May 2023 - Corpora - ELRA lists

Call For Papers: The SIGIR '23 Workshop on Knowledge Discovery from Unstructured Data in Financial Services
by Xiaodan Zhu 06 May '23

06 May '23

The SIGIR '23 Workshop on Knowledge Discovery from Unstructured Data in Financial Services (KDF) Artificial intelligence (AI) and information retrieval (IR) systems and techniques have been widely adopted in financial services to tackle various tasks, such as information retrieval from business documents, retrieval from non-textual content like tables and graphs, recommending financial products and services to customers, providing decision support for investment practices, automating of due diligence protocols, detecting fraudulent transactions, financial sentiment analysis on social media, and understanding Environmental, Social and Governance (ESG) impact on investment practices. Knowledge from IR systems can help augment human intelligence. However, discovering and extracting the knowledge conveyed inside unstructured financial data, like SEC filings, prospectuses, business reports, and other enterprise documents are extremely challenging due to the massive volume of data, large variation in the data format, low signal-to-noise ratio, scarcity of expert annotated datasets, task ambiguity, hurdles regarding data integrity and privacy, robustness against domain shift, and high-performance requirements set by industry and regulatory standards. Manual extraction of knowledge is usually inefficient, error-prone, and inconsistent, so it is one of the key technical bottlenecks for financial services companies to accelerate their operating productivity. These challenges and issues call for robust artificial intelligence, information retrieval, and machine learning algorithms and systems to help. The automated processing of unstructured data to discover knowledge from complex financial documents requires bringing together a suite of techniques such as natural language processing, information retrieval, semantic analysis, and complex reasoning. In addition, how knowledge is captured and represented, synthesized across diverse sources, and used within AI systems, is crucial to developing effective solutions in financial services. Furthermore, based on the reflections and feedback from our past KDF workshops, the 2023 workshop is particularly interested in multi-modal understanding of financial documents, retrieving and reasoning over tabular data within financial documents, and financial domain-specific representation learning. The workshop will be composed of three components: invited talks, paper presentations, along with a shared task competition. We cordially welcome researchers, practitioners, and students from academic and industrial communities who are interested in the topics to participate and/or submit their original work. The workshop will be a hybrid event – supporting both in-person and virtual participation. Topics of Interest The topics of the workshop include, but are not limited to, the following areas: - AI and IR technologies for business document understanding for financial corpora, including searching and question answering systems, understanding and reasoning over non-textual content such as tables and graphs; - representation learning, and distributed representation learning and encoding in natural language processing for financial documents; - language modeling on financial corpora including tabular and numerical data, and multi-modal modeling; - multi-source knowledge integration and fusion, and knowledge alignment and integration from heterogeneous data; - reconciling unstructured knowledge with structured knowledge and human expertise; - named-entity disambiguation, recognition, resolution, relationship discovery, ontology learning and extraction in financial and business documents; - AI-assisted domain data tagging, labeling, and annotation for IR tasks; automatic data extraction from financial filings and quality verification; - corporate ESG event discovery, evaluation, and impact assessment; - event discovery from alternative data and impact on corporate equity pricing; - AI and IR systems for financial risk assessment on financial legal documents such as contracts and prospectuses; - verifying facts and statements generated by large pre-trained language models using IR and knowledge discovery; - IR or QA techniques and applications on financial documents leveraging large language models. Submission Guidelines We invite submissions of relevant work that be of interest to the workshop. All submissions must be original contributions that have not been previously published and that are not currently under review by other conferences or journals. Submissions will be peer reviewed, single-blinded. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. All submissions must be in PDF format and follow the current ACM two-column conference format https://www.acm.org/publications/proceedings-template. We accept two types of submissions: - full research paper: no longer than 9 pages (including references, proofs, and appendixes). - short/poster paper: no longer than 4 pages (including references, proofs, and appendixes). Submission will be accepted via Microsoft CMT https://cmt3.research.microsoft.com/KDF2023/. All accepted papers will be presented in the workshop. Submissions will be non-archival, and the authors may post their work on arXiv or other online repositories. Important Dates - Paper abstract due (optional): May 1, 2023 AoE - Paper submission deadline: May 21, 2023 AoE - Submission notification date: May 31, 2023 - Workshop: July 27, 2023 Organizing Committee - Sameena Shah - JPMorgan AI Research - Xiaodan Zhu - Queen's University - Wenhu Chen - University of Waterloo - Manling Li - University of Illinois Urbana-Champaign - Armineh Nourbakhsh - JPMorgan AI Research - Xiaomo Liu - JPMorgan AI Research - Zhiqiang Ma - JPMorgan AI Research - Charese Smiley - JPMorgan AI Research - Yulong Pei - JPMorgan AI Research - Akshat Gupta - JPMorgan AI Research Workshop Website http://kdf-workshop.github.io/kdf23 Contact For general inquiries about KDF, please write to the organizers at kdf.workshop(a)gmail.com. <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_cam…> Virus-free.www.avg.com <http://www.avg.com/email-signature?utm_medium=email&utm_source=link&utm_cam…> <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>

