** Call for Research Papers **
Scholarly literature is the chief means by which scientists and academics
document and communicate their results and is therefore critical to the
advancement of knowledge and improvement of human well-being. At the same
time, this literature poses challenges to NLP uncommon in other genres,
such as specialized language and high background knowledge requirements,
long documents and strong structural conventions, multimodal presentation,
citation relationships among documents, an emphasis on rational
argumentation, and the frequent availability of detailed metadata. These
challenges necessitate the development of NLP methods and resources
optimized for this domain. The Scholarly Document Processing (SDP) workshop
provides a venue for discussing these challenges, bringing together
stakeholders from different communities including computational
linguistics, machine learning, text mining, information retrieval, digital
libraries, scientometrics and others, to develop methods, tasks, and
resources in support of these goals.
This workshop builds on the success of prior workshops: the 1st, 2nd, and
3rd SDP workshops held at EMNLP 2020, NAACL 2021, and COLING 2022, and the
1st and 2nd SciNLP workshops held at AKBC 2020 and 2021. In addition to
having broad appeal within the NLP community, we hope the SDP workshop will
attract researchers from other relevant fields including meta-science,
scientometrics, data mining, information retrieval, and digital libraries,
bringing together these disparate communities within ACL.
Website: https://sdproc.org/2024/
X (Twitter): https://twitter.com/sdpworkshop
Topics of Interest
We invite submissions from all communities demonstrating usage of and
challenges associated with natural language processing, information
retrieval, and data mining of scholarly and scientific documents. Relevant
topics include (but are not limited to):
-
Large Language Models (LLMs) for Science
-
Representation learning and language modeling
-
Information extraction and NER
-
Document understanding
-
Summarization and generation
-
Question-answering
-
Discourse modeling/argumentation mining
-
Network analysis
-
Bibliometrics, scientometrics, and altmetrics
-
Reproducibility and research integrity, including new challenges posed
by generative AI
-
Peer review tools, principles and technology
-
Metadata and indexing
-
Inclusion of datasets and computational resources
-
Research infrastructures and digital libraries
-
Increasing the representation in scholarly work of disadvantaged
populations
-
LLM-based interfaces to consume/produce scholarly documents
** Submission Information **
Authors are invited to submit full and short papers with unpublished,
original work. Submissions will be subject to a double-blind peer-review
process. Accepted papers will be presented by the authors at the workshop
either as a talk or a poster. All accepted papers will be published in the
workshop proceedings (proceedings from previous years can be found here:
https://aclanthology.org/venues/sdp/).
The submissions must be in PDF format and anonymized for review. All
submissions must be written in English and follow the ACL 2024 formatting
requirements:
Long paper submissions: up to 8 pages of content, plus unlimited references.
Short paper submissions: up to 4 pages of content, plus unlimited
references.
Submission Website: Paper submission has to be done through openreview: <
https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/SDProc>
Final versions of accepted papers will be allowed 1 additional page of
content so that reviewer comments can be taken into account.
** Important Dates (Main Research Track) **
Paper submission deadline: May 17 (Friday), 2024
Notification of acceptance: June 17 (Monday), 2024
Camera-ready paper due: July 1 (Monday), 2024
Workshop dates: August 16, 2024
** SDP 2024 Keynote Speakers **
We are excited to have several keynote speakers at SDP 2024.
1.
Iryna Gurevych, Professor at Technical University Darmstadt and head of
the UKP Lab, Germany.
2.
Anna Rogers, Assistant Professor, University of Copenhagen, Denmark
3.
Heng Ji, Professor, University of Illinois at Urbana-Champaign, USA.
4.
Doug Downey, Associate Professor at Northwestern University and Research
Manager at Allen Institute for AI, USA.
** SDP 2024 Shared Tasks **
SDP 2024 will host two exciting shared tasks. More information about all
shared tasks is provided on the workshop website:
https://sdproc.org/2024/sharedtasks.html
DAGPap24: Detecting automatically generated scientific papers
A big problem with the ubiquity of Generative AI is that it has now become
very easy to generate fake scientific papers. This can erode public trust
in science and attack the foundations of science: are we standing on the
shoulders of robots? The Detecting Automatically Generated Papers (DAGPAP)
competition aims to encourage the development of robust, reliable
AI-generated scientific text detection systems, utilizing a diverse dataset
and varied machine learning models in a number of scientific domains.
Organizers: Savvas Chamezopoulos, Yury Kashnitsky, Drahomira Herrmannova,
Anita de Waard (Elsevier), Domenic Rosati (Scite)
Context24: Contextualizing Scientific Figures and Tables
When making sense of results across many research papers on a topic,
figures or tables of key results from the papers can serve as effective,
information-dense summaries that can be compared/contrasted and synthesized
with other results. However, to understand the results, key elements (e.g.,
measures, sample) need to be contextualized with associated methodological
details, which are typically dispersed throughout the text, often far from
the figure/table and from each other. In this shared task, we are
interested in contextualizing scientific figures and tables, i.e.,
automatically retrieving and ranking snippets from the paper that are most
needed to interpret their results, with the goal of making figures/tables
more self-contained.
