Azur (Polytech Nice) | I3S | INRIA wimmics team -------------------------------------------- Templiers 1, Bureau 414, 930 Route des Colles, BP 145 06903 Sophia Antipolis Cedex, France anais.ollagnier(a)inria.fr |https://aollagnier.github.io/

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