International Conference ‘New Trends in Translation and Technology’ (NeTTT’2024)
Varna, Bulgaria, 3-6 July 2024 (https://nettt-conference.com/)
Call for ‘Last minute results’ submissions
In view of the special track of the NeTTT'24 event on Future of Translation Technology in the Era of LLMs and Generative AI and the latest dynamic developments with LLMs, we would like to call on researchers and users/companies to submit ‘‘Last minute results” of ongoing studies in the form of short 4-to-page submissions (The conference will not consider and evaluate abstracts only). The idea is to fast-track the reviewing process for these submissions so that the results presented at the event are as up-to-date as possible.
The presentations can be either in oral or poster format.
Submission deadline: 5 June 2024
Notification: 12 June 2024
Submission is done via the Softconf START conference management system at https://softconf.com/n/nettt2024.
We invite the authors to comply with the Springer format, following the templates:
* LaTeX<https://resource-cms.springernature.com/springer-cms/rest/v1/content/192386…>,
* Overleaf<https://nettt-conference.com/wp-content/uploads/2024/03/Overleaf_Springer_C…>,
* Word<https://nettt-conference.com/wp-content/uploads/2024/03/Word_splnproc2311.p…>.
Registration
Conference registration is open on https://nettt-conference.com/fees-registration/
Venue
The conference will take place at Conference Hotel Cherno More<https://www.chernomorebg.com/en/conference-centre.html>, Varna, situated only 200 m away from the fine sandy Black Sea beach.
Further information and contact details
The conference website is https://nettt-conference.com<https://nettt-conference.com/> and will be updated on a regular basis. For further information, please contact us at nettt2024(a)nettt-conference.com<mailto:nettt2024@nettt-conference.com>
*Apologies for cross-posting*
Fifth Workshop on Gender Bias in Natural Language Processing
Bangkok, Thailand, on August 16, 2024
https://genderbiasnlp.talp.cat/
Final Call for Papers and Updated Dates
Gender bias, among other demographic biases (e.g. race, nationality, religion), in machine-learned models is of increasing interest to the scientific community and industry. Models of natural language are highly affected by such biases, which are present in widely used products and can lead to poor user experiences. There is a growing body of research into improved representations of gender in NLP models. Key example approaches are to build and use balanced training and evaluation datasets (e.g. Webster et al., 2018), and to change the learning algorithms themselves (e.g. Bolukbasi et al., 2016). While these approaches show promising results, there is more to do to solve identified and future bias issues. In order to make progress as a field, we need to create widespread awareness of bias and a consensus on how to work against it, for instance by developing standard tasks and metrics. Our workshop provides a forum to achieve this goal.
Topics of interest
We invite submissions of technical work exploring the detection, measurement, and mediation of gender bias in NLP models and applications. Other important topics are the creation of datasets, identifying and assessing relevant biases or focusing on fairness in NLP systems. Finally, the workshop is also open to non-technical work addressing sociological perspectives, and we strongly encourage critical reflections on the sources and implications of bias throughout all types of work.
In addition this year we are organising a Shared Task on Gender Bias Machine Translation evaluation.
Paper Submission Information
Submissions will be accepted as short papers (4-6 pages) and as long papers (8-10 pages), plus additional pages for references, following the ACL 2024 guidelines. Supplementary material can be added, but should not be central to the argument of the paper. Blind submission is required.
Each paper should include a statement which explicitly defines (a) what system behaviors are considered as bias in the work and (b) why those behaviors are harmful, in what ways, and to whom (cf. Blodgett et al. (2020)). More information on this requirement, which was successfully introduced at GeBNLP 2020, can be found on the workshop website. We also encourage authors to engage with definitions of bias and other relevant concepts such as prejudice, harm, discrimination from outside NLP, especially from social sciences and normative ethics, in this statement and in their work in general.
Non-archival option
The authors have the option of submitting research as non-archival, meaning that the paper will not be published in the conference proceedings. We expect these submissions to describe the same quality of work and format as archival submissions.
Updated dates:
May 24, 2024: Workshop Paper Due Date
June 21, 2024: Notification of Acceptance
July 5, 2024: Camera-ready papers due
August 16, 2024: Workshop Dates
Keynote Speakers.
Isabelle Augenstein, University of Copenhagen
Hal Daumé III, University of Maryland and Microsoft Research NYC
Organizers.
Christine Basta, Alexandria University
Marta R. Costa-jussà, FAIR, Meta,
Agnieszka Falénska, University of Stuttgart
Seraphina Goldfarb-Tarrant, Cohere
Debora Nozza, Bocconi University
The Department of Computer Science at the IT University of Copenhagen is
offering a Postdoc position in Natural Language Processing/Computational
Linguistics*,* with a start date of *1 September 2024* or as soon as
possible. The *application deadline is 31* *May** 2024.* Applications for
the position can be submitted via ITU job portal
<https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181…>
.
