- Corpora - ELRA lists

[QPP++] 2nd CfP Query Performance Prediction and Its Evaluation in New Tasks @ CIKM 2022
by Guglielmo Faggioli 05 Aug '22

05 Aug '22

Query Performance Prediction (QPP) is currently primarily used for ad-hoc retrieval tasks. The Information Retrieval (IR) field is reaching new heights thanks to recent advances in large language models and neural networks, as well as emerging new ways of searching, such as conversational search. Such advancements are quickly spreading to adjacent research areas, including QPP, necessitating a reconsideration of how we perform and evaluate QPP. Important Dates --------------------- Submission deadline: September 2, 2022 Notification of acceptance: September 27, 2022 Camera ready: October 06, 2022 Conference days: October 17-20, 2022 Workshop day: October 21, 2022 Call for Papers ------------------- This workshop aims at stimulating discussion on three main aspects concerning the future of QPP: What are the emerging QPP challenges posed by new methods and technologies, including but not limited to dense retrieval, contextualized embeddings, and conversational search? How might these new techniques be used to improve the quality of QPP? Can we claim that the current techniques for evaluating QPP are effective in all arising scenarios? Can we envision new evaluation protocols capable of granting generalizability in new domains? We plan to foster the discussion via two focus groups led by the workshop's organizers. The first focus group will identify what possibilities the QPP offers regarding new research models and IR tasks, primary considerations, issues linked to different aspects of the QPP, and the potentialities provided by new tools. The second focus group will gather the community’s concerns and solutions with respect to the QPP evaluation, especially for what concerns emerging domains. Themes and Topics The workshop will focus on the following themes: Query performance prediction applied to new tasks: Can existing QPP techniques be exploited, or which new QPP theories and models need to be devised for new tasks, such as passage-retrieval, Q&A, and conversational search? Query performance prediction exploiting new techniques: How can new technologies, such as contextualized embeddings, large language models, and neural networks be exploited to improve QPP? Evaluation of query performance prediction: How should QPP techniques be evaluated, including best practices, datasets, and resources, and, in particular, should QPP be evaluated the same for different IR tasks? It is possible to submit three main categories of manuscripts to the workshop: Full papers: up to 6 pages. Short papers: up to 3 pages. Discussion papers: up to 3 pages. All manuscripts are expected to address the workshop's themes as mentioned above. Full and short papers should contain innovative ideas and their experimental evaluation. We are also interested in works containing (methodologically sound) preliminary results and incremental endeavours. Discussion papers should include work with or without preliminary results, position papers, and papers describing failures. Such papers should foster the discussion and thus are not required to contain full-fledged results. In this sense, the experimental evaluation of the submitted discussion paper is appreciated but not required. We are also interested in receiving contributions regarding (methodologically sound) failed experiments; since the workshop will focus on new research directions, we consider it necessary also to discuss the reasons and causes of failures. Each manuscript will be peer-reviewed by at least two program committee members Accepted papers will be published online as a volume of the CEUR-WS proceeding series. Website -------------- qpp2022.dei.unipd.it Organizers -------------- Guglielmo Faggioli, University of Padova, Italy, faggioli(a)dei.unipd.it <http://faggiolidei.unipd.it/> Nicola Ferro, University of Padova, Italy, ferro(a)unipd.it <http://ferrounipd.it/> Josiane Mothe, Université de Toulouse, IRIT, France, josiane.mothe(a)irit.fr <http://josiane.motheirit.fr/> Fiana Raiber, Yahoo Research, Israel, fiana(a)yahooinc.com <http://fianayahooinc.com/> ---------- Guglielmo Faggioli Dipartimento di Ingegneria Informatica, University of Padua Via Gradenigo 6/b, 35138, Padua, Italy

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PhD Position in Speech Translation at Fondazione Bruno Kessler
by Matteo Negri 04 Aug '22