Organizers: Joel Chan, Matthew Akamatsu
** Organizing Committee **
Tirthankar Ghosal, Oak Ridge National Laboratory, USA
Philipp Mayr, GESIS – Leibniz Institute for the Social Sciences, Germany
Aakanksha Naik, Allen Institute for AI, USA
Shannon Shen, Massachusetts Institute of Technology, USA
Amanpreet Singh, Allen Institute for AI, USA
Anita de Waard, Elsevier, Netherlands
Orion Weller, Johns Hopkins University, USA
Yanxia Qin, National University of Singapore, Singapore
Yoonjoo Lee, Korea Advanced Institute of Science & Technology, South Korea
--
+++++++++++++++++++++++++++++++++++
*Tirthankar Ghosal*
Scientist
National Center for Computational Sciences (NCCS)
Oak Ridge National Laboratory, United States
++++++++++++++++++++++++++++++++++++
DLnLD: Deep Learning and Linked Data — Last Call for Paper
Workshop colocated with LREC-COLING 2024,
Date: May 21, 2024
Submissions due: 9th March 2024
Venue: Torino, Italy and online
For up to date info, check: https://dl-n-ld.github.io/ <https://dl-n-ld.github.io/>
Call for Papers
----------------------------------------------------------------------------------------
What does Linguistic Linked Data brings to Deep Learning and vice versa ? Let’s bring together these two complementary approaches in NLP.
----------------------------------------------------------------------------------------
Motivations for the Workshop
Since the appearance of transformers (Vaswani et al., 2017), Deep Learning (DL) and neural approaches have brought a huge contribution to Natural Language Processing (NLP) either with highly specialized models for specific application or via Large Language Models (LLMs) (Devlin et al., 2019; Brown et al., 2020; Touvron et al., 2023) that are efficient few-shot learners for many NLP tasks. Such models usually build on huge web-scale data (raw multilingual corpora and annotated specialized, task related, corpora) that are now widely available on the Web. This approach has clearly shown many successes, but still suffers from several weaknesses, such as the cost/impact of training on raw data, biases, hallucinations, explainability, among others (Nah et al., 2023).
The Linguistic Linked Open Data (LLOD) (Chiarcos et al., 2013) community aims at creating/distributing explicitly structured data (modelled as RDF graphs) and interlinking such data across languages. This collection of datasets, gathered inside the LLOD Cloud (Chiarcos et al., 2020), contains a huge amount of multilingual ontological (e.g. DBpedia (Lehmann et al., 2015)); lexical (e.g., DBnary (Sérasset, 2015), Wordnet (McCrae et al., 2014), Wikidata (Vrandečić and Krötzsch, 2014)); or linguistic (e.g., Universal Dependencies Treebank (Nivre et al., 2020; Chiarcos et al., 2021), DBpedia Abstract Corpus (Brümmer et al., 2016)) information, structured using common metadata (e.g., OntoLex (McCrae et al., 2017), NIF (Hellmann et al., 2013), etc.) and standardised data categories (e.g., lexinfo (Cimiano et al., 2011), OliA (Chiarcos and Sukhareva, 2015)).
Both communities bring striking contributions that seem to be highly complementary. However, if knowledge (ontological) graphs are now routinely used in DL, there is still very few research studying the value of Linguistic/Lexical knowledge in the context of DL. We think that, today, there is a real opportunity to bring both communities together to take the best of both worlds. Indeed, with more and more work on Graph Neural Networks (Wu et al., 2023) and Embeddings on RDF graphs (Ristoski et al., 2019), there is more and more opportunity to apply DL techniques to build, interlink or enhance Linguistic Linked Open Datasets, to borrow data from the LLOD Cloud for enhancing Neural Models on NLP tasks, or to take the best of both worlds for specific NLP use cases.
Submission Topics
This workshop aims at gathering researchers that work on the interaction between DL and LLOD in order to discuss what each approach has to bring to the other. For this, we welcome contributions on original work involving some of the following (non exhaustive) topics:
• Deep Learning for Linguistic Linked Data, among which (but not exclusively):
• Modelling, Resources & Interlinking,
• Relation Extraction
• Corpus annotation
• Ontology localization
• Knowledge/Linguistic Graphs creation or expansion
• Linguistic Linked Data for Deep Learning, among which (but not exclusively):
• Linguistic/Knowledge Graphs as training data
• Fine tuning LLMs using Linguistic Linked (meta)Data
• Graph Neural Networks
• Knowledge/Linguistic Graphs embeddings
• LLOD for model explainability/sourcing
• Neural models for under-resourced languages
• Joint Deep Learning and Linguistic Data applications
• Use cases combining Language Models and Structured Linguistic Data
• LLOD and DL for Digital Humanities
• Question-Answering on graph data
All application domains (Digital Humanities, FinTech, Education, Linguistics, Cybersecurity…) as well as approaches (NLG, NLU, Data Extraction…) are welcome, provided that the work is based on the use of BOTH Deep Learning techniques and Linguistic Linked (meta)Data.
Important Dates
All deadlines are 11:59PM UTC-12:00 (“anywhere on Earth”)
• Submissions due: 9th March 2024 (Hard deadline: there will be no deadline extension)
• Notification of acceptance: 2nd April 2024
• Camera-ready due: 12th April 2024
Authors kit
All papers must follow the LREC-COLING 2024 two-column format, using the supplied official style files. The templates can be downloaded from the Style Files and Formatting page provided on the website. 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.