*Proposed project title: *Efficiency and Robustness in Language Model
Pre-training
*Proposed project description.* Recent generative systems based on
pre-trained language models are remarkably fluent, but this is achieved by
extreme volumes of computation and training data. This means not only high
energy costs, but also training on data that is problematic in various
ways: copyright, harmful social stereotypes, non-representative sampling,
misinformation, junk SEO texts, pornography, and contamination with NLP
datasets used for evaluation.
This project will create an ambitious resource for research on transfer
learning, in which pre-training data is held constant, and evaluation takes
into account how much similar data was observed in training, and in what
ways it was similar. This resource will encourage the development of more
efficient and robust approaches, since it will not be possible to improve
benchmark scores by simply training on more data.
The ideal candidate will have a strong background in Computational
Linguistics/Natural Language Processing and experience developing NLP
resources, as well as core skills in programming in Python and machine
learning.
The position is funded for 1 year, and it is our intention to find
additional funding to extend this postdoc to a 2- or 3-year position.
Besides research, the postdoc will gain experience with organization of an
international workshop and shared task and build up their international
network. For those interested in pursuing an academic career, it is also
possible to:
- gain experience in applying for external funding with professional
support (either for the continuation of the postdoc’s own position, e.g.
Marie Curie postdoctoral fellowship, or by contributing to PI’s grant
proposals);
- supervise Master students solo, and/or assist in supervising a PhD
student;
- undertake a formal teacher training program, including teaching guest
lectures in the relevant data science courses at the ITU computer science
department.
The successful candidate will be a member of the national Pioneer Centre
for Artificial Intelligence <https://aicentre.dk/>, a 5-university Danish
research endeavor, and of the NLPnorth <https://nlpnorth.github.io/>research
group at the IT University’s Computer Science Department. Both the centre
and research group are highly international and well-funded, working on a
broad range of research topics.
The project will be supervised by Associate Professor Anna Rogers
<https://annargrs.github.io/> (arog(a)itu.dk), to whom inquiries about the
project can be directed. The candidates attending LREC/COLING 2024 are
welcome to reach out and set up a meeting during the conference.
--
Best regards,
Anna Rogers
Associate Professor
IT University of Copenhagen
http://annargrs.github.io/
*** Last Call for Papers ***
ACM 4th International Conference on Information Technology for Social Good
(GoodIT''24)
Special Track on Educating for a Sustainable Digital Future
https://blogs.uni-bremen.de/goodit2024/
( *** Submission Deadline: 17 May 2024 ***)
SCOPE
Exploring the development of our digital future requires a comprehensive examination of both
individual and societal consequences. Placing excessive emphasis on individual gains, a
common practice in individualistic societies for many years, has hindered the ability to grasp
the complex dynamics and forward-thinking mindset essential for the sustainability of a
contemporary society.
The evolving landscape of technology and the ongoing digital advancements have paved the
way for creative applications in the field of education, allowing us to adapt to the
ever-changing circumstances. When shaping a new approach for Information Systems and
Information Technology education, it is crucial to emphasize the significance of individuals
as key stakeholders and integral members of the wider community, while also recognizing the
pivotal role of collaboration.
In this track, we are searching for papers employing innovative technology and approaches to
educate the future generation towards world equality, collegiality, inclusion and a more
cooperative learning for a sustainable digital future. Values which are emphasized in the
Sustainable Development Goals (SDGs) which overall aim towards creating a more equitable,
sustainable, and peaceful world.
This track is particularly relevant to IS/IT educators and those creative IT practitioners who
care about developing a sustainable digital future.
TOPICS
Potential topics for papers include (but are not limited to):
• Sustainable and innovative education technologies and practices
• Universal access to quality education
• The new role for IS/IT in society and education and the value of information and knowledge
• The role of cooperative learning for life-long learning and societal developments
• Digital transformation: opportunities and challenges for education, work, and society
• Digital learning environments: Innovations and trends
• Equality, diversity, and inclusion in education, work, and society
• The use of large language models and generative AI in education
• New topics and domains in IT-enhanced education
We hope to attract the interest of IS/IT educators and those creative IT practitioners who care
about developing a sustainable digital future.
SUBMISSION GUIDELINES
Please refer to the instructions on the conference web site:
https://blogs.uni-bremen.de/goodit2024/submission-of-papers/ .
All accepted papers will be included in the ACM Digital Library .