04 Aug '22

-- Apologies for cross-posting. -- Have you recently completed or expect very soon an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering, or a related area? Are you interested in carrying out research on Speech Translation during the next few years? Are you excited to spend a part of your life in a pleasant city in the heart of the Italian Alps? WE ARE LOOKING FOR YOU!!! The Machine Translation <https://ict.fbk.eu/units/hlt-mt/> (MT) group at Fondazione Bruno Kessler (Trento, Italy) in conjunction with the ICT International Doctorate School of the University of Trento <https://iecs.unitn.it/> is pleased to announce the availability of the following fully-funded Ph.D. position in Speech Translation. TITLE: Application-oriented Speech Translation DESCRIPTION: The need to translate audio input from one language into text in a target language has dramatically increased in the last few years with the growth of audiovisual content freely available on the Web. Current speech translation (ST) systems are now required to be flexible and robust enough to operate in different application scenarios. On one side, the industry calls for key features like real-time processing, domain adaptability, extended language coverage, and the capability to meet application-specific constraints. On the other side, society calls for new efforts towards inclusiveness with respect to specific categories and groups (e.g. gender-sensitivity, customization to the needs of impaired users). Both industry and society face the orthogonal challenges posed by the variability of audio conditions (e.g. background noise, strong speakers’ accent, overlapping speakers). The objective of this Ph.D. is to make ST flexible and robust to these and other factors. CONTACT: negri(a)fbk.eu COMPLETE DETAILS AVAILABLE AT: https://iecs.unitn.it/education/admission/call-for-application IMPORTANT DATES: The deadline for application is September 6, 2022, hrs. 04:00 PM (CEST) Potential candidates are strongly invited to contact us in advance for preliminary interviews. Precedence for interviews will be given to short-listed candidates that will send us a complete CV via email ( negri(a)fbk.eu) by August 18, 2022. Candidate profile The ideal candidate must have recently completed or expect very soon an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering, or a closely related area. In addition, the applicant should: - Have interest in Machine and Speech Translation - Have experience in deep learning and machine learning, in general - Have good programming skills in Python and experience in PyTorch - Enjoy working with real-world problems and large data sets - Have good knowledge of written and spoken English - Enjoy working in a closely collaborating team Working Environment The doctoral student will be employed at the MT group at Fondazione Bruno Kessler, Trento, Italy. The group (about 10 people including staff and students) has a long tradition in research on machine and speech translation and is currently involved in several projects. Former students are nowadays employed in leading IT companies in the world. Benefits Fondazione Bruno Kessler offers an attractive benefits package, including a flexible work week, full reimbursement for conferences and summer schools, a competitive salary, an excellent team of supervisors and mentors, help for housing, full health insurance, the possibility of Italian courses, and sporting facilities. Further Information For preliminary interviews, and should you need further information about the position, please contact Matteo Negri (negri(a)fbk.eu). Best Regards, Matteo Negri -- -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

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EVALITA 2023: Call for NLP tasks
by Marco Polignano 04 Aug '22

