July 2023 - Corpora - ELRA lists

Workshop DiSLiDaS 2023
by Purificação Silvano 20 Jul '23

20 Jul '23

Second Workshop DISLiDAS 2023 Discourse studies and linguistic data science: Addressing challenges in interoperability, multilinguality and linguistic data processing Vienna, Austria, University of Vienna Website: http://dislidas.mozajka.co Date: 13 September 2023 Zoom link: TBA The Cost Action CA18209 NexusLinguarum (https://nexuslinguarum.eu) invites you to attend the Second Workshop Discourse studies and linguistic data science: Addressing challenges in interoperability, multilinguality and linguistic data processing – DiSLiDaS 2023, organized as part of LDK 2023 (http://2023.ldk-conf.org). We are glad to announce that the program features one keynote (in-person), Professor Johan Bos, and seven oral presentations. DiSLiDaS 2023 will be a hybrid event (in-person and online) open to anyone interested in the thematic. If you have not yet registered, please contact the LDK’s local organizers per e-mail (dagmar.gromann(a)gmail.com; barbara.heinisch(a)univie.ac.at). Online participation is still possible, but also requires prior registration. The registration form (https://ldk-registration.univie.ac.at) for online participation will be open until 3rd September 2023. We are very much looking forward to seeing you in Vienna. Program (All times are CEST - UTC+2) 9:15 Opening remarks 9:30-10:00 Adopting ISO 24617-8 for Discourse Relations Annotation in Polish: Challenges and Future Directions, Sebastian Żurowski, Daniel Ziembicki, Aleksandra Tomaszewska, Maciej Ogrodniczuk and Agata Drozd 10:00-10:30 Testing the Continuity Hypothesis: A decompositional approach, Debopam Das and Markus Egg 10:30-11:00 DRIPPS: a Corpus with Discourse Relations in Perfect Participial Sentences, Purificação Silvano, António Leal, João Cordeiro e Sebastaião Pais 11:00-11:30 Coffee break 11:30-12:30 Invited Talk: Johan Bos – A Simple Annotation Scheme for Annotating the Meaning of Discourse 12:30-14:00 Lunch break 14:00-14:30 Validation of Language Agnostic Models for Discourse Marker Detection, Mariana Damova, Giedre Valunaite Oleskeviciene, Kostadin Mishev, Purificação Silvano, Dimitar Trajanov, Ciprian-Octavian Truică, Chaya Liebeskind, Elena-Simona Apostol, Anna Baczkowska and Christian Chiarcos 14:30-15:00 An Algorithm for Pythonizing Rhetorical Structures, Andrew Potter 15:00-15:30 Lexical Retrieval Hypothesis in Multimodal Context, Wang Po-Ya Angela, Pin-Er Chen, Hsin-Yu Chou, Yu-Hsiang Tseng and Shu-Kai Hsieh 15:30-16:00 The shaping of the narrative on migration: A corpus assisted quantitative discourse analysis of the impact of the divisive media framing of migrants in Korea, Clara Delort and Jo Eun-Kyoung 16:00-16:30 Coffee break 16:30-17:00 Discussion 17:00-17:15 Closing remarks

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Call For Participation - PLABA @ TAC 2023
by Ondov, Brian (NIH/NLM/LHC) [F] 20 Jul '23

20 Jul '23

We are pleased to announce the inaugural offering of the Plain Language Adaptation of Biomedical Abstracts (PLABA) track, as part of the 2023 Text Analysis Conference (TAC) hosted by the U.S. National Institute of Standards and Technology (NIST). This track is an opportunity to showcase your cutting-edge research on an important topic, and to take advantage of large amounts of expert annotated data and manual evaluation. Background: Deficits of Health Literacy are linked to worse outcomes and drive health disparities. Though unprecedented amounts of biomedical knowledge are available online, patients and caregivers face a type of “language barrier” when confronted with jargon and academic writing. Advances in language modeling have improved plain language generation, but the task of automatically and accurately adapting biomedical text for a general audience has thus far lacked high-quality, standardized benchmarks. Task: Systems will adapt biomedical abstracts to plain language. This includes substituting medical jargon, providing explanations for necessary terms, simplifying sentences, and other modifications. The training set is the publicly available PLABA dataset<https://doi.org/10.1038%2Fs41597-022-01920-3>, which contains 750 abstracts with manual, sentence-aligned adaptations for each, totaling more than 7k sentence pairs with document context. Evaluation: Participating systems will be evaluated on 400 held out abstracts, manually adapted four-fold by different annotators for robust automatic metrics. Additionally, a subset of system output will be manually evaluated along several axes to ensure they are accurate and faithful to the original, which is crucial for the biomedical domain. URL: https://bionlp.nlm.nih.gov/plaba2023/ Mailing list: https://groups.google.com/g/plaba2023 Key dates: Jul 19 – Evaluation data released Aug 16 – Submissions due Oct 18 – Results posted We look forward to your submissions.

