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[CfP] Third Call for Papers: Applied Sciences (IF: 2.7) Special Issue on "Application of Artificial Intelligence Methods in Processing of Emotions, Decisions and Opinions"
by Ptaszynski Michal 09 Nov '23

09 Nov '23

Dear Colleagues Apologies for cross-posting. This is Michal Ptaszynski from Kitami Institute of Technology, Japan. We are accepting papers for the Applied Sciences journal (Impact Factor: 2.7) special issue on "Application of Artificial Intelligence Methods in Processing of Emotions, Decisions and Opinions". The new deadline for manuscript submission is March 31, 2024, but your paper will be sent for review as soon as it is submitted and will be published shortly after being accepted. We hope you will consider submitting your paper. https://www.mdpi.com/journal/applsci/special_issues/NTMDOE41MY Best regards, Michal PTASZYNSKI, Ph.D., Associate Professor Department of Computer Science Kitami Institute of Technology, 165 Koen-cho, Kitami, 090-8507, Japan TEL/FAX: +81-157-26-9327 michal(a)mail.kitami-it.ac.jp ============================================ Applied Sciences (Impact Factor: 2.7) Special Issue on "Application of Artificial Intelligence Methods in Processing of Emotions, Decisions and Opinions" Special Issue Information During recent years, social infrastructure has become irreversibly linked to the Internet through its everyday manifestations, such as social networking services (Twitter, Facebook, etc.). Every second this new tangible information-based reality provides large amounts of data filled with 1) emotional expressions; 2) people's opinions on various topics; and 3) their reasoning, revealing their decision-making processes. As these three categories are also closely interrelated with each other, they should be studied together to obtain a more robust view on all of the topics involved. This, as never before, provides an opportunity for the development and application of natural language processing methods, in particular those regarding such topics as emotion processing, decision-making, and opinion mining. For this issue, we invite high-quality papers from researchers with an interest in knowing more about those topics and their connection to the world we live in through opinion and sentiment analysis, recommendation systems, web mining, automated decision-making, etc. We also invite papers on the topic of using Natural Language Processing tools and methods to process emotions, metaphors, ethics, or other phenomena related to human activities. List of Topics The Special Issue will invite papers on topics listed, but not limited to the following: - opinion mining - decision support systems - emotion detection - sentiment analysis - natural language processing - computational linguistics - NLP applications - natural language generation - emotional language processing - humor and joke processing - deceptive language detection - emoticon processing - automatic cyberbullying detection - fake news detection - abusive language processing - story generation - poetry generation - cognitive agents Guest Editors Dr. Pawel Dybala Dr. Rafal Rzepka Dr. Michal Ptaszynski Michal Ptaszynski michal.ptaszynski(a)gmail.com

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Call for Shared Task Participation - CASE @ EACL 2024: Climate Activism Stance and Hate Event Detection & previous shared tasks
by ali hürriyetoglu 09 Nov '23

