(apologies for cross posting)
*** Second Call for Participation for GUA-SPA at IberLEF 2023 ***
GUA-SPA - Guarani-Spanish Code Switching Analysis at IberLEF 2023
News: The training dataset has just been released, and you can send submissions to the development phase!
https://codalab.lisn.upsaclay.fr/competitions/11030
Guarani is a South American indigenous language that has been in contact with Spanish and other Indo-European languages for about 500 years, which has resulted in many interesting varieties with different levels of mixture. In Paraguay, according to the most recent census, most of the population of the country speak at least some Guarani, and there is a high prevalence of Guarani-Spanish bilingualism. Bilingual speakers often make use of the two languages at the same time, mixing them in different ways, in a phenomenon called code-switching. We propose a challenge for analyzing code-switched texts in Guarani and Spanish, trying to identify the language used in each span of text, the named entities mentioned in the text, and the way Spanish is used. For this, we will provide a corpus of news and tweets where each token is labeled with an appropriate language or category identifier.
Three tasks are presented:
* Language identification in code-switched data: identify each token in the text as Guarani, Spanish, mix, named entity, or other categories.
* Named entity classification: classify the named entities found in the text as locations, organizations or people.
* Spanish code classification: classify the spans in Spanish as code changes or unadapted loans.
How to participate:
If you want to participate in this task, please join our Codalab competition: https://codalab.lisn.upsaclay.fr/competitions/11030
Important Dates:
* March 22nd, 2023: training and development set. Development phase begins.
* May 24th, 2023: test set and open for submissions. Evaluation phase begins.
* June 7th, 2023: evaluation phase ends. Publication of results.
* June 14th, 2023: paper submission.
* June 28th, 2023: notification of acceptance.
* July 3rd, 2023: camera-ready paper submission.
* September 26th, 2023: IberLEF 2023 Workshop.
Apologies for cross-posting.
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We kindly invite you to participate at the Pan-2023 Task 2 - “Profiling Cryptocurrency Influencers with Few-Shot Learning”.
This task is being held as part of CLEF 2023, and all participating teams will be able to publish their system description paper at the CLEF proceedings.
This shared task focuses on the author profiling of cryptocurrency influencers in social media from a low-resource perspective, that is, with little training data. Moreover, we propose to profile types of influencers also using a low-resource setting.
Specifically, we focus on English Twitter posts for three different sub-tasks:
• Low-resource influencer profiling (subtask-1): profile authors according to their degree of influence (null, nano, micro, macro, mega).
• Low-resource influencer interest profiling (subtask-2): profile authors according to their main interests or areas of influence (technical information, price update, trading matters, gaming, other).
• Low-resource influencer intent profiling (subtask-3): profile authors according to the intent of their messages (subjective opinion, financial information, advertising, announcement).
Important Links
• Task Website - https://pan.webis.de/clef23/pan23-web/author-profiling.html
• Dataset site - https://zenodo.org/record/7701748#.ZBxxrnbMKiM
Important Dates
• February 20, 2023: Training data ready
• May 10, 2023: Early bird software submission phase (optional)
• May 29, 2023: Software submission deadline
• June 05, 2023: Participant paper submission
• September 18-21, 2023: Conference
Task organizers
• Francisco Rangel (Symanto)
• Mara Chinea-Rios (Symanto) - Contact Email: mara.chinea(a)symanto.com
• Marc Franco-Salvador (Symanto)
• Paolo Rosso (Universidad Politécnica de Valencia)
Please reach out to the organizers at crypto-influencers-pan-organizers(a)googlegroups.com, or join the Slack workspace (https://pan2023profil-0q48349.slack.com) to connect with the other participants and organizers.
The University of Manchester is hiring a Lecturer (UK equivalent to Assistant Professor) in Computational Linguistics, to be based in the Department of Linguistics and English Language. It is a permanent post. Applications are welcome from people working in all areas of Natural Language Processing.