IMPORTANT DATES
• Submission deadline: 17 May 2024 (AoE)
• Notification of acceptance: 8 July 2024
• Camera ready: 19 July 2024
TRACK CHAIRS
• George A. Papadopoulos, University of Cyprus, Cyprus
• Vasso Stylianou, University of Nicosia, Cyprus
CONTACT DETAILS
Vasso Stylianou, stylianou.v(a)unic.ac.cy
Saarland University, Germany, is a campus university with an
international focus and a strong research profile. With
numerous internationally respected research institutes on campus and
dedicated support for collaborative
projects, Saarland University is an ideal environment for innovation and
technology transfer. The German
Research Center for Artificial Intelligence ﴾DFKI﴿ is Germany's leading
application‐driven research institute
with a core technology transfer mission. DFKI is currently the world's
largest research centre for artificial
intelligence operated as a public‐private partnership. DFKI maintains
close collaborative ties with national
and international companies and is firmly rooted in the worldwide
scientific AI landscape.
To further strengthen this excellence in research and teaching, the
Department of Language Science and
Technology ﴾LST﴿ in collaboration with the German Research Center for
Artificial Intelligence ﴾DFKI﴿ is inviting
applications for the following position:
Professorship (W3) in Language Technology
(m/f/x; Reference: W2464)
This position is a permanent public sector appointment ﴾equivalent to a
'full‐tenured professorship'﴿ starting
at the earliest possible opportunity. We are looking for an experienced
researcher in the field of language
technology who has extensive knowledge of natural language processing
and machine learning/AI
methodologies. Experience with dialogue systems and reinforcement
learning, the development of
foundation models and/or trustworthy Artificial Intelligence is also
desirable. In addition to holding a
professorship at the university, the successful candidate will also be
appointed as a scientific director at the
German Research Center for Artificial Intelligence ﴾DFKI﴿ where they
will head a research department. DFKI is
an application‐driven research organization that is largely financed
through external project funding. A
demonstrated ability to attract significant external funding for
research projects at the national and
international level is therefore essential. We also expect candidates to
have experience in interdisciplinary
research and in collaborating with industrial partners. The Department
of Language Science and Technology
is internationally recognized for its collaborative and
interdisciplinary research, and the successful candidate
will be expected to contribute to relevant joint research initiatives.
Language technologies are core elements
of our study programmes at the M.Sc./M.A. and B.Sc./B.A. level and the
person appointed will teach courses
within these programmes.
What we can offer you:
The successful candidate will conduct world‐class research, lead their
own research group at the university
and perform teaching and supervisory duties at the undergraduate,
graduate and doctoral levels. At DFKI,
the person appointed will lead a research department with access to an
extensive worldwide network of
industrial and other research partners, facilitating research and impact
at a scale that is otherwise difficult to
achieve. The position offers excellent working conditions in a lively
and international scientific community.
Saarland University is one of the leading centres for language science
and computational linguistics in
Europe and offers a dynamic and stimulating research environment. The
Department of Language Science
and Technology ﴾LST﴿ employs about 100 research staff across nine
research groups in the fields of
computational linguistics, natural language processing,
psycholinguistics, phonetics and speech science,
speech processing, and corpus linguistics
(https://www.uni‐saarland.de/en/department/lst.html). The
department serves as the focal point of the Collaborative Research
Centre 1102 'Information Density and
Linguistic Encoding' (http://www.sfb1102.uni‐saarland.de) and of the
Research Training Group 'Neuroexplicit
Models of Language, Vision, and Action'
(https://www.neuroexplicit.org/), both of which involve close
collaboration with DFKI. The LST department and the DFKI are both part
of the Saarland Informatics Campus
(SIC: https://saarland‐informatics‐campus.de/en), which brings together
some 800 researchers and over
2000 students from 81 countries. SIC is a collaboration between Saarland
University and world‐class research
institutions on campus, which in addition to DFKI include the Max Planck
Institute for Informatics and the
Max Planck Institute for Software Systems.
Qualifications:
The appointment will be made in accordance with the general provisions
of German public sector
employment law. Candidates must have experience in and an aptitude for
academic teaching. They will have
a PhD or doctorate in an appropriate subject and will have demonstrated
a particular capacity for
independent academic research, typically by having obtained an advanced,
post‐doctoral research degree ﴾
Habilitation﴿ or by having published an equivalent volume of
peer‐reviewed research or by having been
appointed to a junior professorship or similar position. They will have
a proven track record of leading their
own research group and of acquiring external research funding. The
successful candidate will be expected to
actively contribute to departmental research and teaching. The language
of instruction is English ﴾in the
M.Sc. and M.A. programmes﴿ and German ﴾in the B.Sc./B.A. programmes﴿. We
expect the successful
candidate either to have sufficient proficiency to teach in both
languages or to be willing to acquire this
level of proficiency within an appropriate period.
Your Application:
Applications should be submitted online at
www.uni-saarland.de/berufungen. No additional paper copy is
required. The application must contain:
• a letter of application and CV/résumé (including your telephone number
and email
address)
• a complete list of your academic publications
• a complete list of external funding (stating own share if you were not
the sole beneficiary)
• your proposed research concept (2–5 pages)
• your teaching concept (1 page)
• copies of your degree certificates
• complete copies of your five most significant publications
• the names of three academic references (including email addresses), at
least one of whom is not one of
your previous academic supervisors.