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Call for Shared Task Participation: Event Causality Identification with Causal News Corpus at CASE @ RANLP 2023
by ali hürriyetoglu 06 May '23

06 May '23

Competition Website: https://codalab.lisn.upsaclay.fr/competitions/11784 Please contact the organizer at tan.f(a)u.nus.edu with your title starting with “CNC ST”, or post questions at the Forum page in Codalab. FIRST CALL FOR PARTICIPATION CASE-2023 Shared Task: Event Causality Identification with Causal News Corpus ================================================ We invite you to participate in the CASE-2023 Shared Task: Event Causality Identification with Causal News Corpus. The task is being held as part of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022). All participating teams will be able to publish their system description paper in the workshop proceedings published by ACL. Workshop Website: https://emw.ku.edu.tr/case-2023/ <https://emw.ku.edu.tr/case-2022/> Motivation ================================================ 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 to study event causality in 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. Task Overview ================================================ We focused on two subtasks relevant to Event Causality Identification: - Subtask 1: Causal Event Classification – Does an event sentence contain any cause-effect meaning? - Subtask 2: Cause-Effect-Signal Span Detection – Which consecutive spans correspond to cause, effect or signal per causal sentence? - Subtask 2.1: Cause-Effect Span Detection – This subtask identifies the spans corresponding to cause and effect per sentence. - Subtask 2.2: Signal Span Detection – This subtask identifies the spans corresponding to the signal, or causal connective, per cause and effect relation. Participants may design solutions that work on a single, multiple or all subtasks concurrently. Participants are also allowed to combine Subtask 1 and 2 annotations for either task. However, the target labels of development and test sets should not be introduced during training in their set up in any way (E.g. even for data augmentation). This is the second iteration of this shared task. The leaderboard from last year is available at https://codalab.lisn.upsaclay.fr/competitions/2299. There are changes for both Subtask 1 and 2 data: - Added more data. Also revised annotations from previous launch - Changed traditional P, R, F1 calculations to use FairEval calculations instead ( https://huggingface.co/spaces/hpi-dhc/FairEval/blob/main/README.md) Data Content ================================================ Our work extends a prior socio-political news corpus to annotate if event-containing sentences have causal relations or not. Our data sizes and splits are described as follows: - Subtask 1: Causal Event Classification -- 869 news documents and 3,767 English sentences were annotated with labels on whether it contains causal relations or not. The current data splits are: 3,075 training, 340 development, 352 test. - Subtask 2: Cause-Effect-Signal Span Detection – Positive causal sentences from Subtask 1 were retained and annotated with Cause-Effect-Signal spans. We annotated 1,982 sentences with 2,754 causal relations. There can be multiple relations per sentence. The data splits for causal relations are: 2,257 training, 249 development, 248 test. Task Repository: https://github.com/tanfiona/CausalNewsCorpus Codalab Site: https://codalab.lisn.upsaclay.fr/competitions/11784 Important Dates ================================================ Training & Validation data available: May 01, 2023 Test data available: Jun 15, 2023 Test start: Jun 15, 2023 Test end: Jun 30, 2023 System Description Paper submissions due: Jul 10, 2023 Notification to authors after review: Aug 05, 2023 Camera ready: Aug 25, 2023 Workshop period @ RANLP: Sep 7-8, 2023 Organization ================================================ - Fiona Anting Tan, Institute of Data Science/ National University of Singapore, Singapore - Ali Hürriyetoğlu, Koc University, Turkey - Tommaso Caselli, Rijksuniversiteit Groningen, Netherlands - Nelleke Oostdijk, Radboud University - Tadashi Nomoto, National Institute of Japanese Literature, Japan - Onur Uca, Mersin University - Iqra Ameer, Centro de Investigación en Computación/ Instituto Politécnico Nacional, Mexico - Hansi Hettiarachchi, Birmingham City University, United Kingdom - Farhana Ferdousi Liza, University of East Anglia, United Kingdom - Tiancheng Hu, ETH Zürich, Switzerland Please contact the organizer at tan.f(a)u.nus.edu with your title starting with “CNC ST”, or post questions at the Forum page in Codalab.

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First Call for Papers: GenBench, the first workshop on generalisation (benchmarking) in NLP @ EMNLP 2023
by Verna Dankers 05 May '23