LREC-COLING 2024 Author’s Kit Page: https://lrec-coling-2024.org/authors-kit/ <https://lrec-coling-2024.org/authors-kit/>
Paper submission
Submission is electronic at https://softconf.com/lrec-coling2024/dlnld2024/ <https://softconf.com/lrec-coling2024/dlnld2024/>
Workshop Chairs
• Gilles Sérasset, Université Grenoble Alpes, France
• Hugo Gonçalo Oliveira, University of Coimbra, Portugal
• Giedre Valunaite Oleskeviciene, Mykolas Romeris University, Lithuania
Program Committee
• Mehwish Alam, Télécom Paris, Institut Polytechnique de Paris, France
• Russa Biswas, Hasso Plattner Institute, Potsdam, Germany
• Milana Bolatbek, Al-Farabi Kazakh National University, Kazakhstan
• Michael Cochez, Vrije Universiteit Amsterdam, Netherlands
• Milan Dojchinovski, Czech Technical University in Prague, Czech Republic
• Basil Ell, University of Oslo, Norway
• Robert Fuchs, University of Hamburg, Germany
• Radovan Garabík, L’. Štúr Institute of Linguistics, Slovak Academy of Sciences, Slovakia
• Daniela Gifu, Romanian Academy, Iasi branch & Alexandru Ioan Cuza University of Iasi, Romania
• Katerina Gkirtzou, Athena Research Center, Maroussi, Greece
• Jorge Gracia del Río, University of Zaragoza, Spain
• Dagmar Gromann, University of Vienna, Austria
• Dangis Gudelis, Mykolas Romeris University, Lithuania
• Ilan Kernerman, Lexicala by K Dictionaries, Israel
• Chaya Liebeskind, Jerusalem College of Technology, Israel
• Marco C. Passarotti, Università Cattolica del Sacro Cuore, Milan, Italy
• Heiko Paulheim, University of Mannheim, Germany
• Alexandre Rademaker, IBM Research Brazil and EMAp/FGV, Brazil
• Georg Rehm, DFKI GmbH, Berlin, Germany
• Harald Sack, Karlsruhe Institute of Technology, Karlsruhe, Germany
• Didier Schwab, Université Grenoble Alpes, France
• Ranka Stanković, University of Belgrade, Serbia
• Andon Tchechmedjiev, IMT Mines Alès, France
• Dimitar Trajanov, Ss. Cyril and Methodius University – Skopje, Macedonia
• Ciprian-Octavian Truică, POLITEHNICA Bucharest, Romania
• Nicolas Turenne, Guangdong University of Foreign Studies, China
• Slavko Žitnik, University of Ljubljana, Slovenia
== 12th NLP4CALL, Tórshavn, Faroe Islands==
The workshop series on Natural Language Processing (NLP) for Computer-Assisted Language Learning (NLP4CALL) is a meeting place for researchers working on the integration of Natural Language Processing and Speech Technologies in CALL systems and exploring the theoretical and methodological issues arising in this connection. The latter includes, among others, insights from Second Language Acquisition (SLA) research, on the one hand, and promote development of “Computational SLA” through setting up Second Language research infrastructure(s), on the other.
The intersection of Natural Language Processing (or Language Technology / Computational Linguistics) and Speech Technology with Computer-Assisted Language Learning (CALL) brings “understanding” of language to CALL tools, thus making CALL intelligent. This fact has given the name for this area of research – Intelligent CALL, ICALL. As the definition suggests, apart from having excellent knowledge of Natural Language Processing and/or Speech Technology, ICALL researchers need good insights into second language acquisition theories and practices, as well as knowledge of second language pedagogy and didactics. This workshop invites therefore a wide range of ICALL-relevant research, including studies where NLP-enriched tools are used for testing SLA and pedagogical theories, and vice versa, where SLA theories, pedagogical practices or empirical data are modeled in ICALL tools.
The NLP4CALL workshop series is aimed at bringing together competences from these areas for sharing experiences and brainstorming around the future of the field.
We welcome papers:
- that describe research directly aimed at ICALL;
- that demonstrate actual or discuss the potential use of existing Language and Speech Technologies or resources for language learning;
- that describe the ongoing development of resources and tools with potential usage in ICALL, either directly in interactive applications, or indirectly in materials, application or curriculum development, e.g. learning material generation, assessment of learner texts and responses, individualized learning solutions, provision of feedback;
- that discuss challenges and/or research agenda for ICALL
- that describe empirical studies on language learner data.
This year a special focus is given to work done on error detection/correction and feedback generation.
We encourage paper presentations and software demonstrations describing the above- mentioned themes primarily, but not exclusively, for the Nordic languages.
==Shared task==
NEW for this year is the MultiGED shared task on token-level error detection for L2 Czech, English, German, Italian and Swedish, organized by the Computational SLA working group.
For more information, please see the Shared Task website: https://github.com/spraakbanken/multiged-2023
==Invited speakers==
This year, we have the pleasure to announce two invited talks.
The first talk is given by Marije Michel from the University of Amsterdam.
The second talk is given by Pierre Lison from the Norwegian Computing Center.
==Submission information==
Authors are invited to submit long papers (8-12 pages) alternatively short papers (4-7 pages), page count not including references.