09 Nov '23

We invite the community to participate in the shared task we organize and consider working on data from our previous shared tasks in the scope of the CASE workshop @ EACL 2024 (https://emw.ku.edu.tr/case-2024/). Recent & Active Shared task: *T1: Climate Activism Stance and Hate Event Detection* Hate speech detection and stance detection are some of the most important aspects of event identification during climate change activism events. In the case of hate speech detection, the event is the occurrence of hate speech, the entity is the target of the hate speech, and the relationship is the connection between the two. The hate speech event has targets to which hate is directed. Identification of targets is an important task within hate speech event detection. Additionally, stance event detection is an important part of assessing the dynamics of protests and activisms for climate change. This helps to understand whether the activist movements and protests are being supported or opposed. This task will have three subtasks (i) Hate speech identification (ii) Targets of Hate Speech Identification (iii) Stance Detection. *Codalab Link:* https://codalab.lisn.upsaclay.fr/competitions/16206 <https://codalab.lisn.upsaclay.fr/competitions/16206> Registration: In order to register for the shared task, please send a request in Codalab. The organizers will approve requests on a daily basis. *GitHub Page:* https://github.com/therealthapa/case2024-climate <https://github.com/therealthapa/case2024-climate> *Timeline*: Training & Evaluation data available: Nov 1, 2023 Test data available: Nov 30, 2023 Test start: Nov 30, 2023 Test end: Jan 5, 2024 System Description Paper submissions due: Jan 12, 2024 Notification to authors after review: Jan 26, 2024 Camera ready: Jan 30, 2024 CASE Workshop: 21-22 Mar, 2024 Previous shared tasks for working on regular papers (no official competition), please see the regular paper submission timeline: PT1: MULTILINGUAL PROTEST NEWS DETECTION The performance of an automated system depends on the target event type as it may be broad or potentially the event trigger(s) can be ambiguous. The context of the trigger occurrence may need to be handled as well. For instance, the ‘protest’ event type may be synonymous with ‘demonstration’ or not in a specific context. Moreover, the hypothetical cases such as future protest plans may need to be excluded from the results. Finally, the relevance of a protest depends on the actors as in a contentious political event only citizen-led events are in the scope. This challenge becomes even harder in a cross-lingual and zero-shot setting in case training data are not available in new languages. We tackle the task in four steps and hope state-of-the-art approaches will yield optimal results. Contact person: Ali Hürriyetoğlu (ali.hurriyetoglu(a)gmail.com) Github: https://github.com/emerging-welfare/case-2022-multilingual-event PT2: EVENT CAUSALITY IDENTIFICATION Causality is a core cognitive concept and appears in many natural language processing (NLP) works that aim to tackle inference and understanding. We are interested in studying event causality in the news and, therefore, introduce the Causal News Corpus. The Causal News Corpus consists of 3,767 event sentences extracted from protest event news, that have been annotated with sequence labels on whether it contains causal relations or not. Subsequently, causal sentences are also annotated with Cause, Effect and Signal spans. Our subtasks work on the Causal News Corpus, and we hope that accurate, automated solutions may be proposed for the detection and extraction of causal events in news. Contact person: Fiona Anting Tan (tan.f(a)u.nus.edu) Github: https://github.com/tanfiona/CausalNewsCorpus PT3: MULTIMODAL HATE SPEECH EVENT DETECTION Hate speech detection is one of the most important aspects of event identification during political events like invasions. In the case of hate speech detection, the event is the occurrence of hate speech, the entity is the target of the hate speech, and the relationship is the connection between the two. Since multimodal content is widely prevalent across the internet, the detection of hate speech in text-embedded images is very important. Given a text-embedded image, this task aims to automatically identify the hate speech and its targets. This task will have two subtasks. Contact person: Surendrabikram Thapa (surendrabikram(a)vt.edu) Codalab page: https://codalab.lisn.upsaclay.fr/competitions/16203 Github: https://github.com/therealthapa/case2023_task4 Note: The organizers follows a specific timeline. Please see the Codalab page.

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PhD position in Machine Learning, Data Science and Law
by Spanakis, Jerry (DACS) 08 Nov '23