05 May '23

*Call for Papers: GenBench, the first workshop on generalisation (benchmarking) in NLP* *Workshop description*The ability to generalise well is often mentioned as one of the primary desiderata for models of natural language processing. It is crucial to ensure that models behave robustly, reliably and fairly when making predictions about data that is different from the data that they were trained on. Generalisation is also important when NLP models are considered from a cognitive perspective, as models of human language. Yet, there are still many open questions related to what it means for an NLP model to generalise well and how generalisation should be evaluated. The first GenBench workshop aims to serve as a cornerstone to catalyse research on generalisation in the NLP community. In particular, the workshop aims to: - Bring together different expert communities to discuss challenging questions relating to generalisation in NLP; - Crowd-source a collaborative generalisation benchmark hosted on a platform for democratic state-of-the-art (SOTA) generalisation testing in NLP The first GenBench workshop on generalisation (benchmarking) in NLP will be co-located with EMNLP 2023. *Submission types*We call for two types of submissions: regular workshop submissions and collaborative benchmarking task submissions. The latter will consist of a data/task artefact and a companion paper motivating and evaluating the submission. In both cases, we accept archival papers and extended abstracts. *1. Regular workshop submissions*Regular workshop submissions present papers on the topic of generalisation (see examples listed below) but are not intended to be included on the GenBench evaluation platform. Regular workshop papers may be submitted as an archival paper when they report on completed, original and unpublished research; or as a shorter extended abstract. More details on this category can be found below. Topics of interest include, but are not limited to: - Opinion or position papers about generalisation and how it should be evaluated; - Analyses of how existing or new models generalise; - Empirical studies that propose new paradigms to evaluate generalisation; - Meta-analyses that investigate how results from different generalisation studies compare to one another; - Meta-analyses that study how different types of generalisation are related; - Papers that discuss how generalisation of LLMs can be evaluated without access to training data; - Papers that discuss why generalisation is (not) important in the era of LLMs; - Studies on the relationship between generalisation and fairness or robustness. If you are unsure whether a specific topic is well-suited for submission, feel free to reach out to the organisers of the workshop at genbench(a)googlegroups.com. *2. Collaborative Benchmarking Task submissions*Collaborative benchmarking task submissions consist of a data/task artefact and a paper describing and motivating the submission and showcasing it on a select number of models. We accept submissions that introduce new datasets, resplits of existing datasets along particular dimensions, or in-context learning tasks, with the goal of measuring generalisation of NLP models. We especially encourage submissions that focus on: - Generalisation in the context of fairness and inclusivity; - Multilingual generalisation; - Generalisation in LLMs, where we have no control over the training data. Each submission should contain information about the data (URIs, format, preprocessing), model preparation (finetuning loss, ICL prompt templates), and evaluation metrics. These will be defined either in a configuration file or in code. More details about the collaborative benchmark task submissions and example submissions can be found on our website: genbench.org/cbt. Participants proposing previously unpublished datasets or splits may choose to submit an archival paper or an extended abstract. Generalisation evaluation datasets that have already been published elsewhere (or will be published at EMNLP 2023) can be submitted to the platform, as well, but only through an extended abstract, citing the original publication. We allow dual submissions with EMNLP. For more information, see below. If you are in doubt about whether a particular type of dataset is suitable for submission, please consult the information page on our website, or reach out to the organisers of the workshop at genbench(a)googlegroups.com. *Archival vs extended abstract*Archival papers are up to 8 pages excluding references and report on completed, original and unpublished research. They follow the requirements of regular EMNLP 2023 submissions. Accepted papers will be published in the workshop proceedings and are expected to be presented at the workshop. The papers will undergo double-blind peer review and should thus be anonymised. Extended abstracts can be up to 2 pages excluding references and may report on work in progress or be cross-submissions of work that has already appeared in another venue. Abstract titles will be posted on the workshop website but will not be included in the proceedings. *Submission instructions*For both archival papers and extended abstracts, we refer to the EMNLP 2023 website for paper templates. Additional requirements for both regular workshop papers and collaborative benchmarking task submissions can be found on our website. All submissions can be submitted through OpenReview; the link can be found on our website. We also accept regular workshop submissions (papers of category 1) through the ACL Rolling Review system. Authors that have their ARR reviews ready may submit their papers and reviews for consideration to the workshop. *Important dates*- August 1, 2023 – Sample data submission deadline - September 1, 2023 – Paper submission deadline - September 15, 2023 – ARR submission deadline - October 6, 2023 – Notification deadline - October 18, 2023 – Camera-ready deadline - December 6/7, 2023 – Workshop Note: all deadlines are 11:59 PM UTC-12:00 *Dual submissions*We allow dual submissions with EMNLP and encourage relevant papers that were dual-submitted and accepted at EMNLP to redirect to a non-archival extended abstract submission. We furthermore welcome submissions of extended abstracts that describe work already presented at an earlier venue, both in the collaborative benchmarking task and in the regular submission track. *Preprints*We do not have an anonymity deadline. Preprints are allowed, both before the submission deadline as well as after. *Contact* Email address: genbench(a)googlegroups.com Website: <goog_1407501456>genbench.org/workshop *On behalf of the GenBench team,*Dieuwke Hupkes Khuyagbaatar Batsuren Koustuv Sinha Amirhossein Kazemnejad Christos Christodoulopoulos Ryan Cotterell Elia Bruni Verna Dankers

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Call for papers, SIGDIAL 2023 Workshop Connecting Multiple Disciplines to AI Techniques in Interaction-centric Autism Research and Diagnosis (ICARD)
by Amanda Stent 05 May '23