We will be using the NLP4CALL template for the workshop this year. The author kit can be accessed here, alternatively on Overleaf:
<https://spraakbanken.gu.se/sites/default/files/2023/NLP4CALL%20workshop%20t…>
<https://spraakbanken.gu.se/sites/default/files/2023/nlp4call%20template.doc>
<https://www.overleaf.com/latex/templates/nlp4call-workshop-template/qqqzqqy…>
Submissions will be managed through the electronic conference management system EasyChair <https://easychair.org/conferences/?conf=nlp4call2023>. Papers must be submitted digitally through the conference management system, in PDF format. Final camera-ready versions of accepted papers will be given an additional page to address reviewer comments.
Papers should describe original unpublished work or work-in-progress. Papers will be peer reviewed by at least two members of the program committee in a double-blind fashion. All accepted papers will be collected into a proceedings volume to be submitted for publication in the NEALT Proceeding Series (Linköping Electronic Conference Proceedings) and, additionally, double-published through the ACL anthology, following experiences from the previous NLP4CALL editions (<https://www.aclweb.org/anthology/venues/nlp4call/>).
==Important dates==
03 April 2023: paper submission deadline
21 April 2023: notification of acceptance
01 May 2023: camera-ready papers for publication
22 May 2023: workshop date
==Organizers==
David Alfter (1), Elena Volodina (2), Thomas François (3), Arne Jönsson (4), Evelina Rennes (4)
(1) Gothenburg Research Infrastructure for Digital Humanities, Department of Literature, History of Ideas, and Religion, University of Gothenburg, Sweden
(2) Språkbanken, Department of Swedish, Multilingualism, Language Technology, University of Gothenburg, Sweden
(3) CENTAL, Institute for Language and Communication, Université Catholique de Louvain, Belgium
(4) Department of Computer and Information Science, Linköping University, Sweden
==Contact==
For any questions, please contact David Alfter, david.alfter(a)gu.se
For further information, see the workshop website <https://spraakbanken.gu.se/en/research/themes/icall/nlp4call-workshop-serie…>
Follow us on Twitter @NLP4CALL <https://twitter.com/NLP4CALL/>
**
*SECOND CALL FOR PAPERS: EACL 2024 STUDENT RESEARCH WORKSHOP *
*
Student Research Workshop co-located with EACL 2024 in St. Julians, Malta.
Workshop Dates: March 21/22 2024
***Paper Submission Deadline: December 18, 2023 (Direct) and January 17,
2024 (through ARR)***
**
About the Student Research Workshop
**
The EACL 2024 Student Research Workshop (SRW) is a forum to bring
together students investigating various areas of Computational
Linguistics and Natural Language Processing. The workshop provides an
excellent opportunity for participants to present their work and to
receive mentorship and valuable feedback from the international research
community.
The workshop's goal is to aid students at multiple stages of their
education, including undergraduate, MSc/MA, junior and senior PhD
students, in getting familiar with conducting and presenting their
research.
General Invitation for Submission*
We invite papers in two different categories:
*
**
*
Thesis Proposals: This category is appropriate for PhD students who
have decided on a thesis topic and wish to get feedback on their
proposal and broader ideas for their continuing work.
*
Research Papers: Papers in this category can describe completed
work, or work in progress with preliminary results. For these
papers, the first author **MUST BE** a current student (graduate or
undergraduate). Topics of interest for the SRW are the same as for
the main EACL 2024
conference:<https://www.2022.aclweb.org/calls>https://2024.eacl.org/calls/papers/
<https://2024.eacl.org/calls/papers/>
We are opening a unique opportunity for the submission of research
papers that, while not accepted to the EACL main conference, align well
with the themes of this workshop. To be eligible for submission, the
first author must be a current student. Additionally, submissions should
be complemented with the reviews from ARR to provide context and
insights for evaluation. The submission deadline for this will be
January 17, 2024.
Why Submit to EACL SRW?
*
Mentorship program: EACL SRW provides a unique opportunity for
students to receive constructive feedback and advise from more
senior researchers through our on-site mentorship program.
*
Improving your publication record: Publishing a paper as an
undergraduate or as a MSc/MA student is beneficial when applying for
a PhD program. Publishing a paper in an EACL SRW workshop can be
really helpful for improving students’ publication records.
*
Negative results: we encourage the submission of studies with
negative results providing insights on why and in which scenarios a
particular method fails.
All accepted papers and thesis proposals will be presented in the main
conference poster sessions, which will give students an opportunity to
interact with and to present their work to a large and diverse audience,
including top researchers in the field and assigned mentors.**
*Important Dates*
****
*
Direct Workshop paper submission: December 18, 2023
*
Pre-reviewed ARR paper submission: January 17, 2024
*
Notification of acceptance: January 20, 2024
*
Camera-ready deadline: January 30 2024
*
Workshop dates: March 21-22, 2024
All deadlines are 11:59PM UTC-12:00 ("anywhere on Earth").
**
Submission Requirements
**
We accept both archival submissions (which will be included in the
conference proceedings) and non-archival submissions (which will be
presented at the workshop but will not be included in the proceedings).
**
The archival submissions must follow the anonymity period and the
restrictions of the main conference.
Short papersconsist of up to four (4) pages of content, plus unlimited
references. Upon acceptance, they will be given five (5) content pages
in the proceedings.
