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First Call For Papers and Participation: BioNLP 2023 and BioNLP Shared Tasks 2023 (co-located with ACL 2023)
by dina demner 10 Jan '23

10 Jan '23

BIONLP 2023 and Shared Tasks @ ACL 2023 https://aclweb.org/aclwiki/BioNLP_Workshop#SHARED_TASKS_2023 *Tentative* Important Dates(All submission deadlines are 11:59 p.m. UTC-12:00 “anywhere on Earth”)May 1, 2023: Workshop Paper Due DateJune 15, 2023: Camera-ready papers dueBioNLP 2023 Workshop at ACL, July 13 OR 14, 2023, Toronto, Canada Please watch for the updates! SUBMISSION INSTRUCTIONS-----------------------------------------Two types of submissions are invited: full papers and short papers. Full papers should not exceed eight (8) pages of text, plus unlimited references. These are intended to be reports of original research. BioNLP aims to be the forum for interesting, innovative, and promising work involving biomedicine and language technology, whether or not yielding high performance at the moment. This by no means precludes our interest in and preference for mature results, strong performance, and thorough evaluation. Both types of research and combinations thereof are encouraged. Short papers may consist of up to four (4) pages of content, plus unlimited references. Appropriate short paper topics include preliminary results, application notes, descriptions of work in progress, etc. Electronic SubmissionSubmissions must be electronic and in PDF format, using the Softconf START conference management system Submissions need to be anonymous. *The submission site will be announced shortly.* Dual submission policy: papers may NOT be submitted to the BioNLP 2017 workshop if they are or will be concurrently submitted to another meeting or publication. WORKSHOP OVERVIEW AND SCOPE---------------------------------------------------The BioNLP workshop associated with the ACL SIGBIOMED special interest group has established itself as the primary venue for presenting foundational research in language processing for the biological and medical domains. The workshop is running every year since 2002 and continues getting stronger. BioNLP welcomes and encourages work on languages other than English, and inclusion and diversity. BioNLP truly encompasses the breadth of the domain and brings together researchers in bio- and clinical NLP from all over the world. The workshop will continue presenting work on a broad and interesting range of topics in NLP. The interest to biomedical language has broadened significantly due to the COVID-19 pandemic and continues to grow: as access to information becomes easier and more people generate and access health-related text, it becomes clearer that only language technologies can enable and support adequate use of the biomedical text. BioNLP 2023 will be particularly interested in language processing that supports DEIA (Diversity, Equity, Inclusion and Accessibility). The work on detection and mitigation of bias and misinformation continues to be of interest. Research in languages other than English, particularly, under-represented languages, and health disparities are always of interest to BioNLP. Other active areas of research include, but are not limited to: Tangible results of biomedical language processing applications;Entity identification and normalization (linking) for a broad range of semantic categories;Extraction of complex relations and events;Discourse analysis;Anaphora/coreference resolution;Text mining / Literature based discovery;Summarization;Τext simplification;Question Answering;Resources and strategies for system testing and evaluation;Infrastructures and pre-trained language models for biomedical NLP (Processing and annotation platforms);Development of synthetic data & data augmentation;Translating NLP research into practice;Getting reproducible results. SHARED TASKS 2023-------------------------------------Shared Tasks on Summarization of Clinical Notes and Scientific Articles The first task focuses on Clinical Text. Task 1A. Problem List SummarizationAutomatically summarizing patients’ main problems from the daily care notes in the electronic health record can help mitigate information and cognitive overload for clinicians and provide augmented intelligence via computerized diagnostic decision support at the bedside. The task of Problem List Summarization aims to generate a list of diagnoses and problems in a patient’s daily care plan using input from the provider’s progress notes during hospitalization.This task aims to promote NLP model development for downstream applications in diagnostic decision support systems that could improve efficiency and reduce diagnostic errors in hospitals. This task will contain 768 hospital daily progress notes and 2783 diagnoses in the training set, and a new set of 300 daily progress notes will be annotated by physicians as the test set. The annotation methods and annotation quality have previously been reported here. The goal of this shared task is to attract future research efforts in building NLP models for real-world decision support applications, where a system generating relevant and accurate diagnoses will assist the healthcare providers’ decision-making process and improve the quality of care for patients. Task 1B. Radiology report summarizationRadiology report summarization is a growing area of research. Given the Findings and/or Background sections of a radiology report, the goal is to generate a summary (called an Impression section) that highlights the key observations and conclusions of the radiology study. The research area of radiology report summarization currently faces an important limitation: most research is carried out on chest X-rays. To palliate these limitations, we propose two datasets: A shared summarization task that includes six different modalities and anatomies, totalling 79,779 samples, based on the MIMIC-III database.A shared summarization task on chest x-ray radiology reports with images and a brand new out-of-domain test-set from Stanford. SEE MORE at: https://vilmedic.app/misc/bionlp23/sharedtask Task 2. Lay Summarization of Biomedical Research ArticlesBiomedical publications contain the latest research on prominent health-related topics, ranging from common illnesses to global pandemics. This can often result in their content being of interest to a wide variety of audiences including researchers, medical professionals, journalists, and even members of the public. However, the highly technical and specialist language used within such articles typically makes it difficult for non-expert audiences to understand their contents. Abstractive summarization models can be used to generate a concise summary of an article, capturing its salient point using words and sentences that aren’t used in the original text. As such, these models have the potential to help broaden access to highly technical documents when trained to generate summaries that are more readable, containing more background information and less technical terminology (i.e., a “lay summary”). This shared task surrounds the abstractive summarization of biomedical research articles, with an emphasis on controllability and catering to non-expert audiences. Through this task, we aim to help foster increased research interest in controllable summarization that helps broaden access to technical texts and progress toward more usable abstractive summarization models in the biomedical domain. For more information, see: Main site: https://biolaysumm.org/CodaLab page - subtask 1: https://codalab.lisn.upsaclay.fr/competitions/9541CodaLab page - subtask 2: https://codalab.lisn.upsaclay.fr/competitions/9544 *Workshop Organizers* Dina Demner-Fushman, US National Library of Medicine Kevin Bretonnel Cohen, University of Colorado School of Medicine Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK Jun-ichi Tsujii, National Institute of Advanced Industrial Science and Technology, Japan