More information on the position and how to apply can be found here:
https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=24945
The closing date for applications is April 24th 2023.
Best,
Colin
This full-day "Communication in Human-AI Interaction" (CHAI) workshop
welcomes submissions of position papers (8 pages maximum in Springer LNCS
format).
The workshop will be held as part of the *INTERACT 23 conference* (Aug 28 -
Sep 1, York, UK and online, https://interact2023.org/).
It will be organized as an interactive work group event, including a design
activity and group discussions.
Important dates and links
* Paper deadline: April 28, 2023 AoE
* Notification: May 19, 2023
* Workshop date: between August 28 and September 1, 2023 (TBD)
* Workshop website:https://chai-workshop.github.io/
* Submission website:https://easychair.org/conferences/?conf=chai23
*Goal and topics:*
Human interactions with AI systems are becoming part of our everyday life.
If designed and developed efficiently, these interactions have great
potential to enhance human work, abilities, and well-being. Communication,
here is the iterative process of establishing shared meaning, is a crucial
aspect of successful interaction and has been studied for years, from HCI,
AI, and cognitive sciences points of view, among others. The goal of this
workshop is to bring together experts from HCI, AI, and Cognitive Sciences
to explore and understand the specificities and characteristics of
communication in human-AI interactions, as well as the salient principles,
methods, and theories one has to consider to build meaningful human-AI
communication systems.
Topics of interest include but are not limited to:
* Blended social contexts, comprising both human and technological
communication
* Communication in multi-user interaction with intelligent agents
* Verbal and non-verbal human-AI communication
* Explicit and implicit human-AI communication
* Rules of etiquette and social norms in human-AI communication
* Communication in human-AI collaboration
* Human-AI communication design
* Language and communication
* Theory of Mind
* Common ground
* Inclusion and Diversity in Human-AI Communication
* Embodied multi-modal communication between humans and physical robots
*Format:*
The workshop will be a one-day event, envisioned as a collaborative
thinking group activity focusing on the challenges surrounding
Communication in Human-AI Interaction. The workshop aims at being
interactive and will consist of two main parts.
First, participants will be invited to collaborate on a design activity.
For this activity, participants will be grouped as best as possible by
topics and each group will be given the same challenge: analyzing and
suggesting a solution to an HAI communication problem. At the end of the
activity, each group will report on their solution.
Second, we will have group discussions in two phases, for which groups will
be shuffled to be cross-disciplinary. Each group will be given a separate
topic. The goal of each group will be to identify common interests, open
questions, and challenges related to this topic. The groups are shuffled
between phases, and participants are encouraged to build on top of the
previous groups’ discussion. Each discussion phase will be followed by a
quick report of each group. The day will end by a longer plenary discussion
during which we will also outline the after-workshop steps.
The design activity problem and the discussion topics will be chosen
following participants submissions so that they align with the expertise
and interest of the workshop participants.
By the end of the workshop, we expect to be as close as possible to a
common agreement about an outline for the coordinated research agenda,
including key points to explore further.
Post-workshop, the results will be communicated to a larger audience
through various activities, to be synchronized with the participants.
*Submission Requirements:*
We welcome interested participants to submit position papers stating
existing work, conceptual design, or their position with respect to the
workshop topics. The submission should also include one or two points of
discussion that the participant would like to address during the workshop.
Submissions should be made through EasyChair (
https://easychair.org/conferences/?conf=chai23) and be formatted according
to the Springer LNCS format, templates available for LaTeX and Word,
maximum 8 pages. We strongly encourage authors of position papers to follow
the SIGCHI accessibility guidelines.