Long papersconsist of up to eight (8) pages of content, plus unlimited
references. Upon acceptance, they will be given nine (9) content pages
in the proceedings.
Thesis proposalsconsist of up to eight (8) pages of content, plus
unlimited references. The title must begin with “Thesis Proposal:”. Upon
acceptance, they will be given nine (9) content pages in the proceedings.
We strongly recommend the use of the official ARR style templates. The
paper templates are available as an Overleaf template and can also be
downloaded directly (LaTeX and Word) via
https://aclrollingreview.org/cfp <https://aclrollingreview.org/cfp>under
'Paper Submission and Templates'.
All submissions must be in PDF format. Submissions that do not adhere to
the above author guidelines or ACL policies will be rejected without
review.
Submission is electronic, using the OpenReview conference management.
The submission link is available here:
https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/SRW
<https://openreview.net/group?id=eacl.org/EACL/2024/Workshop/SRW>
Grants
We expect to have grants to offset some portion of students' travel,
conference registration, and accommodation expenses. Further details
will be posted on the SRW website.
To contact the organizers of the workshop, please email us at:
eaclsrw(a)gmail.com
Website and Contact Information
For more information, please visit
https://sites.google.com/view/eacl2024srw
<https://sites.google.com/view/eacl2024srw>and follow us on Twitter
@eacl_srw. To contact the organizers of the workshop, please email us at
eaclsrw(a)gmail.com*
Applications are invited for a 4-year salaried PhD position within the
research project “Polyglot Machines: Human-like Learning of Morphologically
Rich Languages”, financed by a NWO-VIDI Talent Grant and coordinated by
Principal Investigator (PI) dr. Arianna Bisazza. This is an
interdisciplinary project at the intersection of Computational
Linguistics/Natural Language Processing (NLP), Computational
Psycholinguistics and Language Acquisition.
Despite the impressive advances made possible by neural networks, current
NLP systems are still far from displaying the learning abilities of humans
in many languages. This project aims to improve language modeling for
low-resource morphologically rich languages, taking inspiration from child
language acquisition insights.
Among other methodologies, an artificial language learning paradigm will be
used to simulate the learning of typologically diverse languages and
evaluate the effect of known properties of child-directed language on the
acquisition of morphology and other language aspects.
Other possible research directions include: the design of better input
segmentation methods; language acquisition inspired curriculum learning;
and leveraging existing language resources (like dictionaries or
morphological analyzers) to boost the learning process in very low-resource
settings.
This PhD position offers a unique opportunity to acquire valuable research
experience in an international environment: You will be part of the
Computational
Linguistics group <https://www.rug.nl/research/clcg/research/cl/?lang=en> (@
GroNLP <https://twitter.com/GroNlp>), which is part of the Centre for
Language and Cognition of the University of Groningen (CLCG).
Main requirement: A Master’s degree in computational linguistics,
artificial intelligence, computer science, information science, or related
area.
Find more details and apply here by 11 March 2024:
https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0…
Starting date: September 2024
For questions about the position: A. Bisazza a.bisazza(a)rug.nl (do not use
email for applications)
--
Arianna Bisazza
Associate Professor
University of Groningen
http://www.cs.rug.nl/~bisazza
Call for Papers: 2024 IEEE ICEBE: The IEEE International Conference on e-Business Engineering
Dates: 11 - 13 October 2024
Venue: Shanghai, China
Conference URL: https://conferences.computer.org/icebe/2024/index.html
The IEEE International Conference on e-Business Engineering (ICEBE) is a prestigious conference, and a flagship event co-sponsored by IEEE Technical Committee on Business Informatics and Systems (TCBIS, formerly known as TC on Electronic Commerce), and the National Engineering Laboratory for E-Commerce Technologies (NELECT). Since 2003, ICEBE has been provided as a high-quality international forum for researchers, engineers and business specialists to exchange the cutting-edge ideas, findings and experiences of e-business.
New IT breakthrough always brings the evolution of e-business in wide spectrum, e.g. innovative business model, new marketing and sales channel, rapid sense-and-response, etc. How to adapt the changing computing paradigm and adopt new IT technologies for keeping competitive is a great challenge for modern enterprises. Based on the essential complexities in e-business, ICEBE 2024 invites an extensive coverage of system, software, service, business, combinations of the aforementioned, etc. to address related issues and promote research opportunities.
All of the accepted and presented papers in the conference will be included in the conference proceedings published by IEEE Computer Society. The proceedings will be submitted for inclusion in the IEEE Xplore Digital Library and will also be submitted to EI and INSPEC for indexing. The best quality papers presented in the conference will be selected and invited for journal special issues by creating an extended version.
We invite submissions of high-quality papers describing fully developed results or on-going foundational and applied work on the various tracks.