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First Call For Papers and Participation: BioNLP 2023 and BioNLP Shared Tasks 2023 (co-located with ACL 2023)
by dina demner 10 Jan '23

10 Jan '23

BIONLP 2023 and Shared Tasks @ ACL 2023 https://aclweb.org/aclwiki/BioNLP_Workshop#SHARED_TASKS_2023 *Tentative* Important Dates (All submission deadlines are 11:59 p.m. UTC-12:00 “anywhere on Earth”) May 1, 2023: Workshop Paper Due Date June 15, 2023: Camera-ready papers due BioNLP 2023 Workshop at ACL, July 13 OR 14, 2023, Toronto, Canada Please watch for the updates! SUBMISSION INSTRUCTIONS ----------------------------------------- Two types of submissions are invited: full papers and short papers. Full papers should not exceed eight (8) pages of text, plus unlimited references. These are intended to be reports of original research. BioNLP aims to be the forum for interesting, innovative, and promising work involving biomedicine and language technology, whether or not yielding high performance at the moment. This by no means precludes our interest in and preference for mature results, strong performance, and thorough evaluation. Both types of research and combinations thereof are encouraged. Short papers may consist of up to four (4) pages of content, plus unlimited references. Appropriate short paper topics include preliminary results, application notes, descriptions of work in progress, etc. Electronic Submission Submissions must be electronic and in PDF format, using the Softconf START conference management system Submissions need to be anonymous. *The submission site will be announced shortly.* Dual submission policy: papers may NOT be submitted to the BioNLP 2017 workshop if they are or will be concurrently submitted to another meeting or publication. WORKSHOP OVERVIEW AND SCOPE --------------------------------------------------- The BioNLP workshop associated with the ACL SIGBIOMED special interest group has established itself as the primary venue for presenting foundational research in language processing for the biological and medical domains. The workshop is running every year since 2002 and continues getting stronger. BioNLP welcomes and encourages work on languages other than English, and inclusion and diversity. BioNLP truly encompasses the breadth of the domain and brings together researchers in bio- and clinical NLP from all over the world. The workshop will continue presenting work on a broad and interesting range of topics in NLP. The interest to biomedical language has broadened significantly due to the COVID-19 pandemic and continues to grow: as access to information becomes easier and more people generate and access health-related text, it becomes clearer that only language technologies can enable and support adequate use of the biomedical text. BioNLP 2023 will be particularly interested in language processing that supports DEIA (Diversity, Equity, Inclusion and Accessibility). The work on detection and mitigation of bias and misinformation continues to be of interest. Research in languages other than English, particularly, under-represented languages, and health disparities are always of interest to BioNLP. Other active areas of research include, but are not limited to: Tangible results of biomedical language processing applications; Entity identification and normalization (linking) for a broad range of semantic categories; Extraction of complex relations and events; Discourse analysis; Anaphora/coreference resolution; Text mining / Literature based discovery; Summarization; Τext simplification; Question Answering; Resources and strategies for system testing and evaluation; Infrastructures and pre-trained language models for biomedical NLP (Processing and annotation platforms); Development of synthetic data & data augmentation; Translating NLP research into practice; Getting reproducible results. SHARED TASKS 2023 ------------------------------------- Shared Tasks on Summarization of Clinical Notes and Scientific Articles The first task focuses on Clinical Text. Task 1A. Problem List Summarization Automatically summarizing patients’ main problems from the daily care notes in the electronic health record can help mitigate information and cognitive overload for clinicians and provide augmented intelligence via computerized diagnostic decision support at the bedside. The task of Problem List Summarization aims to generate a list of diagnoses and problems in a patient’s daily care plan using input from the provider’s progress notes during hospitalization.This task aims to promote NLP model development for downstream applications in diagnostic decision support systems that could improve efficiency and reduce diagnostic errors in hospitals. This task will contain 768 hospital daily progress notes and 2783 diagnoses in the training set, and a new set of 300 daily progress notes will be annotated by physicians as the test set. The annotation methods and annotation quality have previously been reported here. The goal of this shared task is to attract future research efforts in building NLP models for real-world decision support applications, where a system generating relevant and accurate diagnoses will assist the healthcare providers’ decision-making process and improve the quality of care for patients. Task 1B. Radiology report summarization Radiology report summarization is a growing area of research. Given the Findings and/or Background sections of a radiology report, the goal is to generate a summary (called an Impression section) that highlights the key observations and conclusions of the radiology study. The research area of radiology report summarization currently faces an important limitation: most research is carried out on chest X-rays. To palliate these limitations, we propose two datasets: A shared summarization task that includes six different modalities and anatomies, totalling 79,779 samples, based on the MIMIC-III database. A shared summarization task on chest x-ray radiology reports with images and a brand new out-of-domain test-set from Stanford. SEE MORE at: https://vilmedic.app/misc/bionlp23/sharedtask Task 2. Lay Summarization of Biomedical Research Articles Biomedical publications contain the latest research on prominent health-related topics, ranging from common illnesses to global pandemics. This can often result in their content being of interest to a wide variety of audiences including researchers, medical professionals, journalists, and even members of the public. However, the highly technical and specialist language used within such articles typically makes it difficult for non-expert audiences to understand their contents. Abstractive summarization models can be used to generate a concise summary of an article, capturing its salient point using words and sentences that aren’t used in the original text. As such, these models have the potential to help broaden access to highly technical documents when trained to generate summaries that are more readable, containing more background information and less technical terminology (i.e., a “lay summary”). This shared task surrounds the abstractive summarization of biomedical research articles, with an emphasis on controllability and catering to non-expert audiences. Through this task, we aim to help foster increased research interest in controllable summarization that helps broaden access to technical texts and progress toward more usable abstractive summarization models in the biomedical domain. For more information, see: Main site: https://biolaysumm.org/ CodaLab page - subtask 1: https://codalab.lisn.upsaclay.fr/competitions/9541 CodaLab page - subtask 2: https://codalab.lisn.upsaclay.fr/competitions/9544 *Workshop Organizers* Dina Demner-Fushman, US National Library of Medicine Kevin Bretonnel Cohen, University of Colorado School of Medicine Sophia Ananiadou, National Centre for Text Mining and University of Manchester, UK Jun-ichi Tsujii, National Institute of Advanced Industrial Science and Technology, Japan

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Final Call for Papers - Workshop on Language-Based AI Agent Interaction with Children
by Maike Paetzel-Prüsmann 09 Jan '23