04 Aug '22

****************************************************** *********** EVALITA 2023: Call for tasks *********** ****************************************************** *EVALITA 2023 *is an initiative of AILC (Associazione Italiana di Linguistica Computazionale, *AILC* https://www.ai-lc.it/). As in the previous editions (https://www.evalita.it/), EVALITA 2023 will be organized along a few selected tasks, which provide participants with opportunities to discuss and explore both emerging and traditional areas of *Natural Language Processing and Speech*. The participation is encouraged for teams working both in academic institutions and industrial organizations. *TASK PROPOSAL SUBMISSION* Tasks proposals should be no longer than 4 pages and should include: - task title and acronym; - names and affiliation of the organizers (minimum 2 organizers); - brief task description, including motivations and state of the art; - explanation of the international relevance of the task; - description and examples of the data, including information about their availability, development stage, and issues concerning privacy and data sensitivity. The examples are mandatory because they are intended to give potential participants an idea of what the task data will look like, how it’ll be formatted, etc. - expected number of participants and attendees; - names and contact information of the organizers. /In submitting your proposal, please bear in mind that we encourage:/ - c*hallenging tasks* involving linguistic analysis, e.g., beyond “simple” classification problems; - tasks focused on multimodality, e.g., considering both textual and visual information; - tasks characterized by *different levels of complexity*, e.g., with a straightforward main subtask and one or more sophisticated additional subtasks; - the re-annotation/expansion of datasets from previous years with new annotation levels, and texts from publicly available corpora; - both new tasks and re-runs: for new tasks, organizers will have to specify in the proposal why it would attract a reasonable number of participants, and why it is needed; - application-oriented tasks, that is tasks that have a clearly defined end-user application showcasing; - *multilingual tasks*, i.e. with data both in Italian and in other languages; - *industrial tasks*, i.e. task with real data provided by companies. The organizers of the accepted tasks should take care of planning, according to the scheduled deadlines (see below): - the development and distribution of datasets needed for the contest, i.e. data for training and development, and data for testing; the scorer to be used to evaluate the submitted systems should be included in the release of development data; - the development of task guidelines, where all the instructions for the participation are made clear together with a detailed description of data and evaluation metrics applied for the evaluation of the participant results; - the collection of participants results; - the evaluation of participants results according to standard metrics and baseline(s); - the solicitation of participation and of submissions; - the reviewing process of the papers describing the participants approach and results (according to the template to be made available by the EVALITA 2023 chairs); - the production of a paper describing the task (according to the template to be made available by the EVALITA 2023 chairs). **** Email your proposal in PDF format to evalita2023(a)gmail.com with "EVALITA 2023 TASK Proposal" as the subject line by the submission deadline: October 4th 2022. **** Please feel free to contact the EVALITA 2023 chairs at evalita2023(a)gmail.com in case of any questions or suggestions. Deadlines of the task proposal: - October 4th 2022: submission of task proposals - October 18th 2022: notification of task proposal acceptance *Tentative timelines of EVALITA 2023:* - 17th January 2023: development data available to participants - 13th April 2023: registration closes - 14th - 27th April 2023: evaluation windows - 4th May 2023: assessment returned to participants - first half of July: final workshop, location to be announced shortly *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)

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TempoWiC shared task at EMNLP EvoNLP Workshop: Evaluation starts (deadline: September 12)
by Jose Camacho Collados 04 Aug '22

04 Aug '22

************************************ Call for participation: TempoWiC shared task at EvoNLP shared task (co-located with EMNLP) Training and test data available! Shared Task website: https://sites.google.com/view/evonlp/shared-task Codalab evaluation page: https://codalab.lisn.upsaclay.fr/competitions/5360 Important dates: * 1 August 2022: Test data released and evaluation phase starts * 12 September 2022: Evaluation phase ends * 16 September 2022: Results released * 10 October 2022: System description paper deadline ************************************ TempoWiC is the Shared Task for the "EvoNLP: The First Workshop on Ever Evolving NLP" workshop, co-located with EMNLP 2022. For this novel temporal meaning shift task, users are given a pair of sentences (or, in this case, tweets) and a target word (e.g. delta), and the task consists of deciding whether the meaning of the target word is the same or not. Basically, the framing is the same binary classification as the original WiC (Word-in-Context) task but adapted so the temporal aspect is taken into account (tweets in each pair were selected from different time periods). For example, we can observe a meaning shift happening to the word folklore in the following instance, where its meaning represents a recent music album in the second example. (1) There's a thunderstorm outside so clearly it's the perfect time to watch videos about folklore monsters. (August 2019) (2) Cardigan on folklore is my favorite song. I wish @taylorswift13 would love me (August 2020) -- Jose Camacho Collados http://www.josecamachocollados.com<http://www.josecamachocollados.com/>

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Open position: Independent Research Group Leader in Natural Language Processing, TU Darmstadt, Germany
by Elisabeth Niemann 04 Aug '22

04 Aug '22

The Department of Computer Science at the Technical University of Darmstadt keeps growing - we are now looking for an Independent Research Group Leader (equivalent to the assistant professor level) in NLP to join our team! Are you interested in doing cutting-edge research on Natural Language Processing and AI, often in collaboration with top academic and industrial partners? We are a diverse team working on some of the hardest and most exciting machine learning challenges, including representation learning, neural IR, explainable NLP, continual learning, multi-task learning, self-supervised learning, and more. Visit our website and read more about the opening: https://www.informatik.tu-darmstadt.de/ukp/ukp_home/jobs_ukp/2022_independe… -------------------------------------------------------------------- Prof. Dr. Iryna Gurevych UKP Lab Computer Science Department Technical University Darmstadt, Germany http://www.ukp.tu-darmstadt.de/