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Announcing the ALTA 2023 Shared Task
by Diego Molla-Aliod 20 Jul '23

20 Jul '23

CALL FOR PARTICIPATION http://www.alta.asn.au/events/sharedtask2023<http://www.alta.asn.au/events/sharedtask2023> The Australasian Language Technology Association (ALTA) is organising a programming competition for university undergraduate and postgraduate students. Following on the series of shared tasks by ALTA since 2010, all participants compete to solve the same problem. The problem highlights an active area of research and programming in the area of language technology. This year's shared task is fitting for the times we are living: Distinguish between human-generated and AI-generated text. The tentative key dates are: Right Now - Registration and release of training and development data 27 Sep 2023 - Release of test data 03 Oct 2023 - Deadline of submission of runs 06 Oct 2023 - Notification of results 25 Oct 2023 - Deadline of submission of system description 29 Nov - 1 Dec 2023 - Presentation of results at ALTA 2023 Details of the task and registration are available at the competition website (https://www.alta.asn.au/events/sharedtask2023<https://www.alta.asn.au/events/sharedtask2023>) Good luck! Diego -- Dr. Diego Mollá-Aliod Senior Lecturer School of Computing | Room 358 (Level 3), 4 Research Park Drive Macquarie University, NSW 2109, Australia T: +61 2 9850 9531 | F: +61 2 9850 9551 https://macquarie.zoom.us/my/diego.molla http://comp.mq.edu.au/~diego I acknowledge the traditional custodians of the land on which Macquarie University stands – the Wallumattagal clan of the Dharug nation – whose cultures and customs have nurtured and continue to nurture this land since time immemorial. I pay my respects to Elders past and present.

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BioCreative VIII Challenge and Workshop 2nd Call for Participation
by Islamaj, Rezarta (NIH/NLM/NCBI) [E] 19 Jul '23