09 Jan '23

Workshop on Language-Based AI Agent Interaction with Children https://aichildinteraction.github.io/ February 21st, 2023, in Los Angeles, USA & Virtual (Hybrid Format) Paper Submission Deadline: January 13th, 2023 (extended) Easychair: https://easychair.org/conferences/?conf=aiaic23 Contact: https://groups.google.com/g/ai-child-interactions or aichildinteraction(a)gmail.com More information about registering to our workshop for those not attending IWSDS will be shared in a separate call for participation closer to the workshop day. =================================================== In this workshop, we aim to bring together researchers looking into multimodal interactions between children and artificial agents to discuss research problems that center around interactivity and go beyond just processing child speech. We are interested in discussing approaches to collecting and annotating datasets involving child speech, intent classification in child speech, designing dialogue flow with artificial agents that primarily interact with children, as well as repair strategies, active listening behavior, and other aspects of dialogue modeling. Moreover, multiparty conversations involving several children, children, and their adult caregivers or several artificial agents are of particular interest to this workshop. Acknowledging the early-stage nature of research in this area, the workshop will invite short position papers as contributions. In addition to selected talks that will be invited based on the submitted papers, we will host roundtable discussions allowing attendees to discuss ideas, share challenges they have faced, and highlight ideas for future research.  ## Topics of Interest The workshop welcomes contributions across a wide range of topics including, but not limited to: Natural Language Understanding of Child Speech  Dialogue Modeling of Child-Agent, Child-Robot, Child-Child, and Child-Adult Speech  Conversational Flow and Repair in Dialogue with Children  Multiparty-Interaction Involving Children  Multimodal Processing of Child Interactions  Automatic Speech Recognition of Child Speech  Evaluating Child Interactions with Artificial Agents/Robots Challenges in Designing Interactions for Children  Datasets of Child-Child, Child-Adult, or Child-Agent/Robot Interaction Ethics and Responsible AI for Child-Agent/Robot Interaction Related Topics ## Important Dates - Paper submission deadline: January 13th, 2023 (extended) - Author Notification deadline: February 1st, 2023 - Workshop: February 21st, 2023 (morning session) ## Submission Guidelines We invite short position papers of 3-4 pages (plus additional pages for references and appendices without page limitation), including work in progress containing preliminary results, technical reports, case studies, surveys, and state-of-the-art research in language-based AI agent interactions with children. Recently submitted or published papers are welcome to be submitted to this workshop if they are highly relevant to the topic of the workshop. Please select the appropriate track during the EasyChair submission to mark the submission accordingly. Papers will be reviewed for their relevance, novelty, and scientific and technical soundness. Submissions do not need to be anonymized for review. All manuscripts must be written in English and submitted electronically in PDF format via EasyChair: https://easychair.org/conferences/?conf=aiaic23 Accepted papers will be published on the workshop website. However, papers are still considered non-archival and can be submitted to other conferences. Authors of accepted papers are expected to present their paper during the workshop in the form of a short talk, which can either be given in person in Los Angeles, USA, or virtually via Zoom. Authors should use the official IWSDS template: Latex Style and Template: https://drive.google.com/open?id=1mnzjvTlIVEsdPb2IZXbzxU8WRJj3mLiJ Overleaf: https://www.overleaf.com/read/djcrwzgrdjvj Word Template: https://drive.google.com/open?id=1WmO9iLvJtO0cH1E0VSC1bPsC0vRDpzbd ## Participation Participation in our workshop will be possible online or in person in Los Angeles. If you are planning on attending IWSDS, then you can register for the conference here: https://sites.google.com/view/iwsds2023/registration Registration to the main conference includes the workshop participation. If you would like to participate in our workshop only, please wait for further instructions on the registration process, which we will share in a separate call for participation closer to the workshop day. ## Contact If you have questions, please get in touch via our public Google Group https://groups.google.com/g/ai-child-interactions or by sending an e-mail to aichildinteraction(a)gmail.com

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2nd CFP: Special Issue on The Role of Context in Neural Machine Translation Systems and its Evaluation
by Knowles, Rebecca 09 Jan '23

09 Jan '23

*Apologies for cross-posting* [image.png] Second CFP: Special Issue on The Role of Context in Neural Machine Translation Systems and its Evaluation in Natural Language Engineering Guest editors: - Sheila Castilho (The ADAPT Centre, School of Applied Languages and Intercultural Studies, Dublin City University) - Rebecca Knowles (National Research Council Canada) For this special issue, we invite the submission of papers focusing on the variety of novel implementations of context into neural machine translation systems as well as novel approaches to its evaluation. Recent claims that machine translation systems are reaching (near) human parity at the sentence level have been followed by subsequent analyses that indicate remaining gaps in translation quality at the document level. How best to evaluate machine translation at the document level (and what exactly constitutes document level evaluation) remains an open question. At the same time, there is work seeking to add discourse and context into neural machine translation systems. Papers that focus on topics of context in neural machine translation, machine translation evaluation, or both are welcome. For full details, see: https://sites.google.com/dcu.ie/nlecontextnmt/home Topics of interest include, but are not limited to: - Novel language processing techniques for implementing discourse in NMT systems - Document-level NMT and evaluation - Use of target and source context - Context-aware techniques for quality evaluation - Context-aware automatic and human evaluation metrics - The size and composition of the training data and its effect on context-aware systems - The effect of the quality of training data and test sets on context-aware systems - Translationese and its effect on document-level training - Lexical diversity and lexical density in discourse NMT - Discourse NMT for different domains Publication Timeline: - Article deadline submission: 1 February 2023 - Return of reviews to contributors: 1 April 2023 - Revised articles deadline submission: 1 May 2023 - Return of second reviews to contributors (if applicable): 1 July 2023 - Final Submission: 15 September 2023 - Publication: November 2023 / January 2024 Format and Submission: Typical submissions will be 12-25 pages in length. Authors should follow the "Author Instructions" section on the journal website: https://www.cambridge.org/core/journals/natural-language-engineering/inform… We highly recommend using the LaTeX template found under "Preparing your materials" at the link above. All manuscripts must be submitted online via the NLE ScholarOne website: http://mc.manuscriptcentral.com/nle. Under "Special Issue Designation", choose "The Role of Context in Neural Machine Translation Systems and its Evaluation". Queries: Any queries related to this special issue should be addressed to sheila.castilho(a)dcu.ie<mailto:sheila.castilho@dcu.ie> with NLE-ContextNMT in the subject line.