08 Nov '23

At Maastricht Law & Tech lab<https://www.maastrichtuniversity.nl/about-um/faculties/law/research/law-and…> we are looking for a PhD candidate to work on the intersection of Machine Learning, Data Science and Law. We are explicitly looking for candidates that have proven experience working on NLP and ML. See recent examples of our work [1<https://aclanthology.org/2023.eacl-main.203.pdf>,2<https://aclanthology.org/2023.acl-long.481.pdf>,3<https://arxiv.org/abs/2309.17050>] Deadline is December 10th. The full text of the position is here<https://www.academictransfer.com/en/334212/phd-candidate-position-on-machin…> and attached below. Feel free to reach out if you have questions, enquiries, etc. — Maastricht University invites applications for a fully funded PhD position focused on integrating machine learning and data science techniques with the law. JOB DESCRIPTION Law affects us all, but technology often benefits the wealthy the most. In your project, you will seek to contribute to a better understanding of how technical methods can assist in the application, interpretation, and evaluation of laws, for instance by developing innovative solutions for start-ups and ordinary citizens. Data sources may include legal texts (e.g. laws, court decisions), social media data, or computer code itself. You will work closely with industry partners and public authorities and have tangible real-world impact with your work. The ability to find innovative technical solutions to legal challenges could become a key skill of your future career be it as a researcher, entrepreneur, or engineer. Your project will connect to previous research. In prior research, we have analyzed whether AI can assist in (I) retrieving relevant legal information given a layperson’s question, (ii) detecting vendors on the Dark Web, (iii) measuring where a user’s data ends up when using Android and IOS, (iv) researching cancel culture, and (v) detecting important court decisions. You will undertake PhD research at the intersection of law and computer science under the supervision of professors of the Maastricht Law & Tech Lab. Your primary task is conducting the research for your PhD project. Your exact project will be determined in consultation with you. A small proportion of the appointment may be devoted to teaching activities, which commonly amounts to teaching activities in a period of eight weeks per year. You will be offered the opportunity to collaborate with researchers from different disciplines, including machine learning, data science, and law. You will be part of an exciting, vibrant, and quickly growing community where researchers from different disciplines meet and form interdisciplinary teams that conduct academically and societally relevant research. You will be offered the opportunity to gain insights not only on applying computational techniques, but also on law, regulation, and ethics. For this, you will be encouraged, coached, and allowed to attend courses, conferences and workshops that will add social and legal knowledge to your skillset. PhD researchers participate in the Maastricht University Graduate School of Law. REQUIREMENTS Requirements MSc degree in Computer Science, Machine Learning, or Data Science (or equivalent). Proven experience with applying machine learning, natural language processing and/or data science. Interest in learning about other disciplines, law in particular. Community-friendly team player. Excellent oral and written English communication. Optional: geek-friendly. CONDITIONS OF EMPLOYMENT As PhD candidate at Faculty of Law, you will be employed by the most international university in the Netherlands, located in the beautiful city of Maastricht. In addition, we offer you: Good employment conditions. The position is graded in scale P according to UFO profile Promovendus, with corresponding salary based on experience ranging from €2770,00 and €3539,00 gross per month (based on a full-time employment of 38 hours per week). In addition to the monthly salary, an 8.0% holiday allowance and an 8.3% year-end bonus apply. An employment contract for a period of 12 months with a scope of 1,0 FTE. At Maastricht University, the well-being of our employees is of utmost importance, we offer flexible working hours and the possibility to work partly from home if the nature of your position allows it. You will receive a monthly commuting and internet allowance for this. If you work full-time, you will be entitled to 29 vacation days and 4 additional public holidays per year, namely carnival Monday, carnival Tuesday, Good Friday, and Liberation Day. If you choose to accumulate compensation hours, an additional 12 days will be added. Furthermore, you can personalize your employment conditions through a collective labor agreement (CAO) choice model. As Maastricht University, we offer various other excellent secondary employment conditions. These include a good pension scheme with the ABP and the opportunity for UM employees to participate in company fitness and make use of the extensive sports facilities that we also offer to our students. Last but certainly not least, we provide the space and facilities for your personal and professional development. We facilitate this by offering a wide range of training programs and supporting various well-established initiatives such as 'acknowledge and appreciate'. The terms of employment at Maastricht University are largely set out in the collective labor agreement of Dutch Universities. In addition, local provisions specific to UM apply. For more information, click here.

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Release of the ICNALE Global Rating Archives
by Shin ISHIKAWA 08 Nov '23

08 Nov '23

(Sorry for cross-posting) Dear ML members We are delighted to announce the release of the ICNALE Global Rating Archives V2.0, which is the first public release version. The ICNALE GRA includes analytic/holistic ratings of L2 English learner speeches/essays by 160 raters with varied L1 and occupational backgrounds. It also includes fully edited versions of learner essays. Please download the data from the link below: https://language.sakura.ne.jp/icnale/download.html Additional info is available from the link below: https://language.sakura.ne.jp/icnale/modules.html#5 Thank you. Shin _______________________________ The ICNALE Development Team Dr. Shin ISHIKAWA (he/his) Professor of Applied Linguistics at Kobe University, Japan iskwshin(a)gmail.com

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release of thePxCorpus : A Spoken Drug Prescription Dataset in French for Spoken Language Understanding and Dialogue
by François Portet 08 Nov '23