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Associate Research Scientist in Machine Learning and Natural Language Processing, UKP Lab Darmstadt (Germany)
by Elisabeth Niemann 04 Aug '22

04 Aug '22

The Ubiquitous Knowledge Processing (UKP) Lab at the Department of Computer Science, Technical University Darmstadt in Germany has several ERC-, HORIZON- or DFG-funded openings for an Associate Research Scientist (PostDoc- or PhD-level; for an initial term of two to three years) in Machine Learning and Natural Language Processing. As an interdisciplinary team, we are happy to accommodate a wide variety of research questions and backgrounds, ranging from machine learning to dataset creation. We particularly welcome proposals on neuro-symbolic reasoning, multilingual and multimodal language modeling, and creative ideas on modeling cross-document relations. Interested to become part of our diverse, ambitious and successful team doing cutting edge research? Visit our website and read more about the openings: https://www.informatik.tu-darmstadt.de/ukp/ukp_home/jobs_ukp/2022_associiat… -------------------------------------------------------------------- Prof. Dr. Iryna Gurevych UKP Lab Technical University Darmstadt, Germany http://www.ukp.tu-darmstadt.de/

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Important UPDATES/EXTENSION: ClinSpEn medical machine translation sub-track (Biomedical WMT Task, EMNLP 2022)
by Salvador Lima 04 Aug '22

04 Aug '22

Important UPDATES/EXTENSION: ClinSpEn sub-track (Biomedical WMT Task, EMNLP 2022) Machine Translation of Clinical cases, ontologies & medical entities: Spanish - English https://temu.bsc.es/clinspen/ Evaluation period extension, test and background data available on Zenodo and CodaLab submission available. The ClinSpEn track of the Biomedical WMT 2022 shared task tries to address a pressing need and emerging research topic related to the development and exploitation of multilingual clinical NLP and text mining applications. Recent advances in neural machine translation approaches (MT) adapted to specific domains and text genres have resulted in promising results that facilitate processing of healthcare and clinical data beyond language silos. The ClinSpEn sub-track tries to promote the use of advanced machine translation technologies applied to three high impact healthcare application scenarios: (1) automatic translation of clinical case documents of importance to examine how MT could be further applied to cope with clinical records (2) automatic translation of clinical terms and entity mentions extracted directly from medical records and literature to improve multilingual semantic annotation technologies (3) automatic translation of ontologies and controlled vocabulary concepts of uttermost importance for multilingual data and concept normalization These three scenarios will be addressed by three specific benchmark data collections used for evaluation purposes by the ClinSpEn biomedical WMT track: ClinSpEn-CC (Clinical