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Postdoc Position (Hate Speech Detection) for up to 3 years in Milan
by mail＠dirkhovy.com 09 Jan '23

09 Jan '23

We are looking for postdocs to work with us on INDOMITA! Online hate speech has resulted in actual hate crimes. INDOMITA offers automated assistance to combat online hate speech. However, hatred is complex. The offensiveness of a phrase is determined by social customs and user demographics: “Yo, a**hole!” is acceptable among friends but not strangers. Our user-centric approach takes into account social customs and user demographics to enhance detection of nuanced forms of hate speech. We will use three strategies: - modeling a complex problem with socio-demographic context, - automating counter-argument and responding to aggressive users, and - creating evaluation methods to analyze fairness, performance, and subjectivity. Our research will bridge language gaps and shed light on the relationships between online actors and online hatred. We are seeking candidates to work on NLP, machine learning, and neural networks for representation learning, natural language understanding, and hate speech detection in various languages and modalities. Successful candidates will work closely with Prof. Dirk Hovy, Prof. Debora Nozza, and the MilaNLP lab. Your profile: • a Ph.D. in Computer Science, Computational Linguistics/NLP, Machine Learning, Data Science, or related fields. • Excellent programming skills in Python. Additional languages (C++, R, etc) a plus. • Fluency in spoken and written English. Knowledge of Italian is NOT a requirement. • Knowledge of current neural network models and implementation tools for neural networks (e.g. PyTorch, Tensorflow, Keras, etc.). • Proven track record with publications in top-tier venues in the field of NLP/Computational Linguistics/ML. Position Details: • Starting date: March 1 2023, or any time thereafter • Duration: 2 years, 1 year extension possible • Deadline: 23rd January 2023 • Salary: 42k EUR p.a. (median salary Milan: 37k EUR) Applicants from outside Italy may qualify for a researcher taxation scheme How to apply: Go to the https://jobmarket.unibocconi.eu/?type=a&urlBack=/wps/wcm/connect/Bocconi/Si… <https://jobmarket.unibocconi.eu/?type=a&urlBack=/wps/wcm/connect/Bocconi/Si…> and search for “INDOMITA”, you will then have to click on “Apply online” for proceeding with the application. Candidates should attach publications and a cover letter to their application. Online interviews will take place during February 2023. Please contact dirk.hovy(a)unibocconi.it <mailto:dirk.hovy@unibocconi.it> if you have any question.

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[cfp] QPP++ 2023: Query Performance Prediction and Its Evaluation in New Tasks @ ECIR
by Guglielmo Faggioli 09 Jan '23

09 Jan '23

*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 reconsidering how we perform and evaluate QPP. Important Dates Submission deadline: February 5th, 2023 Notification of acceptance: March 5th, 2023 Camera ready: March 15th, 2023 Workshop day: April 2nd, 2023 Conference days: April 3rd-6th, 2023 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. 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 like 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.* Submit your contribution via Easychair at the following link *https://easychair.org/conferences/?conf=qpp2023 <https://easychair.org/conferences/?conf=qpp2023>* To prepare the submission, use the one-column CEUR template. A precompiled version is available at *https://drive.google.com/file/d/1sTW16i0vlsVHVf75t0rC_30UVMPUmn3Z/view?usp=share_link <https://drive.google.com/file/d/1sTW16i0vlsVHVf75t0rC_30UVMPUmn3Z/view?usp=…>* Website *https://qpp.dei.unipd.it/ <https://qpp.dei.unipd.it/>* Organizers Guglielmo Faggioli, University of Padova, Italy, faggioli(a)dei.unipd.it Nicola Ferro, University of Padova, Italy, ferro(a)unipd.it Josiane Mothe, Université de Toulouse, IRIT, France, josiane.mothe(a)irit.fr Fiana Raiber, Yahoo Research, Israel, fiana(a)yahooinc.com