• If you hold a university degree from a foreign university, please
provide proof of equivalence from
Germany's Central Office for Foreign Education ﴾ZAB﴿ if available. If
proof of equivalence has not been
requested at the time of application, it must be submitted later upon
request.
Applications must be received no later than May 30, 2024.
Please include the job reference number W2464 when you apply. Selected
candidates will be interviewed. If
you have any questions, please contact: crocker(a)lst.xn--unisaarland-nf3f.de.
At Saarland University, we view internationalization as a process
spanning all aspects of university life. We
therefore expect members of our professorial staff to engage in
activities that promote and foster further
internationalization. Special support will be provided for projects that
maintain collaborative interactions
within existing international cooperative networks, e.g. projects with
partners in the European University
Alliance Transform4Europe (www.transform4europe.eu) or the University of
the Greater Region (www.uni‐
gr.eu)
Saarland University is an equal opportunity employer. In accordance with
its affirmative action policy,
Saarland University is actively seeking to increase the proportion of
women in this field. Qualified women
candidates are therefore strongly encouraged to apply. Preferential
consideration will be given to
applications from disabled candidates of equal eligibility. We welcome
applications regardless of nationality,
ethnic and social origin, religion/belief, age, sexual orientation and
identity.
When you submit a job application to Saarland University you will be
transmitting personal data. Please refer
to our privacy notice
(https://www.uni-saarland.de/verwaltung/datenschutz/) for information on
how we
collect and process personal data in accordance with Art. 13 of the
General Data Protection Regulation
(GDPR). By submitting your application, you confirm that you have taken
note of the information in the
Saarland University privacy notice.
Apologies for cross-postings!
** Please forward to anyone who might be interested **
************************************************************************************
CALL FOR PAPERS
Sixth International Conference on AI in Computational Linguistics
(ACLing2024)
September 21-22, 2024 (Hybrid Conference)
Brochure: http://acling.org/wp-content/uploads/2024/05/ACLing24_CFP.pdf
Publication: Procedia Computer Science by ELSEVIER (
https://www.sciencedirect.com/journal/procedia-computer-science)
Website: https://acling.org/
************************************************************************************
* IMPORTANT DATES
* Paper submission deadline: 31 May 2024 (Extended and Final)
* Notification of Acceptance: 21 June 2024
* Registration: 25 June 2024
* Camera ready version submission: 14 July 2024
* Conference Date: 20 – 21 September 2024
************************************************************************************
INTRODUCTION
With the recent advances in the field of Computational Linguistics (CL)
brought on by rapid developments in neural models, the goal of this
conference is to focus on the application of AI/ML in NLP and CL. The
ACLing 2024 aims to bring together leading academicians, scientists,
researchers and practitioners from all over the world to exchange new ideas
and the latest results in Computational Linguistics and NLP; a field that
has become increasingly important. The scope of the conference encompasses
the theory and practice of all aspects of AI/ML in Computational
Linguistics. The British University in Dubai has been chosen to organize
the ACLing2024 conference because it has a mission for establishing itself
as a provider of world class scholarship, education and research.
TOPICS OF INTEREST
ACLing2024 invites researchers from academia and industry to submit their
papers on recent, unpublished research that addresses theoretical and
practical aspects, algorithms, and architectures of Natural Language
Processing systems. Papers describing the creation of resources, as well as
survey and discussion papers, are also welcomed.
Topics of interest include, but are not limited to:
* Large Language Models and their applications
* Information Retrieval and Question Answering
* Information Extraction
* Linguistic Theories and Resources
* Language Modeling
* Speech and Multimodality
* Machine Learning, Text Categorization, and Text Mining
* Machine Translation
* Multilinguality and Cross-linguality
* NLP Applications
* Segmentation, Tagging, and Parsing
* Semantics
* Sentiment Analysis and Opinion Mining
* Web, Social Media and Computational Social Science
* Natural Language Generation
* Text Categorization and Topic Modeling
* Text Mining
* Language and Vision
* AI applications in Computational linguistics
HOW TO SUBMIT
We encourage submissions that describe original unpublished work not
currently under review for any other conference or journal. Submissions
should be prepared according to the main conference guidelines and format
described at the Submission Web Page: https://acling.org/submission/. All
submissions should be written in English and submitted as PDF. Submissions
will be peer reviewed by the program committee members. Evaluation criteria
will include correctness, originality, technical strength, significance,
quality of presentation, and interest and relevance to the conference
attendees. All the submissions should be submitted via EasyChair:
https://easychair.org/my/conference?conf=acling2024
* Long papers: 8 pages including including figures, tables and references.
* Short papers: 4 pages including including figures, tables and references.