19 Jul '23

BioCreative VIII Challenge and Workshop 2nd Call for Participation Where, When: The BioCreative VIII workshop<BioCreative%20VIII%20workshop> will run with AMIA 2023, November 11-15, 2023, In New Orleans, LA. BioCreative VIII: The VIIIth BioCreative workshop seeks to attract researchers interested in automatic methods of extracting medically relevant information from clinical data and aims to bring together the medical NLP community and the health professionals community. The challenge tracks include: * BioRED (Biomedical Relation Extraction Dataset) Track will continue to address information extraction from biomedical literature * SYMPTEMIST (Symptom TExt Mining Shared Track) will focus on symptom extraction from clinical records in Spanish and multilingual corpus * Phenotype extraction (genetic conditions in pediatric patients) Track will address phenotype extraction from clinical records * Annotation Tool Track will focus on annotation tools that facilitate the job of domain experts by offering seamless integration with relevant ontologies and other features to improve efficiency (dataset provided). Workshop Proceedings and Special Issue: The BioCreative VIII Proceedings will host all the submissions from participating teams, and it will be freely available by the time of the workshop. In addition, we are happy to announce that the journal Database will host the BioCreative VIII special issue for work that has passed their peer-review process. Invitation to submit will be sent after the workshop. Participation: Teams can participate in one or more of these tracks. Team registration will continue until final commitment is requested by the individual tracks. To register a team go to the Registration form<https://urldefense.com/v3/__https:/forms.gle/cwEPevGPjrjm687z5__;!!KOmnBZxC…>. If you have restrictions accessing Google forms please send e-mail to BiocreativeChallenge(a)gmail.com<mailto:BiocreativeChallenge@gmail.com> BioCreative VIII Tracks: Track 1: BioRED (Biomedical Relation Extraction Dataset) Track. (Rezarta Islamaj and Zhiyong Lu) This track aims to foster the development of systems that automatically extract biomedical relations in journal articles, and the final resource -- freely available to the community -- will consist of 1000 MEDLINE articles fully annotated with biological and medically relevant entities, biomedical relations between them, and the novelty of the relation (whether the relation is a key point of the article versus background knowledge that can be found elsewhere). The participants will use the training data (600 articles) to design and develop their NLP systems to extract asserted relationships from free text and are encouraged to classify relations that are novel findings. In the BioCreative setting we will enrich the BioRED training dataset with 400 recently published MEDLINE articles fully annotated, bringing this valuable resource to 1000 articles. This track serves as a continuation of previous BioCreative Workshops that addressed the individual extraction of bio entities and/or specific relations such as disease-gene, protein-protein, or chemical-chemical, in biomedical articles. In contrast from previous challenges, this track calls for the extraction of all semantic relations expressed in the article and their novelty factor. Track 2: SYMPTEMIST (Symptom TExt Mining Shared Task) (Martin Krallinger) A considerable effort has been made to automatically extract from clinical texts relevant variables and concepts using advanced entity recognition approaches. Despite the importance of clinical signs and symptoms for diagnosis, prognosis and healthcare data analytics strategies, this kind of clinical entity has received far less attention when compared to other entity classes such as medications or diseases. To understand and characterize relationships between different symptoms, their onset, or associations of symptoms to diseases is a central question for medical research. Due to the complexity underlying the annotation process and normalization or mapping of symptom mentions to controlled vocabularies, very few datasets or corpora have been generated to train and evaluate advanced clinical named entity recognition systems. To foster the development, research and evaluation of semantic annotation strategies that can be useful for systematically extracting and harmonizing symptoms from clinical documents we propose the SYMPTEMIST track. We will invite researchers, health-tech professionals, NLP, and ontology experts to develop tools capable of detecting automatically mentions of clinical symptoms from clinical texts in Spanish and normalizing or mapping them to a widely used multilingual clinical vocabulary, namely SNOMED CT. For this task we will release a large collection of manually annotated symptoms mentions, together with detailed annotation guidelines, consistency analysis and additional resources. For this track we plan also to release a multilingual version of the corpus (English, Italian, Romanian, Catalan, Portuguese, French, Dutch, Swedish and Czech). This is a new challenge. Track 3: Phenotype extraction (genetic conditions in pediatric patients) (Graciela Gonzalez, Ian Campbell, Davy Weissenbacher) The dysmorphology physical examination is a critical component of the diagnostic evaluation in clinical genetics. This process catalogs often minor morphological differences of the patient's facial structure or body, but it may also identify more general medical signs such as neurologic dysfunction. The findings enable the correlation of the patient with known rare genetic diseases. Although the medical findings are key information, they are nearly always captured within the electronic health record (EHR) as unstructured free text, making them unavailable for downstream computational analysis. Advanced Natural Language Processing methods are therefore required to retrieve the information from the records. This is a new challenge. Track 4: Annotation Tool track (Rezarta Islamaj, Cecilia Arighi, Lynette Hirschman, Martin Krallinger, Graciela Gonzalez) Recognizing the need for freely available, time-saving tools that help build quality gold-standard resources, the goal of BioCreative 2023 Annotation Tool Track is to foster development of such biocuration annotation systems. This track calls for text mining developers to submit systems that are: 1) both publicly available, and offer local setup options to allow for data with privacy concerns, such as clinical records, 2) able to support team annotation, and collaboration between annotators to ensure data annotation quality, 3) able to annotate documents for triage, entities, and/or relations, and 4) able to integrate the selected ontology, and provide search capabilities/browsing, as well as suggestions to the curator for the selected ontology. A select number of systems will be showcased at the workshop. Organizing Committee * Dr. Rezarta Islamaj, National Library of Medicine * Dr. Cecilia Arighi, University of Delaware * Dr. Ian M. Campbell, Children Hospital of Philadelphia * Dr. Graciela Gonzalez-Hernandez, Cedars-Sinai Medical Center * Dr. Lynette Hirschman, MITRE * Dr. Martin Krallinger, Barcelona Supercomputing Center * Dr. Davy Weissenbacher, Cedars-Sinai Medical Center * Dr. Zhiyong Lu, National Library of Medicine

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[EVALITA 2023]: call for participation
by Giulia Venturi 19 Jul '23