05 May '23

Call for papers, SIGDIAL 2023 Workshop Connecting Multiple Disciplines to AI Techniques in Interaction-centric Autism Research and Diagnosis (ICARD) We welcome submissions on one or more of the following topics: Multimodal information processing of interactions involving people with symptoms of autism Datasets of autism behavior: child-child, child-parent, child-researcher and multi-party conversation Application of Social science and AI techniques in autism understanding and diagnosis Speech recognition for autism speech Conversational tools for language development in autism Dialogue modeling for autism diagnosis and intervention AI-mediated tools for improving cognitive and social development in autism Applications, demos, and resources for studying social interaction and dialogue in autism Submissions We welcome reports of original research in the form of two types: Long papers (8 pages + references) Short papers (4 pages + references) We also welcome submission of non-archival one page abstracts describing work in progress. We encourage all authors to include relevant discussions of ethical considerations and impact in the body of the paper. Non-archival Option Authors have the option of submitting previously unpublished research as non-archival, meaning that only the abstract will be published in the proceedings. We expect these submissions to describe the same quality of work as archival submissions. These will be reviewed following the same procedure as archival submissions. Submission Format All long, short, and abstract submissions must follow the two-column ACL format , which are available as an Overleaf template and also downloadable directly (Latex and Word). Please refer to the SIGDIAL 2023 website for the most recent version of the templates. Submissions must conform to the official ACL style guidelines, which are contained in these templates. Submissions must be electronic, in PDF format. All submissions should be anonymized to facilitate double blind reviewing. Submissions that do not adhere to the author guidelines or ACL policies will be rejected without review. Important Dates Submission deadline: June 15, 2023 Author notification: July 14, 2023 Camera-ready deadline: August 14, 2023 Workshop date: September 12, 2023 All deadlines are 11.59 pm AOE time.

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Job Announcement: Associate Professor of Linguistics with a Specialization in Computational Linguistics (University of Olso, Norway)
by Luca Onnis 05 May '23

05 May '23

Dear colleagues, Please, could you forward the job announcement below to all who might be interested? Job Title: Associate Professor of Linguistics with a Specialization in Computational Linguistics Location: Department of Linguistics and Scandinavian Studies, University of Oslo, Norway Application Deadline: 31st October 2023 URL: < https://www.jobbnorge.no/en/available-jobs/job/243214/associate-professor-o… > Description: A permanent position of Associate Professor of Linguistics with a specialization in Computational Linguistics is available at the Department of Linguistics and Scandinavian Studies, University of Oslo. (Associate Professor is the entry-level in Norway; moreover, it is possible to apply for promotion to Full Professor after starting the job.) General linguistics at the department covers all the discipline’s core areas (phonetics, phonology, morphology, syntax, semantics, pragmatics), and a range of methodological approaches, including corpus linguistics and experimental linguistics with a designated focus on the promotion of open science. Resources at the department include the Socio-Cognitive Lab (advanced audiovisual system, eye-trackers, and EEG), and we maintain close ties with the TextLab (corpora, databases, and other digital resources) at the faculty level. The successful candidate is expected to initiate and lead research, supervise PhD and MA candidates, and participate in teaching and in exam setting and assessment at all levels. They are also expected to carry out administrative duties in accordance with the needs of the Department. Qualification requirements - Ph.D. or equivalent academic qualifications within linguistics or another discipline related to the profile of the position. - Documented experience with research in computational linguistics that engages with questions from general linguistics (e.g., phonetics, phonology, morphology, syntax, semantics, pragmatics). - An ability to contribute to teaching at all levels, including general courses at the BA level and more advanced BA and MA courses in computational linguistics. - Documented pedagogical skills (either a teaching course certificate or based on teaching experience) and a willingness to take active part in academic leadership and administration. - Documented potential for project acquisition - Excellent English language skills, both spoken and written - Personal suitability and motivation for the position The following qualifications will count in the assessment of the applicants: - Academic qualifications and academic production (publications, tools, programs, libraries, etc) relevant to the advertised position, with emphasis on works published within the last 5 years. Originality and innovative thinking will be weighted more heavily than quantity. - International peer-reviewed publications - Experience with research projects - Effort to promote open science, e.g. through open data, open materials, shared code, or preregistrations. - Potential to contribute to the long-term development of the academic and research environment at the Department - Pedagogical qualifications, documented results from teaching and supervision, and disposition to inspire students - Interest and ability in leadership and administration - Ability to create and contribute to a positive environment for collaboration - Experience with and ability to build international networks - Skills in popular dissemination, public outreach, and innovation We offer: - Salary NOK 615 000 - 714 000 per annum depending on qualifications - A professionally stimulating working environment - Membership in the Norwegian Public Service Pension Fund - Attractive welfare benefits - The opportunity to apply for promotion to a full professorship at a later stage For more information on the position and how to apply, see the full job announcement at the application link provided below. Web Address for Applications: < https://www.jobbnorge.no/en/available-jobs/job/243214/associate-professor-o… > We would like to highlight the following three aspects of the job announcement: - in spite of the title (Associate Professor), this is an entry-level position in the Norwegian system; newly minted PhDs are eligible to apply, but their thesis must have been submitted by the application deadline, which should be documented; - the position is permanent/tenured; - applicants are not required to know Norwegian (or another Scandinavian language) by the start date, and the faculty provides support for learning Norwegian after arriving in Oslo.