CONFERENCE ORGANIZERS
* Prof. Dr. Khaled Shaalan, The British University of Dubai, UAE
* Prof. Dr. Samhaa R. El-Beltagy, Newgiza University, Egypt
* INDEXING, RANKING, AND IMPACT (web sources):
* Abstracting and indexing:
https://www.sciencedirect.com/journal/procedia-computer-science/about/insig…
* Scopus: https://www.scopus.com/sourceid/19700182801?origin=sbrowse
* CiteScore: https://www.scopus.com/sourceid/19700182801?origin=sbrowse
* SJR (scimago):
https://www.scimagojr.com/journalsearch.php?q=19700182801&tip=sid
* ACLingy by Google Citation:
https://scholar.google.com/citations?user=jkpMuFMAAAAJ&hl=en
* ACLing by DBLP: https://dblp.org/db/conf/acling/index.html
FURTHER INFORMATION & CONTACT DETAILS
* Visit the conference website link https://acling.org/ (will be updated on
a regular basis).
* For further information, please contact us at ACLing2024(a)gmail.com
** Abstract deadline May 13th **
** One week to go **
===============
===============
* We apologize if you receive multiple copies of this CfP *
* For the online version of this Call, visit: https://cikm2024.org/call-for-papers/
===============
CIKM 2024: 33rd ACM International Conference on Information and Knowledge Management
Boise, Idaho, USA
October 21–25, 2024
===============
The Conference on Information and Knowledge Management (CIKM) provides a unique venue for industry and academia to present and discuss state-of-the-art research on artificial intelligence, search and discovery, data mining, and database systems, all at a single conference. CIKM is uniquely situated to highlight technologies and insights that materialize the big data and artificial intelligence vision of the future. CIKM 2024 will take place between October 21-25, 2024 in Boise, Idaho, USA.
--------------------------
Key Dates
--------------------------
* Full Papers abstract: 13 May 2024
* Full Papers: 20 May 2024
* Papers notifications: 16 July 2024
* Camera ready: 8 August 2024
(All deadlines are at 11:59 pm AOE)
--------------------------
Topics of Interest
--------------------------
We encourage submissions of high-quality research papers on the general areas of artificial intelligence, data science, databases, information retrieval, and knowledge management. Topics of interest include, but are not limited to, the following areas:
* Data and information acquisition and preprocessing (e.g., data crawling, IoT data, data quality, data privacy, mitigating biases, data wrangling)
* Integration and aggregation (e.g., semantic processing, data provenance, data linkage, data fusion, knowledge graphs, data warehousing, data lake, privacy and security, modeling, information credibility)
* Efficient data processing (e.g., serverless, data-intensive computing, database systems, indexing and compression, architectures, distributed data systems, dataspaces, customized hardware)
* Special data processing (e.g., multilingual text, sequential, stream, time series, spatio-temporal, (knowledge) graph, multimedia, scientific, and social media data)
* Analytics and machine learning (e.g., OLAP, data mining, machine learning and AI, scalable analysis algorithms, algorithmic biases, event detection, and tracking, understanding, and interpretability)
* Neural Information and knowledge processing (e.g., graph neural networks, domain adaptation, transfer learning, network architectures, neural ranking, neural recommendation, and neural prediction)
* Data preparation, Valuation, and Trading
* Information access and retrieval (e.g., web search, question answering and dialogue systems, retrieval models, query processing, personalization, recommender, and filtering systems)
* Users and interfaces for information systems (e.g., user behavior analysis, user interface design, perception of biases, personalization, interactive information retrieval, interactive analysis, spoken interfaces)
* Evaluation, performance studies, and benchmarks (e.g., online and offline evaluation, best practices)
* Crowdsourcing (e.g. task assignment, worker reliability, optimization, trustworthiness, transparency, best practices)
* Mining multi-modal content (e.g., natural language processing, speech recognition, computer vision, content understanding, knowledge extraction, knowledge graphs, and knowledge representations)
* Data presentation (e.g., visualization, summarization, readability, VR, speech input/output)
* Applications (e.g., urban systems, biomedical and health informatics, legal informatics, crisis informatics, computational social science, data-enabled discovery, social media)
* Knowledge graphs support data representation and manipulation
* Generation of knowledge graphs using unstructured data
* Information retrieval in the era of LLMs
* Open-ended QA systems
* Fairness, Accountability, Transparency, Ethics, and Explainability in Information and Knowledge Management
--------------------------
Paper Submissions
--------------------------
Authors are invited to submit original, full-length research papers that are not previously published, accepted to be published, or being considered for publication in any other forum. Full-length papers should satisfy the standard requirements of top-tier international research conferences.
Manuscripts should be submitted to CIKM 2024 Easychair site in PDF format, using the 2-column ACM sigconf template, see https://www.acm.org/publications/proceedings-template . Full papers cannot exceed 9 pages, including an appendix, plus unlimited references. Rejected full papers will not be considered for publication as short papers. The review of manuscripts will be double-blind, and submissions not properly anonymized will be desk-rejected without review.