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First Call For Papers: The Forth Workshop on Insights from Negative Results (co-located with EACL 2023)
by Shabnam Tafreshi 08 Jan '23

08 Jan '23

Dear colleagues, The Fourth Workshop on Insights from Negative Results in NLP Co-located with EACL, May 2 or 6, 2023 First Call for Participation TO-BE-UPDATED: <https://insights-workshop.github.io/ <https://insights-workshop.github.io/index>> Contact email: insights-workshop-organizers(a)googlegroups.com *Overview Publication of negative results is difficult in most fields, but in NLP the problem is exacerbated by the near-universal focus on improvements in benchmarks. This situation implicitly discourages hypothesis-driven research, and it turns creation and fine-tuning of NLP models into art rather than science. Furthermore, it increases the time, effort, and carbon emissions spent on developing and tuning models, as the researchers have no opportunity to learn what has already been tried and failed. This workshop invites both practical and theoretical unexpected or negative results that have important implications for future research, highlight methodological issues with existing approaches, and/or points out pervasive misunderstandings or bad practices. In particular, the most successful NLP models currently rely on different kinds of pretrained meaning representations (from word embeddings to Transformer-based models like BERT and GPT-3). To complement all the success stories, it would be insightful to see where and possibly why they fail. Any NLP tasks are welcome: sequence labeling, question answering, inference, dialogue, machine translation - you name it. A successful negative results paper would contribute one of the following: ** broadly applicable recommendations for training/fine-tuning, especially if X that didn’t work is something that many practitioners would think reasonable to try, and if the demonstration of X’s failure is accompanied by some explanation/hypothesis; ** ablation studies of components in previously proposed models, showing that their contributions are different from what was initially reported; ** datasets or probing tasks showing that previous approaches do not generalize to other domains or language phenomena; ** trivial baselines that work suspiciously well for a given task/dataset; ** cross-lingual studies showing that a technique X is only successful for a certain language or language family; ** experiments on (in)stability of the previously published results due to hardware, random initializations, preprocessing pipeline components, etc; ** theoretical arguments and/or proofs for why X should not be expected to work; ** demonstration of issues with data processing/collection/annotation pipelines, especially if they are widely used; ** demonstration of issues with evaluation metrics (e.g. accuracy, F1, or BLEU), which prevent their usage for fair comparison of methods. * Important Dates ** Submission due: February 13, 2023 ** Submission due for papers reviewed through ACL Rolling Review: March 17, 2023 ** Notification of acceptance: March 13, 2023 ** Camera-ready papers due: March 27, 2023 ** Workshop: May 2 or 6, 2023 * Submission Submission is electronic, using the Softconf START conference management system. Submission link: <https://softconf.com/eacl2023/insights2023/> The workshop will accept short papers (up to 4 pages, excluding references), as well as 1-2 page non-archival abstract submissions for papers published elsewhere (e.g. in one of the main conferences or in non-NLP venues). The goal of this event is to stimulate a meaningful community-wide discussion of the deep issues in NLP methodology, and the authors of both types of submissions will be welcome to take part in our get-togethers. The workshop will run its own review process, and papers can be submitted directly to the workshop by March 13, 2023. It is also possible to submit a paper accompanied by reviews from the ACL Rolling Review system by March 17, 2023. The submission deadline for ARR papers follows the ACL RR calendar. Both research papers and abstracts must follow the ACL two-column format. Official style sheets: <https://www.overleaf.com/read/crtcwgxzjskr> <https://github.com/acl-org/ACLPUB/tree/master/templates> Please do not modify these style files, nor should you 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. * Multiple Submission Policy The workshop cannot accept work for publication or presentation that will be (or has been) published elsewhere and that has been or will be submitted to other meetings or publications whose review periods overlap with that of Insights. Any questions regarding submissions can be sent to insights-workshop-organizers(a)googlegroups.com. If the paper has been rejected from another venue, the authors will have the option to provide the original reviews and the author's response. The new reviewers will not have access to this information, but the organizers will be able to take into account the fact that the paper has already been revised and improved. * Anonymity Period We are not enforcing any anonymity period. * Presentation All accepted papers must be presented at the workshop to appear in the proceedings. Authors of accepted papers must notify the program chairs by the camera-ready deadline if they wish to withdraw the paper. At least one author of each accepted paper must register for the workshop. Previous presentations of the work (e.g. preprints on arXiv.org) should be noted in a footnote in the camera-ready version (but not in the anonymized version of the paper). The workshop will take place on May 2 or 6 2023. The workshop will be hybrid with both in-person and virtual presentations. * Organization Committee ** Shabnam Tafreshi, University of Maryland: ARLIS ** Arjun Reddy Akula, Google ** João Sedoc, New York University ** Anna Rogers, University of Copenhagen ** Aleksandr Drozd, RIKEN ** Anna Rumshisky, University of Massachusetts Lowell / Amazon Alexa * Contact info Any questions regarding the workshop can be sent to insights-workshop-organizers(a)googlegroups.com. Please continue reading about: Authorship, Citation and Comparison, Ethics Policy, Reproducibility, Anonymity Period, and Presentation in the call for the paper page on our website: https://insights-workshop.github.io/2023/cfp/ Regards, Insights 2023 Organizers -- *Shabnam Tafreshi, PhD* *Assistant Research Scientist* *Computational Linguistics, NLP* *UMD: ARLIS @ College Park* *"All the problems of the world could be settled easily, if people only willing to think."* *-Thomas J. Watson*