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PhD Position on Strategies for improving Neural Dialogue Models generation
by Marco Guerini 05 May '23

05 May '23

---- Apologies for cross-posting. ---- The Language and Dialogue Technologies (LanD) group at Fondazione Bruno Kessler <https://www.fbk.eu/en/> (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*: Strategies for improving Neural Dialogue Models generation *DESCRIPTION*: Conversational agents are experiencing a surge in interest given the continuous release of new models and the ever evolving scenario of NLG. Still, the actual focus is mainly on model size, training data size and prompt engineering. The interaction of these elements with related aspects, such as decoding strategies, knowledge guided generation, data quality, knowledge distillation -just to mention a few- can help in improving the models, especially for better factuality, reducing hallucination and increasing coherence among dialogue turns. The goal of this PhD Thesis is to overcome the shortcomings of present large language models by incorporating novel strategies for better generation. *CONTACTS*: guerini(a)fbk.eu, jacopo.staiano(a)unitn.it *COMPLETE DETAILS AVAILABLE AT*: https://iecs.unitn.it/education/admission/call-for-application *IMPORTANT DATES:* The deadline for application is May 30, 2023, hrs. 04:00 PM (CEST) *FURTHER INFORMATION: *For preliminary interviews, and should you need further information about the position, please contact Marco Guerini ( guerini(a)fbk.eu) and Jacopo Staiano (jacopo.staiano(a)unitn.it). Best Regards, Marco Guerini -- Marco Guerini, PhD www.marcoguerini.eu

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NEJLT: Call for ACL/ICML-reviewed papers with accelerated processing
by Leon Derczynski 05 May '23

05 May '23

CALL FOR PAPERS WITH ACCELERATED REVIEW The Northern European Journal of Language Technology (NEJLT) invites submissions of excellent research papers and letters on language technology. NEJLT invites authors of papers reviewed at ACL 2023 or ICML 2023 to submit their manuscripts and reviews for accelerated processing. Articles accepted in NEJLT are published in the ACL Anthology. https://www.nejlt.org NEJLT is a global journal that publishes peer-reviewed language technology and computational linguistics research on all languages. ### What's special about NEJLT? * Re-use reviews: We welcome revised manuscripts submitted with prior reviews to a fast-track review process. See: https://www.nejlt.org/authorinfo/#sticky * Customised review: Specify a "type" for your paper at submission, that determines how your paper is reviewed * "Letter" format submission: Comments, positions, letters, or small experiments also welcomed as very short articles * Free to submit, free to publish, free to read ### SUBMISSION TYPES NEJLT accepts (1) full articles, and (2) letters. (1) Full articles are to be given a subtype. The types available at NEJLT are: * Computationally-aided linguistic analysis * NLP engineering experiment paper * Reproduction paper * Resource paper * Position paper * Survey Paper Other works are welcome - contact the editor. (2) NEJLT Letters on computational linguistics and natural language processing may be up to six page words long, and are given a special, dedicated review process. Submissions directly to NEJLT via the journal website are welcome at any time. More information about submission types and information for authors is at: https://www.nejlt.org/authorinfo/ ### SCOPE NEJLT invites manuscripts from anywhere in the world that present excellent research in the field of language technology and natural language processing. Work on all languages is welcome. * Language focus: * Global; no specific focus. Research on all and any languages is invited. * Topics of interest: including but not limited to * Cognitive Modeling and Psycholinguistics * Computational Social Science and Social Media * Dialogue and Interactive Systems * Discourse and Pragmatics * Efficient NLP * Ethics and NLP * Generation of language * Information Extraction * Information Retrieval and Text Mining * Interpretability and Analysis of Models for NLP * Language Grounding to Vision, Robotics and Beyond * Language Modelling * Theory and Formalism in NLP (Linguistic and Mathematical) * Machine Learning for NLP * Machine Translation * Model Preferences and Behaviors * NLP Applications * Phonology, Morphology and Word Segmentation * Question Answering * Resources and Evaluation * Semantics: Lexical * Semantics: Sentence, Paragraph, and Discourse level * Semantics: Textual Inference and Other Areas of Semantics * Sentiment Analysis, Stylistic Analysis, and Argument Mining * Speech and Multimodality * Summarization * Syntax: Tagging, Chunking and Parsing The editor-in-chief of NEJLT is appointed by the North European Association for Language Technology. This geographical connection gives the journal its name, though the journal itself does not have a Northern European language focus. More on NEJLT's scope is at: https://www.nejlt.org/ ### REVIEWING NEJLT is committed to rapid and fair reviewing. NEJLT strives to preserve anonymity throughout the review process. The journal also invites revised resubmissions from select events, including the reviews from those events, including ACL, EMNLP, NAACL, EACL, AACL, and NeurIPS. For details, see: https://www.nejlt.org/review/ ### ABOUT THE JOURNAL NEJLT publishes in the field of language technology, i.e. Natural Language Processing, Computational Linguistics, and related topics. Research focused on any natural language is invited. NEJLT invites both journal articles and academic letters, and has a multi-iteration reviewing process, where revisions are a possibility. The reviewing philosophy of the journal is to minimise reviewing biases, and also to provide constructive, helpful feedback during the review process. NEJLT is a global journal with global focus. The journal’s publisher is located in Northern Europe, hence its name, and supports the journal without charge, enabling open access publication with no costs. NEJLT is indexed by many publication indexing services, and ranked by many national bibliographic ranking systems. NEJLT accepts submissions continuously all year round. More at: https://www.nejlt.org/about/ ### ORGANIZATION * Editor-in-Chief: * Leon Derczynski, ITU Copenhagen; ld(a)itu.dk * Editorial board: * Isabelle Augenstein, University of Copenhagen * Nikolaos Aletras, University of Sheffield * Francesco Barbieri, Snap * Jasmijn Bastings, Google * Rachel Bawden, INRIA, Paris * Yonatan Belinkov, Technion * Emily M. Bender, University of Washington * Nicoletta Calzolari, Institute for Computational Linguistics, NRC Italy * Christos Christodoulopoulos, Amazon * Manuel R. Ciosici, USC Information Sciences Institute * Miryam de Lhoneux, University of Copenhagen * Lucia Donatelli, Saarland University * Yanai Elazar, University of Washington * Angela Fan, Meta * Yang Feng, Chinese Academy of Sciences * Mark Fishel, University of Tartu * Hila Gonen, Meta / University of Washington * Eva Hajičová, Charles University * Yufang Hou, IBM * Zhijing Jin, Max Planck Institute & ETH Zurich * Marco Kuhlmann, Linköping University * Sasha Luccioni, Hugging Face * Benjamin Marie, 4i * Yuji Matsumoto, NAIST/Riken AIP * Nafise Sadat Moosavi, The University of Sheffield * Joakim Nivre, Uppsala University * Debora Nozza, Bocconi University * Ellie Pavlick, Brown University * Verena Rieser, Heriot Watt University * Kay Rottmann, Amazon Alexa AI * Vered Shwartz, Allen Institute for Artificial Intelligence (AI2) * Thamar Solorio, University of Houston * Song Linfeng, Tencent * Mark Steedman, University of Edinburgh * Dhanasekar Sundararaman, Microsoft * Jörg Tiedemann, University of Helsinki * Emiel van Miltenburg, Tilburg University * Bonnie Webber, Universty of Edinburgh * Adina Williams, Meta * Steve Wilson, Oakland University NEJLT's editorial team is detailed at: https://www.nejlt.org/team/ ### PUBLICATION AND OPEN ACCESS NEJLT is full open access. This means that accepted papers may be downloaded directly from the web and will not be charged for. There are also no fees for submitting or for publishing. There are no plans to collect fees at any point in the future at any part of the NEJLT process. Papers are published under the CC-BY 4.0 license. NEJLT is a free Open Access Gold journal. Articles published in NEJLT also appear in the ACL Anthology: https://aclanthology.org/venues/nejlt/ The journal is published by Linköping University press. The editor-in-chief of NEJLT is appointed by the North European Association for Language Technology. More details on NEJLT policies at: https://www.nejlt.org/policies/ ### CONTACT Please see www.nejlt.org for further information. We look forward to receiving your manuscripts.