08 Nov '23

Dear colleagues, We are pleased to announce the release of the PxCorpus, a 4 hours of transcribed and annotated dialogues of drug prescriptions in French acquired through an experiment with 55 participants experts and non-experts in drug prescriptions. This corpus was built in collaboration between the Laboratoire d'Informatique de Grenoble (LIG) the University Hospital of Grenoble (CHU Grenoble) and the Calystene society through a CIFRE project financed by the ANRT (Association Nationale de la Recherche et de la Technologie). PxCorpus is to the best of our knowledge, the first spoken medical drug prescriptions corpus to be distributed. The automatic transcriptions were verified by human effort and aligned with semantic labels to allow training of NLP models. The data acquisition protocol was reviewed by medical experts and permit free distribution without breach of privacy and regulation. ## Overview of the Corpus The experiment has been performed in wild conditions with naive participants and medical experts. In total, the dataset includes 2067 recordings of 55 participants (38% non-experts, 25% doctors, 36% medical practitioners), manually transcribed and semantically annotated. | Category | Sessions | Recordings | Time(m)| |------------------| -------- | ---------- | ------ | | Medical experts | 258 | 434 | 94.83 | | Doctors | 230 | 570 | 105.21 | | Non experts | 415 | 977 | 62.13 | | Total | 903 | 1981 | 262.27 | ## License We hope that that the community will be able to benefit from the dataset which is distributed with an attribution 4.0 International (CC BY 4.0) Creative Commons licence. ## How to cite this corpus If you use the corpus or need more details please refer to the following paper: A spoken drug prescription datset in French for spoken Language Understanding @InProceedings{Kocabiyikoglu2022, author = "Alican Kocabiyikoglu and Fran{\c c}ois Portet and Prudence Gibert and Hervé Blanchon and Jean-Marc Babouchkine and Gaëtan Gavazzi", title = "A spoken drug prescription datset in French for spoken Language Understanding", booktitle = "13th Language Ressources and Evaluation Conference (LREC 2022)", year = "2022", location = "Marseille, France" } a more complete description of the corpus acquisition is available on arxiv @misc{kocabiyikoglu2023spoken, title={Spoken Dialogue System for Medical Prescription Acquisition on Smartphone: Development, Corpus and Evaluation}, author={Ali Can Kocabiyikoglu and François Portet and Jean-Marc Babouchkine and Prudence Gibert and Hervé Blanchon and Gaëtan Gavazzi}, year={2023}, eprint={2311.03510}, archivePrefix={arXiv}, primaryClass={cs.CL} } ## Download The corpus can be found in the Zenodoo Catalogue under the following links and references: *PxCorpus : A Spoken Drug Prescription Dataset in French for Spoken Language Understanding and Dialogue* https://zenodo.org/doi/10.5281/zenodo.6482586 -- François PORTET Professeur - Univ Grenoble Alpes Laboratoire d'Informatique de Grenoble - Équipe GETALP Bâtiment IMAG - Office 333 700 avenue Centrale Domaine Universitaire - 38401 St Martin d'Hères FRANCE Phone: +33 (0)4 57 42 15 44 Email:francois.portet@imag.fr www:http://membres-liglab.imag.fr/portet/

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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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[CFP] Call for papers for AAAI workshop on brain encoding and decoding
by jysen sun 07 Nov '23

07 Nov '23

Dear colleagues, I would be happy to announce that the first Artificial Intelligence for Brain Encoding and Decoding (AIBED) workshop will be held in conjunction with AAAI on February 26, 2024 at New Orleans, U.S. We welcome paper submissions and participations for this workshop. Here is the information. This workshop aims to explore the intersection of AI and neuroscience, focusing on how AI, particularly deep artificial neural networks, can facilitate the encoding and decoding of brain activities. We will first delve into the principles of brain encoding and decoding, examining how the brain processes and encodes information into neural signals, and how these signals can be decoded to understand cognition. Next, we will discuss the challenges in encoding and decoding high-dimensional neural imaging data, including but not limited to the complexity of brain signal representations, scarcity of data annotations, and the need for model generalizability. Finally, we will consider the implications of these AI-driven advances in brain encoding and decoding for neuroscience, including understanding cognitive functions, diagnosing neurological disorders, and developing brain-computer interfaces Topics 1. Understanding Brain Encoding and Decoding: - Analyzing the processes of brain information processing and neural signal encoding - Utilizing AI to model complex neural processes and facilitate cognition understanding - Decoding from brain activities to reconstruct perceived or imagined linguistic, visual and audio information with AI 2. Addressing Challenges in Processing Neural Imaging Data: - Proposing AI solutions to process neural images, such as denoising, registering and slicing etc. - Leveraging AI’s proficiency in managing high-dimensional data to innovate solutions of representing brain signals 3. Implications in Neuroscience: - Considering the impact of AI developments on cognitive neuroscience - Aiding in diagnosing neurological disorders with AI Format and Attendance This will be a 1-day workshop with keynotes, poster presentations, and panel discussions. We will invite keynote speakers and all the authors who get papers accepted. Other AAAI attendees who are interested can also attend following AAAI’s related policy. Submission Requirements We accept one-page abstract with posters, as well as short papers with no more than 4 pages and long papers with no more than 7 pages. *Submission Site Information*: https://openreview.net/group?id=AAAI.org/2024/Workshop/AIBED Offiical website of workshop: https://sites.google.com/view/aibed2024/ For more questions about this workshop please contact aibed2024(a)outlook.com <aibed(a)outlook.com> . Workshop Chairs: Prof. Dr. Marie-Francine Moens, sien.moens(a)kuleuven.be Prof. Dr. Shaonan Wang, shaonan.wang(a)nlpr.ia.ac.cn Dr. Jingyuan Sun, jingyuan.sun(a)kuleuven.be Workshop Committee: Mingxiao Li, mingxiao.li(a)kuleuven.be Zijiao Chen, zijiao.chen(a)u.nus.edu Jiaxin Qing, jqing(a)ie.cuhk.edu.hk Xinpei Zhao, zhaoxinpei17(a)mails.ucas.ac.cn Tiedong Liu, tiedong.liu(a)u.nus.edu Prof. Dr. Wei Huang, lembert1990(a)163.com Kind regards Dr. Jingyuan Sun