19 Jul '23

[Apologies for multiples postings] ------------------------------------------------------------ CALL FOR PARTICIPATION EVALITA 2023 8th Evaluation Campaign of Natural Language Processing and Speech Tools for the Italian Language https://www.evalita.it/campaigns/evalita-2023/ 7-8th September 2023 University of Parma, Plesso di via D’Azeglio n. 85 Parma, Italy ------------------------------------------------------------ The EVALITA 2023 final workshop will be held in Parma on September 7-8th, 2023. REGISTRATION is now open: Early registration (until 21/08/2023): regular 80 €, student 60 € Late registration (after 21/08/2023): regular 100 €, student 80 € On site registrazione: regular 120 €, student 100 € Please note that EVALITA is an initiative of AILC (Associazione Italiana di Linguistica Computazionale). Therefore, in order to support the community, participants are requested to become members of AILC before registering to the workshop. Notice that the AILC annual membership expires December 31st. AILC membership fees can be found on the website of the association: https://www.ai-lc.it/en/memberships/ More information: https://www.evalita.it/campaigns/evalita-2023/workshop-registration/ Registration online system: https://www.ai-lc.it/en/evalita-registration-procedure/ TENTATIVE SCHEDULE https://www.evalita.it/campaigns/evalita-2023/final-workshop/workshop-progr… INVITED SPEAKER Julio Gonzalo, full professor of Computer Science at UNED (Universidad Nacional de Educación a Distancia, Madrid, Spain) VENUE https://www.evalita.it/campaigns/evalita-2023/final-workshop/venue/ EVALITA 2023 CHAIRS Mirko Lai (Università di Torino) Stefano Menini (Fondazione Bruno Kessler) Marco Polignano (Università di Bari Aldo Moro) Valentina Russo (Logogramma SRL) Rachele Sprugnoli (Università degli Studi di Parma) Giulia Venturi (Istituto di Linguistica Computazionale “A. Zampolli” – CNR) CONTACT evalita2023[AT]gmail.com FOLLOW US! Twitter: https://twitter.com/EVALITAcampaign

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Research Associate, Oldenburg, Germany
by Jörge Minula 19 Jul '23

19 Jul '23

Dear Members, I would like to bring to your attention the following research associate position in the Field of Psycholinguistics and hearing research at University of Oldenburg, Germany. For more information about the position and how to apply, please refer to the detailed description provided in the email below. Best regards, Jörge Minula --- The cluster of excellence Hearing4all: Models, Technology and Solutions for Diagnostics, Restoration and Support of Hearing at the Universität Oldenburg (in collaboration with Medizinische Hochschule Hannover and Leibniz Universität Hannover) is seeking to fill as soon as possible the position of a Research Associate (fulltime) in the Field of Psycholinguistics and hearing research (m/f/d) in the Department of Dutch, Faculty of Linguistics and Cultural Studies. The position is available from 1st of October 2023 (or as soon as possible after that) until 31st of December 2025. Salary is depending on previous experience and education (German TV-L E13 <https://lohntastik.de/od-rechner/tv-salary-calculator/TV-L/E-13/1>). The position is suitable for part-time work. A paramount goal of the cluster of excellence Hearing4all ( www.hearing4all.de) is to transform audiology into an "exact" science based on the interplay between experiment and theory as well as between basic science and clinical research. In the framework provided by the cluster the successful candidate is expected to contribute to the research goals of the cluster to research thread 1 "Auditory processing deficits throughout the lifespan", in which one of the goals is to identify the impact of hearing loss in young and old age on cognitive and language development and its decline. Specifically, the candidate is expected to do research on the interaction of hearing abilities and language processing/development. Candidates are expected to have PhD in the field of (psycho)- linguistics, psychology, or a related discipline (with a specialization in speech/language processing and/or language acquisition) and have shown their ability to perform excellent scientific work, usually demonstrated by the outstanding quality of their Doctorate/PhD research and a good publication record. Experience in hearing research is an advantage. We are seeking candidates with experience in statistical analysis as well as knowledge in at least one of the following methods/areas: language acquisition, online sentence processing, reaction time studies, eye tracking, ERP. Matlab skills, and/ or experience with E-prime will be helpful, as well as working knowledge of German. Since the positions entail close interdisciplinary cooperation with several other disciplines (audiology, psychology, physics), the willingness and ability to integrate methods, concepts and issues of the 'other' discipline into theories, concepts and methods current in one's own are required for successful work in this project. The University of Oldenburg is an equal opportunities employer. According to § 21 para. 3 of the legislation governing Higher Education in Lower Saxony (NHG), preference shall be given to female candidates in cases of equal qualification. The same applies to persons with disabilities. More information at: https://uol.de/stellen?stelle=69714