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Utrecht PhD positions "Dealing with Meaning Variation in NLP" (AiNed)
by Massimo Poesio 04 May '23

04 May '23

** Job openings: PhD studentships on meaning variation in NLP ** Utrecht University, The Netherlands The Natural Language Processing (NLP) group in the Computing and Information Sciences department of Utrecht University (UU) is looking for young researchers who want to jump-start their career in AI / NLP by taking up a PhD position. Two four-year positions are available now. They are part of the AiNed project “Dealing with Meaning Variation in NLP”, which will be led by Prof. Massimo Poesio. Vacancies for 4 further PhD positions on this project will become available over the coming 1-2 years. The overall aim of the project is to allow NLP models to make better sense of variations in the ways that different speakers and readers interpret language. The plan is for each of the 6 PhD projects to be supervised by one researcher from the NLP group and one from UU's Institute for Language Sciences. PhD PROJECT 1: Formal semantics for vagueness in interpretation This project is concerned with vagueness, a pervasive phenomenon in which the meanings of words have imprecisely defined boundaries, which are applied differently in different contexts and by different people (for example when the air temperature is described as "warm"). This PhD project will study mathematical and computational models of uncertainty and vagueness. In recent years, the theoretical literature in this area has shifted away from 2-valued towards multi-valued models, but these models have rarely been tested with real data. This PhD project will use existing “big” datasets (which are available in the weather domain, for example) to find out which models predict and explain the data best. The successful candidate will hold a Master’s degree in an area relevant to this project; this could be Artificial Intelligence, Computational Cognitive Science, Computing Science, or Linguistics. A good mastery of NLP and Excellent English communication skills (oral and written) is essential. We would also like you to take a strong interest in multi-valued and other models of natural language meaning, and in machine learning. PhD PROJECT 2: Learning under disagreements between annotators In NLP, human annotators are frequently needed to tell researchers what a given expression “means”, by assigning the expression a label. When human judges disagree about a label (e.g., whether an utterance is offensive or not), it is important that these disagreements be taken into account, as opposed to simply aggregating the values e.g., using reconciliation or majority voting. Such disagreements are now generally recognized to provide information rather than being noise. This PhD project will investigate whether the differences between various sources of disagreement (e.g., noise, ambiguity, and subjective bias) can be detected using statistical models (e.g. cross-entropy, Kullback-Leibler divergence). Last but not least, it will investigate to what extent variations in one person’s verbal behaviour can be understood mathematically in the same way as variations between different speakers. The proposed research would ideally be carried out by someone well versed in information theory and the design and analysis of experiments with human participants. The successful candidate will hold a Master’s degree in an area relevant to this project; this area could be Artificial Intelligence, Computational Cognitive Science, Computing Science, Linguistics, or Statistics. A good mastery of statistics and deep learning is essential; experience with NLP would be beneficial. A good mastery of NLP and Excellent English communication skills (oral and written) is essential. You take a strong interest in at least two of the three following areas: (1) machine learning, (2) natural language, and (3) experimental psychology. Further information about these vacancies can be found at PhD position in Natural Language Processing: statistical models of disagreement between annotators (0.8 – 1.0 FTE) - Working at Utrecht University - Utrecht University (uu.nl) <https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-po…> PhD position in Natural Language Processing: verbal expression of quantities (0.8 - 1.0 FTE) - Working at Utrecht University - Utrecht University (uu.nl) <https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-po…> Deadline for application is 29 May 2023. We’re looking for someone to start as soon as possible after the recruitment process is concluded but we understand that it will normally take a few months before the candidate will be ready to start. Applications should be made through the University's site (see links above). For further information, please contact: - Prof. Massimo Poesio (m.poesio AT uu.nl). - Prof. Kees Van Deemter (c.j.vandeemter AT uu.nl).