Cases): EN>ES translation of clinical case documents. ClinSpEn-CT (Clinical Terms): ES>EN translation of clinical terms and entity mentions extracted from records and literature. ClinSpEn-OC (Ontology Concepts): EN>ES translation of highly used open clinical controlled vocabularies and ontology concepts. Important links: - ClinSpEn web: https://temu.bsc.es/clinspen/ - Biomedical WMT web: https://statmt.org/wmt22/biomedical-translation-task.html - WMT2022: https://statmt.org/wmt22/ - EMNLP conference: https://2022.emnlp.org/ - Data (NEW!): - Clinical Cases: https://doi.org/10.5281/zenodo.6497350 - Clinical Terms: https://doi.org/10.5281/zenodo.6497372 - Ontology Concepts: https://doi.org/10.5281/zenodo.6497388 - CodaLab: https://codalab.lisn.upsaclay.fr/competitions/6696 - Team Registration (mandatory): https://temu.bsc.es/clinspen/registration/ For the ClinSpEn track Gold Standard manual translations generated by professional medical translators have been generated to evaluate participating teams. The primary evaluation metric to be used for this track will be SacreBLEU. Participants will also have access to a larger background collection to promote scalability and robustness assessment of machine translation technology. Updated schedule: - Participant Predictions Due: August 30th, 2022 (UPDATED EXTENSION!) - Paper Submission: September 7th, 2022 - Acceptance notification: October 9th, 2022 - Camera-ready version: October 16th, 2022 - WMT workshop at EMNLP: December 7th and 8th, 2022 Publications and workshop Participating teams will be invited to contribute a systems description paper for the WMT 2022 Working Notes proceedings. This workshop will be part of the prestigious EMNLP 2022 conference. More information on the paper’s specifications, formatting guidelines and review process at: https://statmt.org/wmt22/index.html. ClinSpEn Track Organizers - Salvador Lima-López (BSC) - Darryl Johan Estrada (BSC) - Eulàlia Farré-Maduell (BSC) - Martin Krallinger (BSC) Biomedical WMT Organizers - Rachel Bawden (University of Edinburgh, UK) - Giorgio Maria Di Nunzio (University of Padua, Italy) - Darryl Johan Estrada (Barcelona Supercomputing Center, Spain) - Eulàlia Farré-Maduell (Barcelona Supercomputing Center, Spain) - Cristian Grozea (Fraunhofer Institute, Germany) - Antonio Jimeno Yepes (University of Melbourne, Australia) - Salvador Lima-López (Barcelona Supercomputing Center, Spain) - Martin Krallinger (Barcelona Supercomputing Center, Spain) - Aurélie Névéol (Université Paris Saclay, CNRS, LISN, France) - Mariana Neves (German Federal Institute for Risk Assessment, Germany) - Roland Roller (DFKI, Germany) - Amy Siu (Beuth University of Applied Sciences, Germany) - Philippe Thomas (DFKI, Germany) - Federica Vezzani (University of Padua, Italy) - Maika Vicente Navarro, Maika Spanish Translator, Melbourne, Australia - Dina Wiemann (Novartis, Switzerland) - Lana Yeganova (NCBI/NLM/NIH, USA -- Salvador Lima Lopez RESEARCH ENGINEER Life Sciences - Text Mining, BSC-CNS Barcelona, Spain