Papers that include text generated from a large-scale language model (LLM), such as ChatGPT, are prohibited unless this produced text is presented as a part of the paper’s experimental analysis. AI tools may be used to edit and polish authors’ work, such as using LLMs for light editing of their text (e.g., automate grammar checks, word autocorrect, and other editing of author-written text), but text “produced entirely” by generative/AI models is not allowed.
At least one author of each accepted paper must register to present the work on-site in Boise, Idaho, USA, as scheduled in the conference program.
The official publication date is when the proceedings are made available in the ACM Digital Library. This date may be up to two weeks before the first day of the conference. The official publication date affects the deadline for any patent filings related to published work.
--------------------------
Dual Submission Policy
--------------------------
Submitting papers that are identical (or substantially similar) to versions that have been published, accepted for publication, or submitted in parallel to other conferences (or any venue with published proceedings) is not allowed. However, it is allowed to make an abstract submission by May 13, 2024 (without uploading the paper PDF) for a paper that is still under review as long as the ongoing review process ends by the full paper final deadline of May 20, 2024. You need to withdraw your submission in case the paper is accepted or still under review by May 20, 2024.
Authors are allowed to submit papers that have been presented or are to be presented at conferences or workshops without proceedings, or with only abstracts published. Authors may also submit anonymized work already available as a preprint (e.g., in arXiv). In this case, the authors must modify the title and abstract while refraining from citing the manuscript to preserve anonymity.
--------------------------
Authorship Policy
--------------------------
Before paper submission, authors are advised to review ACM’s authorship policy carefully. Please ensure that all authors are identified in EasyChair before the submission deadline. To help reviewers identify potential conflicts of interest, the full author list must be specified by the abstract submission deadline. Consequently, no changes to authorship will be allowed under any circumstance after the abstract submission deadline; neither update will be permitted for camera-ready versions.
--------------------------
Desk Rejection Policy
--------------------------
Submissions that fail to adhere to the anonymity, length, or formatting requirements, or violate ACM’s policies on academic dishonesty—such as plagiarism, author misrepresentation, or falsification—may be subject to desk rejection by the chairs.
--------------------------
ACM Policy Against Harassment
--------------------------
All authors and participants must adhere to the ACM Policy Against Harassment. For full details, please visit this site: https://www.acm.org/about-acm/policy-against-harassment
--------------------------
Chairs Contact Information
--------------------------
For more information, contact the PC chairs at: CIKM2024-pc [at] easychair [dot] org
Carlotta Domeniconi, George Mason University, USA
Zhifeng Bao, RMIT University, Australia
Sole Pera, TU Delft, Netherlands
** Abstract deadline May 13th **
** One week to go **
===============
===============
* We apologize if you receive multiple copies of this CfP *
* For the online version of this Call, visit: https://cikm2024.org/call-for-applied-research-papers
===============
CIKM 2024: 33rd ACM International Conference on Information and Knowledge Management
Boise, Idaho, USA
October 21–25, 2024
===============
The 33rd ACM International Conference on Information and Knowledge Management (CIKM) offers a forum for academia and industry to present cutting-edge research on artificial intelligence, search and discovery, text and data mining, and database systems.
The Applied Research Track invites submissions from both academia and industry that focus on advancing the understanding of issues related to deploying IR, NLP and AI at scale. Unlike the Research Track, the Applied Research Track concentrates on applied work, such as describing the implementation of a system, data acquisition, or application of a methodology that addresses a significant real-world problem and demonstrates measurable benefits and impact. We invite authors to submit papers that showcase their research work’s real-world impact and demonstrate practicality and scalability.
Submissions should clearly outline how the work has been deployed or released and for how long, or how the work is planned to be deployed or released and what is its potential impact in the real world
--------------------------
Key Dates
--------------------------
* Applied Research Papers abstract: 13 May 2024
* Applied Research Papers: 20 May 2024
* Applied Research Papers notifications: 16 July 2024
* Camera ready: 8 August 2024
(All deadlines are at 11:59 pm AOE)
--------------------------
Topics of Interest
--------------------------
We invite submissions along the same topics of interest lines as the CIKM 2024 Research Track, but with a focus on applied and deployed work, substantiated by a system launch, data release, or other practical application evidence.