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PhD and Postdoc position in Cognitive Modelling
by Vera Demberg 04 May '23

04 May '23

We are inviting applications for one PhD position (3 years) and a postdoctoral position (funding available 09/2023-01/2026)of acomputer scientist,computational linguistor psycholinguist,who has experience withor interest incognitive modelling for language processing (e.g., Bayesian models, and/or modelsusing cognitive architectureslike ACT-R). Thepositions will be funded as part of theERC Starting Grant "Individualized Interaction in Discourse" ofProf. Vera Demberg, at Saarland University. The goal of the position is todevelop models that capture individualdifferences in discourse and pragmatic processing. The candidatewill conduct research on the design andimplementation of cognitive models of language processingat the level of discourse and/or pragmatic processing. These models should capture individual differences in cognitionsuch as working memory, language experience, background knowledge, theory-of-mind abilities etc. The successful applicant must have excellent spoken and writtenproficiency inEnglish, and have a background in natural language processing or cognitive modelling. Applicants are requested to submit their application, including a cover letter that specifies why you would like to workon this topic and what qualifies you for it, an academic CV, a list of academic publications, yourBSc/ MSc / PhDthesis (ora current draft), copies of academic degree certificates and names of two potential references. For application to the Postdoctoral position, please quote opening number W2290, for the PhD position please quote opening number W2289. The applicationsshould be sent via emaildirectly to Prof. Vera Demberg: vera(at)coli.uni-saarland.de *The****application deadline is****May****2**1**st**, 202**3* Saarland University is one of the leading centres for computer science and computational linguistics in Europe, and offers adynamic and stimulating research environment.The groupis affiliated with both theDepartment of Computer Scienceand withtheDepartment of Language Scienceand Technology. Both departments are part of the Saarland Informatics Campus, which brings together 800 researchers and 2000 students from 81countries. We collaborate closely with the university's Department of Computer Science, the Max Planck Institute for Informatics,the Max Planck Institute for Software Systems, and the German Research Center for Artificial Intelligence (DFKI). Our researchers and students come from all over the world, and our primary working language is English. The Saarland University is an equal opportunities employer. In accordance with its policy of increasing the proportion of womenin this type of employment, the University actively encourages applications from women. Women are given preference in cases ofequal suitability, ability and professional performance. Applications from severely disabled persons will be given preferential consideration in the event of equal suitability. Part-timeemployment is generally possible. We welcome applications regardless of gender,nationality, ethnic and social origin, religion/belief, disability, age, and sexualorientation and identity. Pay grade classification is based on the particular details of the position held and the extent to which the applicant meetstherequirements of the pay grade within the TV-L salary scale. Unfortunately, costs for attending an interview at Saarland University cannot be reimbursed in principle. When you submit a job application to Saarland University you will be transmitting personal data.Please refer to our privacy noticefor information on how we collect and process personal data in accordance with Art.13 of theDatenschutz-Grundverordnung.Bysubmitting your application you confirm that you have taken note of the information in the Saarland University privacy notice.************ -- Prof. Dr. Vera Demberg Computer Science and Computational Linguistics Saarland Informatics Campus Saarland University Campus C7.2 Room 3.02 D-66123 Saarbrücken Phone: +49-681-302-70024 Sekretariat: +49-681-302-70025 Fax: +49-681-302-70026 -- You received this message because you are subscribed to the Google Groups "XPRAG Wine Gatherings" group. To unsubscribe from this group and stop receiving emails from it, send an email to xpragwine+unsubscribe(a)googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/xpragwine/f9d60192-0120-d71e-a864-1d1fe9d… <https://groups.google.com/d/msgid/xpragwine/f9d60192-0120-d71e-a864-1d1fe9d…>. For more options, visit https://groups.google.com/d/optout.