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[OM-2022] 2nd CFP: 17th workshop on Ontology Matching collocated with ISWC
by Cassia TROJAHN 04 Aug '22

04 Aug '22

** With apologies for multiple posting ** The Seventeenth International Workshop on ONTOLOGY MATCHING (OM-2022) http://om2022.ontologymatching.org/ October 23rd or 24th, 2022, International Semantic Web Conference (ISWC) Workshop Program, Hybrid conference, Hangzhou, China BRIEF DESCRIPTION AND OBJECTIVES Ontology matching is a key interoperability enabler for the Semantic Web, as well as a useful technique in some classical data integration tasks dealing with the semantic heterogeneity problem. It takes ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those ontologies. These correspondences can be used for various tasks, such as ontology merging, data interlinking, query answering or navigation over knowledge graphs. Thus, matching ontologies enables the knowledge and data expressed with the matched ontologies to interoperate. The workshop has three goals: 1. To bring together leaders from academia, industry and user institutions to assess how academic advances are addressing real-world requirements. The workshop will strive to improve academic awareness of industrial and final user needs, and therefore, direct research towards those needs. Simultaneously, the workshop will serve to inform industry and user representatives about existing research efforts that may meet their requirements. The workshop will also investigate how the ontology matching technology is going to evolve, especially with respect to data interlinking, knowledge graph and web table matching tasks. 2. To conduct an extensive and rigorous evaluation of ontology matching and instance matching (link discovery) approaches through the OAEI (Ontology Alignment Evaluation Initiative) 2022 campaign: http://oaei.ontologymatching.org/2022/ 3. To examine similarities and differences from other, old, new and emerging, techniques and usages, such as web table matching or knowledge embeddings. TOPICS of interest include but are not limited to: Business and use cases for matching (e.g., big, open, closed data); Requirements to matching from specific application scenarios (e.g., public sector); Application of matching techniques in real-world scenarios (e.g., in cloud, with mobile apps); Formal foundations and frameworks for matching; Novel matching methods, including link prediction, ontology-based access; Matching and knowledge graphs; Matching and deep learning; Matching and embeddings; Matching and big data; Matching and linked data; Instance matching, data interlinking and relations between them; Privacy-aware matching; Process model matching; Large-scale and efficient matching techniques; Matcher selection, combination and tuning; User involvement (including both technical and organizational aspects); Explanations in matching; Social and collaborative matching; Uncertainty in matching; Expressive alignments; Reasoning with alignments; Alignment coherence and debugging; Alignment management; Matching for traditional applications (e.g., data science); Matching for emerging applications (e.g., web tables, knowledge graphs). SUBMISSIONS Contributions to the workshop can be made in terms of technical papers and posters/statements of interest addressing different issues of ontology matching as well as participating in the OAEI 2022 campaign. Long technical papers should be of max. 12 pages. Short technical papers should be of max. 5 pages. Posters/statements of interest should not exceed 2 pages. All contributions have to be prepared using the LNCS Style: http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0 and should be submitted in PDF format (no later than August 9th, 2022) through the workshop submission site at: https://www.easychair.org/conferences/?conf=om2022 Contributors to the OAEI 2022 campaign have to follow the campaign conditions and schedule at http://oaei.ontologymatching.org/2022/. DATES FOR TECHNICAL PAPERS AND POSTERS: August 9th, 2022: Deadline for the submission of papers. September 6th, 2022: Deadline for the notification of acceptance/rejection. September 20th, 2022: Workshop camera ready copy submission. October 23rd or 24th, 2022: OM-2022, hybrid conference, Hangzhou, China. Contributions will be refereed by the Program Committee. Accepted papers will be published in the workshop proceedings as a volume of CEUR-WS as well as indexed on DBLP. ORGANIZING COMMITTEE 1. Pavel Shvaiko (main contact) Trentino Digitale, Italy 2. Jérôme Euzenat INRIA & Univ. Grenoble Alpes, France 3. Ernesto Jiménez-Ruiz City, University of London, UK & SIRIUS, University of Oslo, Norway 4. Oktie Hassanzadeh IBM Research, USA 5. Cássia Trojahn IRIT, France PROGRAM COMMITTEE (to be completed): Alsayed Algergawy, Jena University, Germany Manuel Atencia, Universidad de Málaga, Spain Jiaoyan Chen, University of Oxford, UK Jérôme David, University Grenoble Alpes & INRIA, France Gayo Diallo, University of Bordeaux, France Daniel Faria, Instituto Gulbenkian de Ciéncia, Portugal Alfio Ferrara, University of Milan, Italy Marko Gulic, University of Rijeka, Croatia Wei Hu, Nanjing University, China Ryutaro Ichise, National Institute of Informatics, Japan Antoine Isaac, Vrije Universiteit Amsterdam & Europeana, Netherlands Naouel Karam, Fraunhofer, Germany Prodromos Kolyvakis, EPFL, Switzerland Patrick Lambrix, Linköpings Universitet, Sweden Oliver Lehmberg, University of Mannheim, Germany Fiona McNeill, University of Edinburgh, UK Majid Mohammadi, Eindhoven University of Technology, Netherlands Hoa Ngo, CSIRO, Australia George Papadakis, University of Athens, Greece Henry Rosales-Méndez, University of Chile, Chile Booma Sowkarthiga, Microsoft, USA Kavitha Srinivas, IBM, USA Ludger van Elst, DFKI, Germany Xingsi Xue, Fujian University of Technology, China Ondrej Zamazal, Prague University of Economics, Czech Republic Songmao Zhang, Chinese Academy of Science, China Lu Zhou, TigerGraph, USA --------------------- Best regards, Cassia

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PhD opening: Adaptive Multimodal Conversational Agents
by Raffaella Bernardi 04 Aug '22