* Data and information acquisition and preprocessing (e.g., data crawling, IoT data, data quality, data privacy, mitigating biases, data wrangling)
* Integration and aggregation (e.g., semantic processing, data provenance, data linkage, data fusion, knowledge graphs, data warehousing, privacy and security, modeling, information credibility)
* Efficient data processing (e.g., serverless, data-intensive computing, database systems, indexing and compression, architectures, distributed data systems, dataspaces, customized hardware)
* Special data processing (e.g., multilingual text, sequential, stream, spatio-temporal, (knowledge) graph, multimedia, scientific, and social media data)
* Analytics and machine learning (e.g., OLAP, data mining, machine learning and AI, scalable analysis algorithms, algorithmic biases, event detection and tracking, understanding, interpretability)
* Neural Information and knowledge processing (e.g., graph neural networks, domain adaptation, transfer learning, network architectures, neural ranking, neural recommendation, and neural prediction)
* Data processing enabled by large language models and other foundation models (e.g. information retrieval or data management facilitated by the use of LLMs)
* Information access and retrieval (e.g., ad hoc and web search, facets and entities, question answering and dialogue systems, retrieval models, query processing, personalization, recommender and filtering systems)
* Users and interfaces for information and data systems (e.g., user behavior analysis, user interface design, perception of biases, personalization, interactive information retrieval, interactive analysis, spoken interfaces)
* Evaluation, performance studies, and benchmarks (e.g., online and offline evaluation, best practices)
Crowdsourcing (e.g. task assignment, worker reliability, optimization, trustworthiness, transparency, best practices)
* Understanding multi-modal content (e.g., natural language processing, speech recognition, computer vision, content understanding, knowledge extraction, knowledge graphs, and knowledge representations)
* Data presentation (e.g., visualization, summarization, readability, VR, speech input/output)
* Network and graph mining (e.g., social network analysis, mining important nodes in networks, subgraphs and graph motifs mining, community detection)
* Applications (e.g., urban systems, biomedical and health informatics, legal informatics, crisis informatics, computational social science, data-enabled discovery, social media)
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Paper Submissions
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We welcome original applied research submissions that are not previously published, accepted to be published, or being considered for publication in any other forum. Full-length papers should satisfy the standard requirements of top-tier international research conferences.
Authors should include their names and affiliations in the manuscript (i.e. submissions are single-blind).
Submissions are limited to 7 pages plus unlimited references (note that additional appendices are not allowed) and must be formatted using ACM’s 2-column template “sig-conf”, see https://www.acm.org/publications/proceedings-template.
Papers that include text generated from a large-scale language model (LLM), such as ChatGPT, are prohibited unless this produced text is presented as a part of the paper’s experimental analysis. AI tools may be used to edit and polish authors’ work, such as using LLMs for light editing of their text (e.g., automate grammar checks, word autocorrect, and other editing of author-written text), but text “produced entirely” by generative/AI models is not allowed.
At least one author of each accepted paper must register to present the work on-site in Boise, Idaho, USA, as scheduled in the conference program.
The official publication date is when the proceedings are made available in the ACM Digital Library. This date may be up to two weeks before the first day of the conference. The official publication date affects the deadline for any patent filings related to published work.
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Dual Submission Policy
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Submitting papers that are identical (or substantially similar) to versions that have been published, accepted for publication, or submitted in parallel to other conferences (or any venue with published proceedings) is not allowed. However, it is allowed to make an abstract submission by May 13, 2024 (without uploading the paper PDF) for a paper that is still under review as long as the ongoing review process ends by the full paper final deadline of May 20, 2024. You need to withdraw your submission in case the paper is accepted or still under review by May 20, 2024.
Authors are allowed to submit papers that have been presented or are to be presented at conferences or workshops without proceedings, or with only abstracts published. Authors may also submit anonymized work already available as a preprint (e.g., in arXiv). In this case, the authors must modify the title and abstract while refraining from citing the manuscript to preserve anonymity.
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Authorship Policy
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Before paper submission, authors are advised to review ACM’s authorship policy carefully. Please ensure that all authors are identified in EasyChair before the submission deadline. To help reviewers identify potential conflicts of interest, the full author list must be specified by the abstract submission deadline. Consequently, no changes to authorship will be allowed under any circumstance after the abstract submission deadline; neither update will be permitted for camera-ready versions.
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Desk Rejection Policy
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Submissions that fail to adhere to the anonymity, length, or formatting requirements, or violate ACM’s policies on academic dishonesty—such as plagiarism, author misrepresentation, or falsification—may be subject to desk rejection by the chairs.
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ACM Policy Against Harassment
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All authors and participants must adhere to the ACM Policy Against Harassment. For full details, please visit this site: https://www.acm.org/about-acm/policy-against-harassment
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Chairs Contact Information
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For more information, contact the Applied Research Track PC chairs at: CIKM2024-applied [at] easychair [dot] org
Wei Chen (Microsoft Research Asia)
Yinglong Xia (Meta)
*GenBench: The second workshop on generalisation (benchmarking) in NLP*
*Workshop description*The ability to generalise well is often mentioned as
one of the primary desiderata for models of natural language processing
(NLP).
Yet, there are still many open questions related to what it means for an
NLP model to generalise well, and how generalisation should be evaluated.
LLMs, trained on gigantic training corpora that are – at best – hard to
analyse or not publicly available at all, bring a new set of challenges to
the topic.