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(AC-SRW 2023) Final CfP, Deadline: 5th May - Student Research Workshop co-located with ACL 2023
by Gisela Vallejo 04 May '23

04 May '23

Student Research Workshop co-located with ACL 2023 in Toronto, Canada. ***Paper Submission Deadline: May 5th, 2023*** The Student Research Workshop The ACL 2023 Student Research Workshop (SRW) is a forum to bring together students investigating various areas of Computational Linguistics, Natural Language Processing and Machine Learning. The workshop provides the opportunity for participants to present their work and to receive mentorship and valuable feedback from the international research community. The workshop's goal is to aid students at multiple stages of their education, including undergraduate, MSc/MA, junior and senior PhD students, in getting familiar with conducting and presenting their research. General Rules for Submission We invite papers in two different categories: - Research Papers: Papers in this category can describe completed work, or work in progress with preliminary results. For these papers, the first author **MUST BE** a current student. Topics of interest for the SRW are the same as for the main ACL 2023 conference: <https://www.2022.aclweb.org/calls> https://2023.aclweb.org/calls/main_conference/ - Thesis Proposals: This category is appropriate for PhD students who have decided on a thesis topic and wish to get feedback on their proposal and broader ideas for their continuing work. Submissions (in both categories) may either be archival or non-archival, based on the wish of the authors. All archival papers will be published in the ACL 2023 SRW Proceedings. Non-archival papers may be submitted to any venue in the future except for another SRW. The submission link is available on our website <https://acl2023-srw.github.io/>. Please read the guidelines carefully. Why Submit to ACL SRW? There are many good reasons to submit to the ACL SRW, such as: - Mentorship program: ACL SRW provides a unique opportunity for students to receive constructive feedback and to improve their work through a pre-submission mentorship program. - Improving your publication record: publishing a paper as an undergraduate or as a MSc/MA student is beneficial when applying for a PhD program. Publishing a paper in an ACL SRW workshop can be really helpful for improving students’ publication record. - Explorative Studies: We encourage the submission of studies with positive and negative results providing insights on why and in which scenarios a particular method succeeds and fails. All accepted papers and thesis proposals will be presented either as oral presentations or during poster sessions, which will give students an opportunity to interact with and to present their work to a large and diverse audience, including top researchers in the field and assigned mentors. Important Dates - Paper submission deadline: May 5, 2023 - Acceptance notifications: May 30 2023 - Camera-ready deadline: June 6, 2023 - ACL 2023 conference dates: July 10-12, 2023 All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth"). Submission Requirements We accept both archival submissions (which will be included in the conference proceedings) and non-archival submissions (which will be presented at the workshop but will not be included in the proceedings). All submissions (archival and non-archival) must follow the anonymity period and the restrictions of the main conference. Long papers consist of up to eight (8) pages of content, plus an unlimited number of pages for references and supplementary material like the appendix. Upon acceptance, papers will be given one additional page of content (up to 9 pages). Short papers consist of up to four (4) pages of content, plus an unlimited number of pages for references and supplementary material like the appendix. Upon acceptance, papers will be given one additional page of content (up to 5 pages). Authors are encouraged to use the additional page to address reviewers’ comments. Paper submissions must use the official ACL style templates, which are available as an Overleaf template <https://www.overleaf.com/read/crtcwgxzjskr> and also downloadable directly <https://github.com/acl-org/ACLPUB/tree/master/templates> (Latex and Word). We strongly encourage participants to use the Latex template. All submissions must be in PDF format and must conform to the official style guidelines, which are contained in these template files. The review process will be double-blind, and thus all submissions must be anonymized. The SRW invites papers on topics related to computational linguistics, including but not limited to the following: - Computational Social Science and Social Media - Dialogue and Interactive Systems - Discourse and Pragmatics - Ethics and NLP - Information Extraction - Information Retrieval and Text Mining - Interpretability and Analysis of Models for NLP - Language Grounding to Vision, Robotics, and Beyond - Linguistic Theories, Cognitive Modeling, and Psycholinguistics - Machine Learning for NLP - Machine Translation and Multilinguality - NLP Applications - Phonology, Morphology, and Word Segmentation - Question Answering - Resources and Evaluation - Semantics: Lexical - Semantics: Sentence-level Semantics, Textual Inference, and Other Areas - Sentiment Analysis, Stylistic Analysis, and Argument Mining - Speech and Multimodality - Summarization - Syntax: Tagging, Chunking, and Parsing Contact Information To contact the organizers of the workshop, please email us at: acl2023-srw(a)googlegroups.com. – Vishakh, Yao and Gisela ACL 2023 - SRW Organizers <https://acl2023-srw.github.io/>

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2024

2023

2022

Corpora May 2023