Workshop organizers
Jennifer Renoux, Örebro University, Sweden
Jasmin Grosinger, Örebro University, Sweden
Marta Romeo, Heriot-Watt University, UK
Victor Kaptelinin, Umeå University, Sweden
Antti Oulasvirta, Aalto University, Finland
Contact information
Workshop website:https://chai-workshop.github.io/
For inquiries about the workshop, please contact:
jennifer.renoux(a)oru.se
[Apologies for multiple postings]
ImageCLEFmedicalGANs (1st edition)
Registration: https://www.imageclef.org/2023/medical/gans
Run submission: May 10, 2023
Working notes submission: June 5, 2023
CLEF 2023 conference: September 18-21, Thessaloniki, Greece
*** CALL FOR PARTICIPATION ***
The task is focused on examining the existing hypothesis that GANs are
generating medical images that contain the "fingerprints" of the real
images used for generative network training. If the hypothesis is
correct, artificial biomedical images may be subject to the same
sharing and usage limitations as real sensitive medical data. On the
other hand, if the hypothesis is wrong, GANs may be potentially used
to create rich datasets of biomedical images that are free of ethical
and privacy regulations. The participants will test the hypothesis by
solving one or several tasks related to the detection of relations
between real and artificial biomedical image datasets.
*** TASK ***
Given a set of real-world medical images comprising 2D axial CT image
slices of the heart (including the middle sections and adjacent
slices) of patients afflicted with lung #tuberculosis, the task
challenges participants to develop #machinelearning solutions to
automatically determine which real images were used in training the
generator of realistic synthetic examples.
*** DATA SET ***
The image datasets comprise 2D axial CT image slices of the heart,
including the middle sections of the heart and adjacent slices. These
images are obtained from patients afflicted with Lung Tuberculosis and
are stored in the form of 8 bit/pixel PNG images with dimensions of
256x256 pixels. The development dataset comprises three distinct sets
of images. One set contains images that were generated using a GAN,
while the other two sets are comprised of real images. The first of
these real image sets contains images that were used during the
algorithm's training process. The second set consists of real images
that were not used during the training process. Test dataset is a
collection of two image sets. The first set contains 10,000 images
that have been generated, while the second set is made up of a
combination of 200 real images that were either used or unused during
the training process.
*** IMPORTANT DATES ***
- Run submission: May 10, 2023
- Working notes submission: June 5, 2023
- CLEF 2023 conference: September 18-21, Thessaloniki, Greece
(https://clef2023.clef-initiative.eu/)
*** OVERALL COORDINATION ***
Serge Kozlovski, Belarusian Academy of Sciences, Belarus
Vassili Kovalev, Belarusian Academy of Sciences, Belarus
Ihar Filipovich, Belarus State University, Belarus
Alexandra Andrei, Politehnica University of Bucharest, Romania
Ioan Coman, Politehnica University of Bucharest, Romania
Bogdan Ionescu, Politehnica University of Bucharest, Romania
Henning Müller, University of Applied Sciences Western Switzerland, Switzerland
*** ACKNOWLEDGEMENT ***
Alexandra Andrei, Ioan Coman, Bogdan Ionescu, and Henning Müller
contribution is supported under the H2020 AI4Media "A European
Excellence Centre for Media, Society and Democracy" project, contract
#951911 https://www.ai4media.eu/.
On behalf of the Organizers,
Bogdan Ionescu
https://www.AIMultimediaLab.ro/
3 July 2023 (online, via Zoom)
Organisers: Catherine Travis & Li Nguyen (ANU; Language Data Commons of Australia (LDaCA))
Over decades of work in Australia, significant collections of language data have been amassed, including of varieties of Australian English, Australian migrant languages, Australian Indigenous languages, sign languages and others. These collections represent a trove of knowledge not only of language in Australia, but also of Australia’s social and cultural history. And yet, not all are well known and many lack published descriptions. The purpose of this workshop is to provide an opportunity to share information about existing language corpora in Australia, with a view to producing a special issue of the Australian Journal of Linguistics that introduces a selection of these corpora, explores how they can contribute to our understanding of language, society, and history in Australia, and considers avenues that such corpora open up for future research.