The second GenBench workshop aims to serve as a cornerstone to catalyse
research on generalisation in the NLP community.
The workshop aims to bring together different expert communities to discuss
challenging questions relating to generalisation in NLP, crowd-source
challenging generalisation benchmarks for LLMs, and make progress on open
questions related to generalisation.
Topics of interest include, but are not limited to:
- Opinion or position papers about generalisation and how it should be
evaluated;
- Analyses of how existing or new models generalise;
- Empirical studies that propose new paradigms to evaluate
generalisation;
- Meta-analyses that compare how results from different generalisation
studies compare;
- Meta-analyses that study how different types of generalisation are
related;
- Papers that discuss how generalisation of LLMs can be evaluated;
- Papers that discuss why generalisation is (not) important in the era
of LLMs;
- Studies on the relationship between generalisation and fairness or
robustness.
The second GenBench workshop on generalisation (benchmarking) in NLP will
be co-located with EMNLP 2024.
*Submission types*
We call for two types of submissions: regular workshop submissions and
collaborative benchmarking task submissions.
The latter will consist of a data/task artefact and a companion paper
motivating and evaluating the submission.
In both cases, we accept archival papers and extended abstracts.
*1. Regular workshop submissions*
Regular workshop submissions present papers on the topic of generalisation
(see examples listed above).
Regular workshop papers may be submitted as an archival paper, when they
report on completed, original and unpublished research, or as a shorter
extended abstract, otherwise.
More details on this category can be found below.
If you are unsure whether a specific topic is well-suited for submission,
feel free to reach out to the organisers of the workshop at
genbench(a)googlegroups.com.
*2. Collaborative Benchmarking Task (CBT) submissions*
The goal of this year's CBT is to generate versions of existing evaluation
datasets for LLMs which, given a particular training corpus, have a larger
distribution shift than the original test set, or – in other words –
evaluate generalisation to a stronger degree than the original dataset.
For this particular challenge, we focus on three training corpora: C4,
RedPajama-Data-1T, and Dolma.
All three corpora are publicly available, and they can be searched via the
What's in My Big Data API (https://github.com/allenai/wimbd).
We will focus on three popular evaluation datasets: MMLU, HumanEval, and
SiQA.
Submitters to the CBT are asked to design a way to assess distribution
shift for one or more of these evaluation datasets, given particular
features of the training corpus, and then generate one or more versions of
the dataset that have a larger distribution shift according to this method.
Newly generated sets do not have to have the same size as the original test
set, but should have at least 200 examples.
Practically speaking, CBT submissions consist of:
1. the data/task artefact, submitted through
https://github.com/GenBench/genbench_cbt
2. a paper describing the dataset and its method of construction,
submitted through
https://openreview.net/group?id=GenBench.org/2024/Workshop
We accept submissions that consider only one pretraining dataset and
evaluation dataset, but encourage submitters to apply their suggested
protocols to both pretraining datasets.
We also suggest that submitters include model results for models trained on
these datasets.
Suggestions are provided on the CBT website: https://genbench.org/cbt.
Given enough high-quality submissions, we aim to write a paper with the
combined results, to which submitters can be co-authors, if they wish so.
More detailed guidelines will be given on https://genbench.org/cbt.
*Archival vs extended abstract*
Archival papers are up to 8 pages excluding references and report on
completed, original and unpublished research.
They follow the requirements of regular EMNLP 2024 submissions.
Accepted papers will be published in the workshop proceedings and are
expected to be presented at the workshop.
The papers will undergo double-blind peer review and should thus be
anonymised.
Extended abstracts can be up to 2 pages excluding references, and may
report on work in progress or be cross-submissions of work that has already
appeared in another venue.
Abstract titles will be posted on the workshop website, but will not be
included in the proceedings.
*Submission instructions*For both archival papers and extended abstracts,
we refer to the EMNLP 2024 website for paper templates and requirements.
Additional requirements for both regular workshop papers and collaborative
benchmarking task submissions can be found on our website.
All submissions can be submitted through OpenReview:
https://openreview.net/group?id=GenBench.org/2024/Workshop.
*Important dates*
These deadlines are tentative, for the latest version see
https://genbench.org/workshop
- August 15, 2024: Paper submission deadline
- September 20, 2024: Notification deadline
- October 4, 2024: Camera-ready deadline
- November 15 or 16, 2024: Workshop
Note: all deadlines are 11:59 PM UTC-12:00
*Preprints*
We do not have an anonymity deadline, preprints are allowed, both before
the submission deadline as well as after.
*Contact*
Email address: genbench(a)googlegroups.com
Website: https://genbench.org/workshop
*On behalf of the organisers*Dieuwke Hupkes
Verna Dankers
Khuyagbaatar Batsuren
Amirhossein Kazemnejad
Christos Christodoulopoulos
Mario Giulianelli
Ryan Cotterell