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SCI-CHAT 2024: Call for Participation & Papers for Workshop on Simulation of Conversational Intelligence in Chat
by Gerasimos Lampouras 07 Nov '23

07 Nov '23

tl;dr: - submission deadline for research track paper via Softconf: December 18th 2023 - submission deadline for research track submissions already reviewed via ARR: January 17th 2024 - submission deadline for shard task systems: January 20th 2024 - submission deadline for shard task system descriptions via SoftConf: January 26th 2024 https://sites.google.com/view/dialogue-evaluation/ Call for Papers The aim of this workshop is to bring together experts working in the area of open-domain dialogue. In this speedily advancing research area many challenges still exist, such as learning information from conversations, engaging in realistic and convincing simulation of human intelligence, reasoning, and so on. SCI-CHAT follows previous workshops on open domain dialogue, but with a focus on the simulation of intelligent conversation, including the ability to follow a challenging topic over a multi-turn conversation, the ability to posit questions, refuting and reasoning with live human evaluation employed as the primary mechanism for evaluating models. The workshop will include a research track and shared task: SCI-CHAT's research track aims to explore recent advances and challenges in open-domain dialogue research. Researchers working on all aspects of open-domain dialogue are invited to submit papers on recent advances, resources, tools, analysis, evaluation, and challenges on the broad theme of open-domain dialogues. The topics of the workshop include but are not limited to the following: - Intelligent conversation, chit-chat, open-domain dialogue; - Automatic and human evaluation of open-domain dialogue; - Limitations, risks and safety in open-domain dialogue; - Instruction-tuned and instruction-enabled models; - Any other topic of interest to the dialogue community. SCI-CHAT's shared task will focus on simulating intelligent conversations; participants will be asked to submit (access to the APIs of) automated dialogue agents with the aim of carrying out nuanced conversations over multiple dialogue turns. Participating systems will be interactively evaluated in a live human evaluation. All data acquired within the context of the shared task will be made public, providing an important resource for improving metrics and systems in this research area. Submission guidelines: Authors are invited to submit their unpublished work that represents novel research through either direct submission or ARR commitment. Papers should consist of up to 8 pages of content, plus unlimited pages for references and appendix. Authors should make use of the EACL Latex Template <https://2023.eacl.org/calls/styles/> alongside supplementary materials, including technical appendices, links to source code, datasets, and multimedia appendices. Papers can also be submitted as non-archival, so that their content can be reused for other venues by adding "(NON-ARCHIVAL)" to the title of their submission. Previously published work can also be submitted as non-archival in the same way, with the additional requirement to state such on the first page. - Direct paper submissions must be submitted through SoftCon submission link: https://softconf.com/eacl2024/SCI-CHAT-2024/ Multiple submissions of the same paper to more EACL workshops are forbidden. All papers will be double-blind peer-reviewed, by at least 2 program committee members. As such, all submissions, including the main paper and its supplementary materials, should be fully anonymized. For more information on formatting and anonymity guidelines, please refer to EACL guidelines <https://eacl.org/index.html>. Organizers - Yvette Graham (Trinity College Dublin, Ireland) - Qun Liu (Huawei Noah's Ark Lab, China) - Gerasimos Lampouras (Huawei Noah's Ark Lab,UK) - Ignacio Iacobacci (Huawei Noah's Ark Lab, UK) - Sinead Madden (Trinity College Dublin, Ireland) - Haider Khalid (Trinity College Dublin, Ireland) - Rameez Qureshi (Trinity College Dublin, Ireland) Important Dates Regarding Research Track: - Research paper via Softconf: December 18th 2023 - Pre-reviewed ARR commitment deadline: January 17th 2024 - Notification of research paper acceptance: January 20th, 2024 - Camera-ready papers due: January 30th 2024 Regarding Shared Task: - Release of training and development data: November 9th 2023 - Release of baseline systems: November 9th 2023 - Preliminary System submission deadline: January 13th 2024 (optional - if you want help testing your API, please submit early) - System submission (API) deadline: January 20th 2024 - System description paper via SoftConf: January 26th 2024 - Camera-ready papers due: January 30th 2024 Overview of results at one-day workshop: March 21 or 22, 2024 CONTACT: sci-chat(a)adaptcentre.ie