Important Date:
Abstract Due: 12 June 2024
Full Paper Due: 15 June 2024
Notification Due: 31 July 2024
Camera-Ready Due: 07 August 2024
Registration Due: 09 August 2024
Conference start: 11 October 2024
Technical Tracks
Agent
Big Data/Machine Learning
Internet of Things(IoTs)
Mobile and Autonomous Computing
Security, Privacy and Blockchain
Service-Oriented and Cloud
Software Engineering
ECommerce Trading Technologies
Diversity, Accessibility and Inclusivity
Steering Committee
Jen-Yao Chung, Inventec Corportation (USA)
Kwei-Jay Lin, Universaity of California, Irvine (USA)
Yinsheng Li, Fudan University (China)
Liangzhao Zeng, Apple Inc. (USA)
Kuo-Ming Chao, University of Roehampton (UK)
Zhiyuan Fang, Sun Yat-sen University (China)
Shang-Pin Ma, National Taiwan Ocean University (Taiwan)
Omar Hussain, University of New South Wales (Australia)
Qingyao Wu, South China University of Technology (China)
Jingzhi Guo, University of Macua (China)
Feng Tian, Xi'An Jiaotong University (China)
Lihong Jiang, Shanghai Jiao Tong University (China)
Nan Jiang, Bournemouth University (UK)
*Call for Papers: 2024 IEEE ICEBE: The IEEE International Conference on
e-Business Engineering*
*Dates*: 11 - 13 October 2024
*Venue*: Shanghai, China
*Conference URL*: https://conferences.computer.org/icebe/2024/index.html
The IEEE International Conference on e-Business Engineering (ICEBE) is a
prestigious conference, and a flagship event co-sponsored by IEEE Technical
Committee on Business Informatics and Systems
<https://tc.computer.org/tcbis/> (TCBIS, formerly known as TC on Electronic
Commerce), and the National Engineering Laboratory for E-Commerce
Technologies (NELECT) <http://www.nelect.cn/>. Since 2003, ICEBE has been
provided as a high-quality international forum for researchers, engineers
and business specialists to exchange the cutting-edge ideas, findings and
experiences of e-business.
New IT breakthrough always brings the evolution of e-business in wide
spectrum, e.g. innovative business model, new marketing and sales channel,
rapid sense-and-response, etc. How to adapt the changing computing paradigm
and adopt new IT technologies for keeping competitive is a great challenge
for modern enterprises. Based on the essential complexities in e-business,
ICEBE 2024 invites an extensive coverage of system, software, service,
business, combinations of the aforementioned, etc. to address related
issues and promote research opportunities.
All of the accepted and presented papers in the conference will be included
in the conference proceedings published by IEEE Computer Society
<https://www.computer.org/>. The proceedings will be submitted for
inclusion in the IEEE Xplore Digital Library and will also be submitted to
EI and INSPEC for indexing. The best quality papers presented in the
conference will be selected and invited for journal special issues by
creating an extended version.
We invite submissions of high-quality papers describing fully developed
results or on-going foundational and applied work on the various tracks.
*Important Date:*
Abstract Due: 12 June 2024
Full Paper Due: 15 June 2024
Notification Due: 31 July 2024
Camera-Ready Due: 07 August 2024
Registration Due: 09 August 2024
Conference start: 11 October 2024
*Technical Tracks*
Agent
Big Data/Machine Learning
Internet of Things(IoTs)
Mobile and Autonomous Computing
Security, Privacy and Blockchain
Service-Oriented and Cloud
Software Engineering
ECommerce Trading Technologies
Diversity, Accessibility and Inclusivity
*Steering Committee*
Jen-Yao Chung, Inventec Corportation (USA)
Kwei-Jay Lin, Universaity of California, Irvine (USA)
Yinsheng Li, Fudan University (China)
Liangzhao Zeng, Apple Inc. (USA)
Kuo-Ming Chao, University of Roehampton (UK)
Zhiyuan Fang, Sun Yat-sen University (China)
Shang-Pin Ma, National Taiwan Ocean University (Taiwan)
Omar Hussain, University of New South Wales (Australia)
Qingyao Wu, South China University of Technology (China)
Jingzhi Guo, University of Macua (China)
Feng Tian, Xi'An Jiaotong University (China)
Lihong Jiang, Shanghai Jiao Tong University (China)
Nan Jiang, Bournemouth University (UK)
(apologies for cross-posting)
Dear colleague,
Once again, we invite you to participate in the 2024 edition of the
CheckThat! Lab at CLEF 2024. This year, we feature six tasks ---two
follow-up and four new--- that correspond to important components within
and around the full fact-checking pipeline in multiple languages:
Task 1 Check-worthiness in tweets. to identify claims that could be
important to verify on social- and mainstream media. Available in Arabic,
English, Dutch and Spanish.
Task 2 Subjectivity in news articles. to spot text that should be processed
with specific strategies; benefiting the fact-checking pipeline. Available
in Arabic, English, German, Italian, and Multilingual.
Task 3 Persuasion Techniques. to identify text spans in which a persuasion
technique is being issued to influence the reader. This task is offered in
four languages: Arabic, Bulgarian, English, Portuguese and Slovene.
Task 4 Detecting hero, villain, and victim from memes. Detecting hero,
villain, and victim from memes:} to predict the role of each entity: hero,
villain, victim, or other in a given meme and a list of entities. Available
in Arabic, English and Code-mixed.
Task 5 Rumor Verification using Evidence from Authorities. to retrieve
evidence from trusted sources (authorities that have “real knowledge'' on
the matter) and determine if the rumor is supported, refuted, or
unverifiable according to the evidence. Available in Arabic and English.