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Post-doc position on Multimodal Neural Web Page Segmentation, GREYC, France
by Mohammed Hasanuzzaman 19 Jul '23

19 Jul '23

Dear All, We have an exciting opportunity for highly motivated and talented researchers to apply for our Postdoctoral position at GREYC Research Centre (https://www.greyc.fr/en/home/), France. Since 2000, the GREYC has been a joint research unit associated with the French National Centre for Scientific Research (CNRS), the University of Caen Normandy (UNICAEN) and the Ecole Nationale Supérieure d’Ingénieurs de Caen (ENSICAEN). The GREYC lab realizes research works in the field of digital science with activities in image processing, machine learning, artificial intelligence, computer security, fundamental computer science, Web science, electronics. It has 7 research groups with faculty members from ENSICAEN, UNICAEN and CNRS, PhD students and administrative & technical members. The postdoctoral scholar will be working on Multimodal Neural Web Page Segmentation with a primary goal to detect the different zones of a web page. This interdisciplinary research project combines computer vision, natural language processing, and machine learning techniques to develop advanced algorithms capable of segmenting web pages into meaningful and semantically distinct regions. *Location: **GREYC Research Centre *(https://www.greyc.fr/en/home/)*, France* *Closing Date: **15 August*, *2023* *Benefits:* The successful candidate will receive a competitive salary and other benefits, as well as access to state-of-the-art research facilities and resources. The fellowship will be initially offered for 12-18 months, with the possibility of extension based on performance. *Eligibility Criteria:* Applicants interested in this position must meet the following criteria: - Hold a recent Ph.D. degree in Computer Science, Electrical Engineering, or a related field. - Demonstrate a strong research background in natural language processing or computer vision. - Possess a track record of publications in top-tier conferences/journals related to computer vision, NLP, or related areas. - Strong programming skills. - Excellent written and verbal communication and interpersonal skills. *Application Process:* Interested candidates can send an application with the following documents directly Prof. Gael Dias, email: gael.dias(a)unicaen.fr and Dr. Mohammed Hasanuzzaman, email: mohammed.hasanuzzaman(a)mtu.ie - Updated Curriculum Vitae (CV) with a list of publications. - A cover letter outlining research interests, relevant background, and motivation for applying. - Contact information for three academic referees who can provide recommendation letters. ------------------------------------------------------------------------------------------------------ *Dr. Mohammed Hasanuzzaman, Lecturer, Munster Technological University <https://www.mtu.ie/> * *Funded Investigator, ADAPT Centre- <https://www.adaptcentre.ie/> A <https://www.adaptcentre.ie/>* World-Leading SFI Research Centre <https://www.adaptcentre.ie/> *Member, Lero, the SFI Research Centre for Software <https://lero.ie/>**C**hercheur Associé*, GREYC UMR CNRS 6072 Research Centre, France <https://www.greyc.fr/en/home/> *Associate Editor:** IEEE Transactions on Affective Computing, Nature Scientific Reports, IEEE Transactions on Computational Social Systems, ACM TALLIP, PLOS One, Computer Speech and Language* Dept. of CS Munster Technological University Bishopstown campus Cork e: mohammed.hasanuzzaman(a)adaptcentre.ie <email(a)adaptcentre.ie>/ Ireland https://mohammedhasanuzzaman.github.io/ [image: Mailtrack] <https://mailtrack.io?utm_source=gmail&utm_medium=signature&utm_campaign=sig…> Sender notified by Mailtrack <https://mailtrack.io?utm_source=gmail&utm_medium=signature&utm_campaign=sig…> 19/07/23, 12:52:06

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Call for papers: The 4th Workshop on Evaluation and Comparison of NLP Systems (Eval4NLP 2023)
by opitz.sci＠gmail.com 19 Jul '23