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PhD position on Explainable NLU at the University of Copenhagen
by Isabelle Augenstein 07 Nov '23

07 Nov '23

The Natural Language Processing Section at the Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD position in Explainable Natural Language Understanding with a start date of 1 September 2024. The application deadline is 1 February 2024. Applications for the position can be submitted via UCPH's job portal<https://candidate.hr-manager.net/ApplicationInit.aspx/?cid=1307&departmentI…>. The Natural Language Processing Section<https://di.ku.dk/english/research/nlp/> provides a strong, international and diverse environment for research within core as well as emerging topics in natural language processing, natural language understanding, computational linguistics and multi-modal language processing. It is housed within the main Science Campus, which is centrally located in Copenhagen. The successful candidate will join Isabelle Augenstein’s Natural Language Understanding research group<http://www.copenlu.com/>. The Natural Language Processing research environment at the University of Copenhagen is internationally leading, as e.g. evidenced by it being ranked 2nd in Europe according to CSRankings. The position is offered in the context of an ERC Starting Grant held by Isabelle Augenstein on ‘Explainable and Robust Automatic Fact Checking (ExplainYourself)’. ERC Starting Grant is a highly competitive funding program by the European Research Council to support the most talented early-career scientists in Europe with funding for a period of 5 years for blue-skies research to build up or expand their research groups. The project team will consist of the principle investigator, three PhD students and two postdocs, collaborators from CopeNLU as well as external collaborators. The role of the PhD student to be recruited in this call will be to research methods for generating faithful free-text explanations of NLU models in collaboration with the larger project team. More information about the project can also be found here<http://www.copenlu.com/talk/2022_11_erc/>. Informal enquiries about the positions can be made to Professor Isabelle Augenstein, Department of Computer Science, University of Copenhagen, e-mail: augenstein(a)di.ku.dk<mailto:augenstein@di.ku.dk?subject=PhD%20position%20on%20Explainable%20Natural%20Language%20Understanding>. Isabelle Augenstein, Dr. Scient., Ph.D. Professor and Head of the NLP Section, Department of Computer Science (DIKU) Co-Lead, Pioneer Centre for Artificial Intelligence University of Copenhagen Østervold Observatory Øster Voldgade 3 1350 Copenhagen augenstein(a)di.ku.dk<mailto:augenstein@di.ku.dk> http://isabelleaugenstein.github.io/

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PhDs in NLP at Queen Mary University of London for CSC candidates
by Matthew Purver 07 Nov '23

07 Nov '23

The school of Electronic Engineering and Computer Science at Queen Mary University of London is inviting applications for several PhD Studentships in specific areas in Electronic Engineering and Computer Science -- including several in natural language processing -- co-funded by the China Scholarship Council (CSC). CSC is offering a monthly stipend to cover living expenses and QMUL is waving fees and hosting the student. These scholarships are available only for Chinese candidates. Projects available include: - Emerging methods for analysing Pretrained Foundation Models - The shape of words - Interpretable language models for healthcare - Personalisation and temporal reasoning in LLMs wth applications in healthcare - Coreference resolution in the era of large language model - Interactive adaptation for large language models - Towards personalising and debiasing online content moderation For details on the available projects and supervising faculty please visit: http://eecs.qmul.ac.uk/phd/phd-studentships/csc-phd-studentships/csc-phd-st… -- Matthew Purver - http://www.eecs.qmul.ac.uk/~mpurver/ Computational Linguistics Lab - http://compling.eecs.qmul.ac.uk/ Cognitive Science Research Group - http://cogsci.eecs.qmul.ac.uk/ School of Electronic Engineering and Computer Science Queen Mary University of London, London E1 4NS, UK *My working days for QMUL are **Tuesday-Thursday**; responses to mail on other days may be delayed.*

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2025

2024

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2022