04 Aug '22

The IECS Doctoral School, at the University of Trento, has several PhD openings. Application deadline on September* 6, 2022 hrs. 04:00 PM *(CEST). See here for details: https://iecs.unitn.it/education/admission/call-for-application If you are interested in the project on *Adaptive Multimodal conversational agents* that will be run in collaboration with Amazon Alexa (in Berlin), please contact me at raffaella.bernardi(a)unitn.it I am looking for PhD candidates with a strong background in Computer Science, in particular on Machine Learning, ideally with some expertise on Natural Language Processing/Natural Language Generation. ============================================================== University of Trento CIMeC: C225, second floor, Corso Bettini 31, 38068 Rovereto (TN), DISI: Povo 2, Room: 110, Via Sommarive 9, I 38123, Povo (TN) Tel. +39 0464 80 8704 (CIMeC) http://disi.unitn.it/~bernardi/ ==============================================================

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[CfP] Workshop on Text Simplification, Accessibility, and Readability (TSAR) @ EMNLP 2022
by Daniel Ferrés 03 Aug '22

03 Aug '22

Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022) Workshop and Shared Task at EMNLP 2022 Workshop: https://taln.upf.edu/pages/tsar2022-ws Shared Task: https://taln.upf.edu/pages/tsar2022-st Call for Papers The web provides an abundance of knowledge and information that can reach large populations. However, the way in which a text is written (vocabulary, syntax, or text organization/structure), or presented, can make it inaccessible for many people, especially for non-native speakers, people with low literacy, and people with some type of cognitive or linguistic impairments. The results of the Adult Literacy Survey (OECD, 2013) indicate that approximately 16.7% of the adult population (averaged over 24 highly-developed countries) requires lexical, 50% syntactic, and 89.4% conceptual simplification of everyday texts (Štajner, 2021). Research on automatic text simplification (TS), textual accessibility, and readability have the potential to improve social inclusion of marginalized populations. These related research areas have attracted attention in the past ten years, evidenced by the growing number of publications in NLP conferences. While only about 300 articles in Google Scholar mentioned TS in 2010, this number has increased to about 600 in 2015 and greater than 1000 in 2020 (Štajner, 2021). Recent research in automatic text simplification has mostly focused on proposing the use of methods derived from the deep learning paradigm (Glavaš and Štajner, 2015; Paetzold and Specia, 2016; Nisioi et al., 2017; Zhang and Lapata, 2017; Martin et al., 2020; Maddela et al., 2021; Sheang and Saggion, 2021). However, there are many important aspects of automatic text simplification that need the attention of our community: the design of appropriate evaluation metrics, the development of context-aware simplification solutions, the creation of appropriate language resources to support research and evaluation, the deployment of simplification in real environments for real users, the study of discourse factors in text simplification, the identification of factors affecting the readability of a text, etc. To overcome those issues, there is a need for collaboration of CL/NLP researchers, machine learning and deep learning researchers, UI/UX and Accessibility professionals, as well as public organizations representatives (Štajner, 2021). The proposed TSAR workshop builds upon the recent success of several regional workshops that covered a subset of our topics of interest, including READI Workshops at LREC 2022 and LREC 2022, SEPLN 2021 Workshop on Current Trends in Text Simplification (CTTS) and the SimpleText workshop at CLEF 2021, as well as the birds-of-a-feather events on Text Simplification at NAACL 2021 (over 50 participants) and ACL 2022. The TSAR workshop aims to foster collaboration among all parties interested in making information more accessible to all people. Through the two invited talks, a shared task on lexical simplification, the round table discussion, oral and poster presentations of novel research, we will discuss recent trends and developments in the area of automatic text simplification, text accessibility, automatic readability assessment, language resources and evaluation for text simplification, etc. Topics We invite contributions on the following topics (among others): Lexical simplification; Syntactic simplification; Modular and end-to-end TS; Sequence-to-sequence and zero-shot TS; Controllable TS; Text complexity assessment; Complex word identification and lexical complexity prediction; Corpora, lexical resources, and benchmarks for TS; Evaluation of TS systems; Domain specific/adaptable TS (e.g. health, legal); Other related topics (e.g. empirical and eye-tracking studies); Assistive technologies for improving readability and comprehension including those