Task 6 Robustness of Credibility Assessment with Adversarial Examples. to
discover small changes that could be applied to the misinformation text,
causing the provided classifiers to make wrong predictions. Available for
news articles, tweets, propaganda techniques and claims (including
regarding COVID-19) in English.
Further information: https://checkthat.gitlab.io/
Datasets: https://gitlab.com/checkthat_lab/clef2024-checkthat-lab
<https://gitlab.com/checkthat_lab/clef2023-checkthat-lab>
Register and participate:
https://clef2024-labs-registration.dei.unipd.it/registrationForm.php
<https://clef2023-labs-registration.dei.unipd.it/registrationForm.php>
Important Dates
---------------------
- 22 April 2024: Lab registration closes
- 2 May 2024: Beginning of the evaluation cycle (test sets release)
- 6 May 2024 (23:59 AOE): End of the evaluation cycle (run submission)
- 31 May 2024: Deadline for the submission of working notes
- 10 June 2024: Submission of Condensed Lab Overviews [LNCS]
- 21 June 2024: Camera Ready Copy of Condensed Lab Overviews [LNCS] due
- 24 June 2024: Notification of acceptance of working notes
- 8 July 2024: Deadline for submission of camera-ready working notes
- 22-26 July 2024: Preview of working notes
- 9-12 September 2024: CLEF 2024 Conference in Grenoble, France
Best regards,
The CLEF-2024 CheckThat! Lab Shared Task Organizers
Third Call for Papers: CALD-pseudo workshop on Computational Approaches to Language Data Pseudonymization @ EACL 2024, March 21 or 22, 2024
Website:
https://mormor-karl.github.io/events/CALD-pseudo/
Submission website: https://softconf.com/eacl2024/CALD-pseudo-2024/
Submission Deadline: Monday, 18 December 2023 (anywhere on earth)
We invite submissions to the first edition of the CALD-pseudo workshop on Computational Approaches to Language Data Pseudonymization, to be held at EACL 2024 on March 21 or 22, 2024.
[Important Dates]
* December 18, 2023: paper submission deadline
* January 17, 2024: resubmission of already pre-reviewed ARR papers
* January 20, 2024: notification of acceptance
* January, 30 2024: camera-ready papers due
* March 21 or 22, 2024: workshop date (the date to be confirmed by the EACL)
[Introduction]
Accessibility of research data is critical for advances in many research fields, but textual data often cannot be shared due to the personal and sensitive information which it contains, e.g names, political opinions, sensitive personal information and medical data. General Data Protection Regulation, GDPR (EU Commission, 2016), suggests pseudonymization as a solution to secure open access to research data but we need to learn more about pseudonymization as an approach before adopting it for manipulation of research data (Volodina et al., 2023). The main challenge is how to effectively pseudonymize data so that individuals cannot be identified, while at the same time keeping the data usable for research in, among others, computational linguistics, linguistics and natural language processing, for which it was collected.
[Topics of Interest]
CALD-pseudo workshop invites a broad community of researchers in all concerned cross-disciplinary fields to jointly discuss challenges within pseudonymization, such as
* automatic approaches to detection and labelling of personal information in unstructured language data, including events and other context-dependent cues revealing a person;
* developing context-sensitive algorithms for replacement of personal information in unstructured data;
* studies into the effects of pseudonymization on unstructured data, e.g. applicability of pseudonymised data for the intended research questions, readability of pseudonymised data or addition of unwelcome biases through pseudonymization;
* effectiveness of pseudonymization as a way of protecting writer identity;
*
reidentification studies; e.g. adversarial learning techniques that attempt to breach the privacy protections of pseudonymized data;
* constructing datasets for automatic pseudonymization, including methodological and ethical aspects of those;
* approaches to the evaluation of automatic pseudonymization both in concealing the private information and preserving the semantics of the non-personal data;
* pseudonymization tools and software: evaluating the available tools and software for pseudonymization in different languages, and their ease of use, scalability, and performance;
* and numerous other open questions.
[Submission Guidelines]
Authors are invited to submit by December 18, 2023 original and unpublished research papers in the following categories:
* Full papers (up to 8 pages) for substantial contributions
* Short papers (up to 4 pages) for ongoing or preliminary work
All submissions must be in PDF format, must follow the EACL 2024 guidelines described in the ARR CfP (https://aclrollingreview.org/cfp), and use the official ACL style templates available here: https://github.com/acl-org/acl-style-files
Direct submission deadline: December 18, 2023 at https://softconf.com/eacl2024/CALD-pseudo-2024/
Deadline for registration of ARR reviewed papers: January 17, 2023. (Further instructions will follow.)
We also invite authors of papers on the topics of the workshop accepted to Findings to reach out to the organizing committee of CALD-pseudo to present them at the workshop.
[Invited speakers]
We are happy to announce that the workshop will host two invited speakers:
*
Anders Søgaard, University of Copenhagen, Denmark
*
Ildikó Pilán, the Norwegian Computing Center, Norway
[Workshop Organizers]
* Elena Volodina, University of Gothenburg, Sweden
* Therese Lindström Tiedemann, University of Helsinki, Finland
* Simon Dobnik, University of Gothenburg, Sweden
* Xuan-Son Vu, Umeå university, Sweden
[Program Committee]
A list of program committee members is available on the workshop website.