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Fwd: Fully funded PhD studentships in NLP, Queen Mary University of London
by Matthew Purver 06 Jan '23

06 Jan '23

A reminder of the funded PhD studentships in NLP/computational linguistics available at Queen Mary University of London - application deadline 31st January 2023 - see below for details of topics and funding. Please note that our EPSRC and Principal's fund studentships have some restrictions on eligibility, and for these we are particularly seeking applicants with *UK home fee status*. ---------- Forwarded message --------- From: Matthew Purver via Corpora <corpora(a)list.elra.info> Date: Mon, 19 Dec 2022 at 12:44 Subject: [Corpora-List] Fully funded PhD studentships in NLP, Queen Mary University of London To: corpora(a)list.elra.info <corpora(a)list.elra.info> A number of funded PhD studentships in NLP/computational linguistics are available in the Computational Linguistics Lab in the School of Electronic Engineering and Computer Science at Queen Mary University of London, UK, for September 2023 entry. Studentships are available on a range of specified topics with particular supervisors. Funding conditions, length of studentship and eligibility vary with topic - please see the links in the list below for details. - Unsupervised text anonymisation using pre-trained language models: Dr Julia Ive <https://julia-ive.github.io/>, funded via CSC (see here) <http://eecs.qmul.ac.uk/phd/phd-studentships/csc-phd-studentships-in-electro…> . - Understanding word embeddings via their algebraic-topological structures: Dr. Haim Dubossarsky <https://scholar.google.com/citations?user=2EDsENQAAAAJ>, funded via CSC (see here) <http://eecs.qmul.ac.uk/phd/phd-studentships/csc-phd-studentships-in-electro…>. - Prompt-based learning for adaptive context-dependent NLP: Prof. Matthew Purver <http://www.eecs.qmul.ac.uk/~mpurver/>, funded via CSC (see here) <http://eecs.qmul.ac.uk/phd/phd-studentships/csc-phd-studentships-in-electro…> . - Evaluating and Learning with Disagreements: Prof. Massimo Poesio <http://www.massimopoesio.org/>, funded via CSC (see here) <http://eecs.qmul.ac.uk/phd/phd-studentships/csc-phd-studentships-in-electro…>. - Next-generation NLP methods for meaning change: Dr. Haim Dubossarsky <https://scholar.google.com/citations?user=2EDsENQAAAAJ>, funded via QMUL's Principal's fund (see here) <http://eecs.qmul.ac.uk/phd/phd-studentships/principal-and-epsrc-dtp-phd-stu…> . - Meaning coordination in dialogue: Prof. Matthew Purver <http://www.eecs.qmul.ac.uk/~mpurver/>, funded via EPSRC (see here) <http://eecs.qmul.ac.uk/phd/phd-studentships/principal-and-epsrc-dtp-phd-stu…> . More details on the topics and funding conditions are available from this page: http://eecs.qmul.ac.uk/phd/phd-studentships/ If you are interested, please get in touch with the relevant supervisor directly. Final applications are due by 31st January 2023. -- Matthew Purver - http://www.eecs.qmul.ac.uk/~mpurver/ Computational Linguistics Lab - http://compling.eecs.qmul.ac.uk/ Cognitive Science Research Group - http://cogsci.eecs.qmul.ac.uk/ School of Electronic Engineering and Computer Science Queen Mary University of London, London E1 4NS, UK *My working days for QMUL are Tuesday-Thursday; responses to mail on other days may be delayed.*

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PhD position: Conversational Agents in Healthcare | Reykjavik University
by Stefán Ólafsson 06 Jan '23