going beyond text. Text Simplification in Languages other than English Multilingual TS Readability Controlled MT Submissions We welcome two types of papers: long papers and short papers. Submissions should be made to the Softconf submission management system: https://softconf.com/emnlp2022/tsar. The papers should present novel research. The review will be double blind and thus all submissions should be anonymized. Format: Paper submissions must use the official EMNLP template, which is available as an Overleaf template and also downloadable directly (Latex and Word) (see here: https://2022.emnlp.org/calls/style-and-formatting/). Authors may not modify these style files or use templates designed for other conferences. Submissions that do not conform to the required styles, including paper size, margin width, and font size restrictions, will be rejected without review. Long Papers: Long papers must describe substantial, original, completed, and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included. Long papers may consist of up to eight (8) pages of content, plus unlimited pages of references. Final versions of long papers will be given one additional page of content (up to 9 pages), so that reviewers’ comments can be taken into account. Long papers will be presented orally or as posters as determined by the program committee. The decisions as to which papers will be presented orally and which as poster presentations will be based on the nature rather than the quality of the work. There will be no distinction in the proceedings between long papers presented orally and long papers presented as posters. Short Papers: Short paper submissions must describe original and unpublished work. Please note that a short paper is not a shortened long paper. Instead, short papers should have a point that can be made in a few pages. Some kinds of short papers include: a small, focused contribution; a negative result; an opinion piece; an interesting application nugget Short papers may consist of up to four (4) pages of content, plus unlimited pages of references. Final versions of short papers will be given one additional page of content (up to 5 pages), so that reviewers' comments can be taken into account. Short papers will be presented orally or as posters as determined by the program committee. While short papers will be distinguished from long papers in the proceedings, there will be no distinction in the proceedings between short papers presented orally and short papers presented as posters. Important Dates 7 September 2022: Workshop paper submission deadline (Softconf) 2 October 2022: Workshop paper notification deadline 16 October 2022: Workshop paper camera ready deadline 8 December 2022: Workshop Proceedings All accepted papers will be included in the workshop proceedings and published in ACL Anthology. Extended versions of best papers will be invited for a special issue of Frontiers in Artificial Intelligence focused on: applied research for TS and readability assessment in the context of TS. Organizers Sanja Štajner, NLP Researcher, Germany Horacio Saggion, Chair in Computer Science and Artificial Intelligence and Head of the LaSTUS Lab in the TALN-DTIC, Universitat Pompeu Fabra Wei Xu, Assistant Professor at School of Interactive Computing, Georgia Institute of Technology Marcos Zampieri, Assistant Professor at the Rochester Institute of Technology Matthew Shardlow, Senior Lecturer at Manchester Metropolitan University Daniel Ferrés, Post-Doctoral Research Assistant at LaSTUS Lab. at TALN-DTIC, Universitat Pompeu Fabra Kai North, Ph.D. student at the Rochester Institute of Technology Kim Cheng Sheang, PhD student at LaSTUS Lab. at TALN-DTIC, Universitat Pompeu Fabra Program committee (Tentative) Rodrigo Alarcón (Universidad Carlos III, Spain) Fernando Alva Manchego (University of Sheffield, UK) Susana Bautista (Universidad Francisco de Vitoria, Spain) Antoine Bordes (Facebook, UK) Remi Cardon (Université Catholique de Louvain, Belgium) Eric De la Clergerie (INRIA, France) Felice Dell'Orletta (Istituto di Linguistica Computazionale “Antonio Zampolli”, Italy) Thomas François (Université catholique de Louvain, Belgique) Nuria Gala (Université Aix-Marseille, France) Goran Glavaš (University of Mannheim, Germany) Itziar Gonzalez-Dios (University of the Basque Country, Spain) Natalia Grabar (Université de Lille, France) Raquel Hervás (Universidad Complutense de Madrid, Spain) Tomoyuki Kajiwara (Ehime University, Japan) David Kauchak (Pomona College, USA) Reno Kriz (University of Pennsylvania, USA) Louis Martin (Facebook, UK) Lourdes Moreno López (Universidad Carlos III, Spain) Christina Niklaus (University St. Gallen, Switzerland) Benoît Sagot (INRIA, France) Giulia Venturi (Istituto di Linguistica Computazionale “Antonio Zampolli”, Italy) Victoria Yaneva (National Board of Medical Examiners, USA) CONTACT Feel free to send us messages at: Email: horacio.saggion(a)upf.edu

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