[Contact]
For inquiries, please contact mormor.karl(a)svenska.gu.se
ACL link to the call: https://www.aclweb.org/portal/content/computational-approaches-language-dat…
___________________
Elena Volodina, PhD, Docent
https://spraakbanken.gu.se/en/about/staff/elena
Life is like a mirror. Smile at it and it smiles back at you.
Peace Pilgrim
2nd Call for Papers: 17th Workshop on Graph-based Natural Language Processing (TextGraphs 2024)
Venue: ACL 2024
Location: Bangkok, Thailand
Date: August 15, 2024
Papers Due: May 7, 2024
Website: https://sites.google.com/view/textgraphs2024
Workshop Description
For the past seventeen years, the workshops in the TextGraphs series have published and promoted the synergy between the field of Graph Theory (GT) and Natural Language Processing (NLP). The mix between the two started small, with graph-theoretical frameworks providing efficient and elegant solutions for NLP applications. Graph-based solutions initially focused on single-document part-of-speech tagging, word sense disambiguation, and semantic role labeling. They became progressively larger to include ontology learning and information extraction from large text collections. Nowadays, graph-based solutions also target Web-scale applications such as information propagation in social networks, rumor proliferation, e-reputation, multiple entity detection, language dynamics learning, and future events prediction, to name a few.
We plan to encourage the description of novel NLP problems or applications that have emerged in recent years, which can be enhanced with existing and new graph-based methods. We widen the workshop topics beyond the familiar graph domain, encompassing a broader range of less examined structured data domains as well. The seventeenth edition of the TextGraphs workshop aims to extend the focus on exploring rising topics of large language models (LLMs) prompting from the unique perspective of GT. Therefore, our workshop aims to foster stronger, mutually advantageous connections between NLP and structured data, tackling key challenges inherent in each field.
This year's TextGraphs workshop will feature a dedicated session to commemorate the memory of Dragomir R. Radev, one of the founders of the TextGraphs workshop series. This session will honor his significant work and contributions to the field.
TextGraphs-17 invites submissions on (but not limited to) the following topics:
1. Knowledge Graphs Meet LLMs. A proper utilization of graph-based methods for reasoning over a Knowledge Graph (KG) is a prospective way to overcome critical limitations of the existing LLMs which lack interpretability and factual knowledge and are prone to the hallucination problem. Vice versa, the incorporation of LLM knowledge learnt from large textual collections may help many graph-related tasks, such as KG completion and graph representation learning. Thus, we are highly interested in novel research on the joint use of KG and LLM for an improved processing of either the NLP or graph domain (preferably both).
2. Chain Prompting of LLMs. Recent studies show that prompting strategies like Chain-of-Thought and Graph-of-Thought enhance language understanding and generation tasks compared to the traditional few-shot methods. We welcome submissions developing advanced prompting schemes and software for LLMs and other pre-trained machine learning models.
3. Learning from Structured Data. We greet novel efforts to build a bridge between NLP and various structured data formats including relational and non-relational databases, as well as standardized data formats (such as XML, JSON, RDF, etc.)
4. Interpretability of NLP Systems. The question of interpretability poses a fundamental challenge for the practical application of NLP methods. We invite researchers to adopt structured data and employ graph-based methods to shed light on decision-making and logic behind modern LLMs. Any work on applying a KG or any other structured knowledge to explore and evaluate factual awareness, treating the interpretability problem from the GT perspective, or any other topic that utilizes graphs and other structured data to make LLMs more understandable, is met with appreciation.
Important dates
- Papers due: May 7, 2024
- Notification of acceptance: June 15, 2024
- Camera-ready papers due: July 1, 2024
- Conference date: August 15, 2024
Submission
We invite submissions of up to eight (8) pages maximum, plus bibliography for long papers and four (4) pages, plus bibliography, for short papers.
The ACL 2024 templates must be used; these are provided in LaTeX and also Microsoft Word format. Submissions will only be accepted in PDF format.
This year, TextGraph submission is managed through OpenReview. Submit papers by the end of the deadline day (timezone is UTC-12; AoE) via the submission link on our site: https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/TextGraphs-17<https://openreview.net/group?id=aclweb.org/ACL/2024/Workshop/TextGraphs-17#…>
Shared Task
We invite participation in the task of Knowledge Graph Question Answering (KGQA). We will ask the participants to analyze candidate answers with text and graph features. For each query-answer candidate, a graph characterizing paths in Wikidata from entity from the query to the answer entity will be given. Please find the shared task github in this link: https://github.com/uhh-lt/TextGraphs17-shared-task
Contact
Please direct all questions and inquiries to our official e-mail address (textgraphsOC(a)gmail.com<mailto:textgraphsOC@gmail.com>) or contact any of the organizers via their individual emails. Also you can join us on Facebook: https://www.facebook.com/groups/900711756665369.
Organizers
- Dmitry Ustalov, JetBrains
- Arti Ramesh, Binghamton University
- Alexander Panchenko, Skolkovo Institute of Science and Technology
- Yanjun Gao, University of Wisconsin-Madison
- Andrey Sakhovskiy, Skolkovo Institute of Science and Technology
- Elena Tutubalina, Artificial Intelligence Research Institute
- Gerald Penn, University of Toronto
- Marco Valentino, Idiap Research Institute