19 Jul '23

Dear Colleagues, the 4th Workshop on Evaluation and Comparison for NLP systems (Eval4NLP), co-located at the 2023 Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL 2023), invites the submission of long and short papers, with a theoretical or experimental nature, describing recent advances in system evaluation and comparison in NLP. ** Important Dates ** All deadlines are 11.59 pm UTC -12h (“Anywhere on Earth”). - Direct submission to Eval4NLP deadline: August 25 - Submission of pre-reviewed papers to Eval4NLP (see below for details) : September 25 - Notification of acceptance: October 2 - Camera-ready papers due: October 15 - Workshop day: November 1 Please see the Call for Papers for more details [1]. ** Shared Task ** This year’s version will come with a shared task on explainable evaluation of generated language (MT and summarization) with a focus on LLM prompts. Please find more information on the shared task page: [2]. ** Topics ** Designing evaluation metrics: Proposing and/or analyzing metrics with desirable properties, e.g., high correlations with human judgments, strong in distinguishing high-quality outputs from mediocre and low-quality outputs, robust across lengths of input and output sequences, efficient to run, etc.; Reference-free evaluation metrics, which only require source text(s) and system predictions; Cross-domain metrics, which can reliably and robustly measure the quality of system outputs from heterogeneous modalities (e.g., image and speech), different genres (e.g., newspapers, Wikipedia articles and scientific papers) and different languages; Cost-effective methods for eliciting high-quality manual annotations; and Methods and metrics for evaluating interpretability and explanations of NLP models Creating adequate evaluation data: Proposing new datasets or analyzing existing ones by studying their coverage and diversity, e.g., size of the corpus, covered phenomena, representativeness of samples, distribution of sample types, variability among data sources, eras, and genres; and Quality of annotations, e.g., consistency of annotations, inter-rater agreement, and bias check Reporting correct results: Ensuring and reporting statistics for the trustworthiness of results, e.g., via appropriate significance tests, and reporting of score distributions rather than single-point estimates, to avoid chance findings; reproducibility of experiments, e.g., quantifying the reproducibility of papers and issuing reproducibility guidelines; and Comprehensive and unbiased error analyses and case studies, avoiding cherry-picking and sampling bias. ** Submission Guidelines ** The workshop welcomes two types of submission -- long and short papers. Long papers may consist of up to 8 pages of content, plus unlimited pages of references. Short papers may consist of up to 4 pages of content, plus unlimited pages of references. Please follow the ACL ARR formatting requirements, using the official templates [3]. Final versions of both submission types will be given one additional page of content for addressing reviewers’ comments. The accepted papers will appear in the workshop proceedings. The review process is double-blind. Therefore, no author information should be included in the papers and the (optional) supplementary materials. Self-references that reveal the author's identity must be avoided. Papers that do not conform to these requirements will be rejected without review. ** The submission sites on Openreview ** Standard submissions: [4] Pre-reviewed submissions: [5] See below for more information on the two submission modes. ** Two submission modes: standard and pre-reviewed ** Eval4NLP features two modes of submissions. Standard submissions: We invite the submission of papers that will receive up to three double-blind reviews from the Eval4NLP committee, and a final verdict from the workshop chairs. Pre-reviewed: To a later deadline, we invite unpublished papers that have already been reviewed, either through ACL ARR, or recent AACL/EACL/ACL/EMNLP/COLING venues (these papers will not receive new reviews but will be judged together with their reviews via a meta-review; authors are invited to attach a note with comments on the reviews and describe possible revisions). Final verdicts will be either accept, reject, or conditional accept, i.e., the paper is only accepted provided that specific (meta-)reviewer requirements have been met. Please also note the multiple submission policy. ** Optional Supplementary Materials ** Authors are allowed to submit (optional) supplementary materials (e.g., appendices, software, and data) to improve the reproducibility of results and/or to provide additional information that does not fit in the paper. All of the supplementary materials must be zipped into one single file (.tgz or .zip) and submitted via Openreview together with the paper. However, because supplementary materials are completely optional, reviewers may or may not review or even download them. So, the submitted paper should be fully self-contained. ** Preprints ** Papers uploaded to preprint servers (e.g., ArXiv) can be submitted to the workshop. There is no deadline concerning when the papers were made publicly available. However, the version submitted to Eval4NLP must be anonymized, and we ask the authors not to update the preprints or advertise them on social media while they are under review at Eval4NLP. ** Multiple Submission Policy ** Eval4NLP allows authors to submit a paper that is under review in another venue (journal, conference, or workshop) or to be submitted elsewhere during the Eval4NLP review period. However, the authors need to withdraw the paper from all other venues if they get accepted and want to publish in Eval4NLP. Note that AACL and ARR do not allow double submissions. Hence, papers submitted both to the main conference and AACL workshops (including Eval4NLP) will violate the multiple submission policy of the main conference. If authors would like to submit a paper under review by AACL to the Eval4NLP workshop, they need to withdraw their paper from AACL and submit it to our workshop before the workshop submission deadline. ** Best Paper Awards ** We will optionally award prizes to the best paper submissions (subject to availability; more details to come soon). Both long and short submissions will be eligible for prizes. ** Presenting Published Papers ** If you want to present a paper which has been published recently elsewhere (such as other top-tier AI conferences) at our workshop, you may send the details of your paper (Paper title, authors, publication venue, abstract, and a link to download the paper) directly to eval4nlp(a)gmail.com. We will select a few high-quality and relevant papers to present at Eval4NLP. This allows such papers to gain more visibility from the workshop audience and increases the variety of the workshop program. Note that the chosen papers are considered as non-archival here and will not be included in the workshop proceedings. ------------------------------------------------- Best wishes, Eval4NLP organizers Website: https://eval4nlp.github.io/2023/index.html Email: eval4nlp(a)gmail.com [1] https://eval4nlp.github.io/2023/index.html [2] https://eval4nlp.github.io/2023/shared-task.html [3] https://github.com/acl-org/acl-style-files [4] https://openreview.net/group?id=aclweb.org/AACL-IJCNLP/2023/Workshop/Eval4N… [5] https://openreview.net/group?id=aclweb.org/AACL-IJCNLP/2023/Workshop/Eval4N…