06 Jan '23

PhD position: Conversational Agents in Healthcare The Department of Computer Science at Reykjavik University is looking for one PhD student to conduct research on conversational agents in healthcare under the supervision of Dr. Stefán Ólafsson. Conversational agents are increasingly becoming ubiquitous and being used in safety-critical domains. This project aims to investigate conversational agents for use in healthcare, research dialog management methods that take advantage of state-of-the-art NLP (e.g., large language models, AI planning, and reinforcement learning), and study aspects of their performance, such as safety, trustworthiness, and information credibility. The ideal candidate should be knowledgeable about AI and language technologies and be passionate about research. The position is at the Center for Analysis and Design of Intelligent Agents (CADIA) and the Language and Voice Lab (LVL) at Reykjavik University in Iceland. The position is for three years. The starting monthly salary is 412,000 ISK (approximately 2,760 €) per month before taxes. The successful candidate will spend 20% of their employment working as a teaching assistant in selected courses. Please visit https://jobs.50skills.com/ru/17159/ for more information. The application deadline is January 31st, 2023.

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Call for Papers: HealthNLP workshop co-located with the 11th International Conference on Healthcare Informatics (ICHI 2023)
by Halil Kilicoglu 05 Jan '23

05 Jan '23

*** Apologies for cross-posting *** Call for Papers --------------- The 6th International Workshop on Health Natural Language Processing (HealthNLP 2023) ICHI 2023 workshop, June 10th, 2023, Houston, Texas, USA https://www.healthnlp.info/ Submission deadline: March 10th, 2023 We cordially invite you to submit your contribution to the 6th International Workshop on Health Natural Language Processing (HealthNLP 2023) that will take place June 10, 2023, in Houston, Texas, United States of America (https://www.healthnlp.info/). In the past few decades, we have seen exponential growth in clinical narratives and biomedical articles. As a result, the natural language process (NLP) specialized in biomedicine, which can unlock information from text, receives great attention in the biomedical and clinical domains. Many NLP methods and systems have been developed and have shown promising results in various information extraction, information retrieval, and knowledge discovery tasks. These methods and tools have also been successfully applied to facilitate biomedicine research and support healthcare applications. At the same time, the availability and use of health information online have exploded through the use of social media, question-answering and community discussion forums, health-related websites, and biomedical articles. These present additional challenges and opportunities for further development of new methodologies and applications. This workshop aims to provide a unique, interdisciplinary, and high-quality platform to bring together researchers and practitioners in healthcare informatics working with health-related free text, and facilitate close interaction among students, scholars, and industry professionals on health NLP challenges. Topics of interest ------------------ - NLP methods: any original methodological research, including but not limited to the following areas: language models and learning architectures (e.g., transformers), deep learning, named entity recognition, word sense disambiguation, relation extraction, syntactic parsing, semantic role labeling, topic modeling, discourse analysis, question answering, and other topics related to health NLP. - NLP software tools: any general or specific NLP tools for health data such as clinical notes, social media, and biomedical literature. - NLP applications: uses of NLP for clinical research or operation, examples including pharmacovigilance, clinical decision support, phenotyping, predictive modeling, risk prediction, and social media mining. Important Dates --------------- - Deadline for all submissions: March 10th, 2023 - Notification of decisions: March 23rd, 2023 - Deadline for camera-ready papers: March 30th, 2023 - Workshop date: June 10th, 2023 Call for Submissions -------------------- Template: https://www.ieee.org/conferences/publishing/templates.html HealthNLP will accept both regular papers (4-8 pages, including references) and abstracts (2 pages, including references). Regular papers will describe mature ideas, where a substantial amount of implementation, experimentation, or data collection and analysis has been completed. Abstracts will describe innovative ideas, where preliminary implementation and validation work have been conducted. Submissions will be handled electronically through EasyChair ( https://easychair.org/my/conference?conf=ieeeichi2023). When submitting papers, the authors must select the "HealthNLP Workshop" track. Papers must adhere to the IEEE Proceedings Format ( https://www.ieee.org/conferences/publishing/templates.html) and be submitted as a single PDF file. Before a submission is sent to the reviewers, the program chairs will perform an assessment to determine the best fit for the submission. HealthNLP uses a single-blind two-layer peer-reviewing process. The final decision will be made by the program chairs based on at least two reviews by program committee members. All accepted submissions will be presented at the workshop and published in the IEEE ICHI 2023 Proceedings (archived in IEEE Xplore Digital Library). Thank you, Yifan Peng, Cornell University Medical College, US Halil Kilicoglu, University of Illinois at Urbana-Champaign, US HealthNLP 2023 Co-Chairs Qingyu Chen HealthNLP 2023 Publication Chair *HALIL KILICOGLU* *Associate Professor* School of Information Sciences University of Illinois at Urbana-Champaign halil(a)illinois.edu https://ischool.illinois.edu/people/halil-kilicoglu

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