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[Job] Senior Research Scientist opportunity at ASUS AICS (Singapore/Taipei)
by Stefan Winkler(Stefan Winkler) 19 Jul '23

19 Jul '23

AICS (https://aics.asus.com/ ) is a young ASUS division incubating applied software and AI services to create a new generation of smart medical solutions. The team is building and deploying deep technologies in Data Analytics, Speech Recognition, Natural Language Understanding, and Computer Vision to help accelerate the transformation towards an AI-powered future in healthcare. The role of our AI Researchers is to work on ambitious long-term research goals, while laying out intermediate milestones to solve large-scale, real-world problems. As a senior member of the team, you will also help define research directions and guide junior researchers. Specific research topics of interest include (but are not limited to) generative models, knowledge discovery, domain generalization, long-tailed learning, and self-supervised approaches. We are currently recruiting at the senior level, either at our Singapore or Taipei offices. Job Responsibilities: * Drive AI/ML research from concepts to concrete output * Invent and implement innovative ML algorithms and tools * Publish and present your work in the top ML/NLP venues * Guide junior research team members and PhD students * Work with the product and engineering team to transform research prototypes into production * Forge research collaborations with university partners and clinicians Requirements: * Ph.D. degree in computer science or related discipline * At least 5+ years experience post-PhD, preferably in industry * Strong track record of publications at top peer-reviewed conferences and journals * Active in the research community and recognized by peers (e.g. conference committee membership, highly cited papers, awards) * Expertise in state-of-the-art machine learning methods, especially in the domains of natural language processing * Hands-on experience with deep learning frameworks such as PyTorch * Familiarity with MLOps and deploying models in production will be beneficial You may apply via https://aics.asus.com/career-en/ai-researcher/ or email me your CV directly. We look forward to hearing from you! Best regards, Stefan Winkler -- Director of R&D Asus AICS Singapore https://aics.asus.com/ =================================================================================================================================== This email and any attachments to it contain confidential information and are intended solely for the use of the individual to whom it is addressed. If you are not the intended recipient or receive it accidentally, please immediately notify the sender by e-mail and delete the message and any attachments from your computer system, and destroy all hard copies. Please be advised that any unauthorized disclosure, copying, distribution or any action taken or omitted in reliance on this, is illegal and prohibited. Any views or opinions expressed are solely those of the author and do not represent those of ASUSTeK. For pricing information, ASUS is only entitled to set a recommendation resale price. All customers are free to set their own price as they wish. ===================================================================================================================================

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[CFP] 3rd Workshop for NLP Open Source Software at EMNLP 2023
by liling tan 18 Jul '23

18 Jul '23

(apologies for cross-posting) *-----Workshop for NLP Open Source Software (NLP-OSS)* 06 Dec 2023, Co-located with EMNLP 2023 https://nlposs.github.io/ Deadline for Long and Short Paper submission: 09 August, 2023 (23:59, GMT-11) ----- You have tried to use the latest, bestest, fastest LLM models and bore grievances but found the solution after hours of coffee and computer staring. Share that at NLP-OSS and suggest how open source could change for the better (e.g. best practices, documentation, API design etc.) You came across an awesome SOTA system on NLP task X that no LLM has beaten its F1 score. But now the code is stale and it takes a dinosaur to understand the code. Share your experience at NLP-OSS and propose how to "replicate" these forgotten systems. You see this shiny GPT from a blog post, tried it to reproduce similar results on a different task and it just doesn't work on your dataset. You did some magic to the code and now it works. Show us how you did it! Though they're small tweaks, well-motivated and empirically tested are valid submissions to NLP-OSS. You have tried 101 NLP tools and there's none that really do what you want. So you wrote your own shiny new package and made it open source. Tell us why your package is better than the existing tools. How did you design the code? Is it going to be a one-time thing? Or would you like to see thousands of people using it? You have heard enough of open-source LLM and pseudo-open-source GPT but not enough about how it can be used for your use-case or your commercial product at scale. So you contacted your legal department and they explained to you about how data, model and code licenses work. Sharing the knowledge with the NLP-OSS community. You have a position/opinion to share about free vs open vs closed source LLMs and have valid arguments, references or survey/data to support your position. We would like to hear more about it. At last, you've found the avenue to air these issues in an academic platform at the NLP-OSS workshop!!! Sharing your experiences, suggestions and analysis from/of NLP-OSS ---- P/S: 2nd Call for Paper *Workshop for NLP Open Source Software (NLP-OSS)* 06 Dec 2023, Co-located with EMNLP 2023 https://nlposs.github.io/ Deadline for Long and Short Paper submission: 09 August, 2023 (23:59, GMT-11) ------------------------------ The Third Workshop for NLP Open Source Software (NLP-OSS) will be co-located with EMNLP 2023 on 06 Dec 2023. Focusing more on the social and engineering aspect of NLP software and less on scientific novelty or state-of-art models, the Workshop for NLP-OSS is an academic forum to advance open source developments for NLP research, teaching and application. NLP-OSS also provides an academic workshop to announce new software/features, promote the collaborative culture and best practices that go beyond the conferences. We invite full papers (8 pages) or short papers (4 pages) on topics related to NLP-OSS broadly categorized into (i) software development, (ii) scientific contribution and (iii) NLP-OSS case studies. - *Software Development* - Designing and developing NLP-OSS - Licensing issues in NLP-OSS - Backwards compatibility and stale code in NLP-OSS - Growing, maintaining and motivating an NLP-OSS community - Best practices for NLP-OSS documentation and testing - Contribution to NLP-OSS without coding - Incentivizing OSS contributions in NLP - Commercialization and Intellectual Property of NLP-OSS - Defining and managing NLP-OSS project scope - Issues in API design for NLP - NLP-OSS software interoperability - Analysis of the NLP-OSS community - *Scientific Contribution* - Surveying OSS for specific NLP task(s) - Demonstration, introductions and/or tutorial of NLP-OSS - Small but useful NLP-OSS - NLP components in ML OSS - Citations and references for NLP-OSS - OSS and experiment replicability - Gaps between existing NLP-OSS - Task-generic vs task-specific software - *Case studies* - Case studies of how a specific bug is fixed or feature is added - Writing wrappers for other NLP-OSS - Writing open-source APIs for open data - Teaching NLP with OSS - NLP-OSS in the industry Submission should be formatted according to the EMNLP 2023 templates <https://2023.emnlp.org/call-for-papers> and submitted to OpenReview <https://openreview.net/group?id=EMNLP/2023/Workshop/NLP-OSS> ORGANIZERS Geeticka Chauhan, Massachusetts Institute of Technology Dmitrijs Milajevs, Grayscale AI Elijah Rippeth, University of Maryland Jeremy Gwinnup, Air Force Research Laboratory Liling Tan, Amazon

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