This workshop is being run as part of the Language Data Commons of Australia (LDaCA), which is working to build national research infrastructure for the Humanities and Social Sciences, facilitating access to and use of digital language corpora for linguists, scholars across the Humanities and Social Sciences, and non-academics.
Abstract submission
For a 20 min presentation, please submit a 250-300 word abstract in English (excluding references). The presentation should include the following information:
· Speech community/fieldsite: Describe the location of the community and/or their brief history in Australia, the languages spoken and their current status.
· Corpus design principles: Specify the sample size, sociolinguistic background of the participants, method of data collection and/or genre (e.g. sociolinguistic interviews, natural conversations, oral histories, elicited data, etc.); data format (written/spoken/audio/video, etc.) and where it is stored.
· Corpus findings and implications: Summarise some key findings from the corpus and discuss other insights that might be obtained from the data in current or future work.
Important dates
22 May Abstracts due
5 June Notification of acceptance
3 July Workshop
How to Submit: Please submit your abstract by 22 May on https://forms.gle/1pwxVVmUV5hCCZ997
Inquiries: Please contact either Catherine Travis or Li Nguyen
CALL FOR PARTICIPATION
IBERLEF 2023 Task - FinancES. Financial Targeted Sentiment Analysis in
Spanish
Training set released!
Held as part of iberLEF 2023 <https://sites.google.com/view/iberlef-2023>,
a shared evaluation campaign for Natural Language Processing (NLP) systems
in Spanish and other Iberian languages
September 26th 2023, Jaen
Codalab link: https://codalab.lisn.upsaclay.fr/competitions/10052
Dear All,
We are inviting researchers and students to participate in the
shared-task FinancES.
Financial Targeted Sentiment Analysis in Spanish held as part of iberLEF
2023, shared evaluation campaign for Natural Language Processing (NLP)
systems in Spanish and other Iberian languages.
This shared task aims to explore targeted sentiment analysis in the
financial domain. Specifically, the approach adopted here is grounded in
the field of microeconomics. In this regard, Bowles (2004) explains the
role of economic agents, that is to say, individuals or organizations
impacting the economy. The author states that the main microeconomic agents
in the capital market are consumers (households/individuals), companies
(firms), governments, and central banks. Consequently, in order to develop
a sentiment analysis method where different viewpoints are considered,
three different perspectives are included: (1) economic target of the news
item; (2) individual economic agent: companies; and (3) individual economic
agent: consumers –the target is the sector where the economic fact applies,
and companies produce the goods and services that households/individuals
consume. From these three viewpoints, the news item has an impact on the
target and the economic agents which are considered as positive, negative,
or neutral. With all, two tasks are proposed. On the one hand, a task
combining the challenges of aspect-term extraction for identifying the
target entity in text, and aspect-based sentiment classification for
determining the sentiment polarity towards the target. On the other hand, a
task devoted to assessing the impact of a news headline on both other
economic agents, namely, companies and consumers.
The participants will be provided development, development_test, training
and test datasets in Spanish. The dataset for this task is composed of news
headlines written in Spanish collected from digital newspapers specialized
in economic, financial and political news. The dataset is labeled with the
target entity and the sentiment polarity on three dimensions: target,
companies, and consumers. That is, given a headline, it has been manually
classified as positive, neutral, or negative for three specific entities:
(1) target entity (i.e., the specific company or asset where the economic
fact applies), (2) companies (i.e., the entities producing the goods and
services that others consume), and (3) consumers (i.e.,
households/individuals). Each headline was annotated by three members of
the organization committee. In case of disagreement, the annotators
discussed the special case and, if no agreement was reached, the headline
was discarded. During this first step, we compiled about 14k headlines, the
headlines with a short length or those that did not specify a target entity
were filtered out. The final dataset is composed of 8k-10k news headlines.
For the shared tasks, training and test sets will be released (80%-20%).
Today, we have released the training dataset that can be found in the "Files"
subsection of the "Participate" tab. It is worth mentioning that this
dataset includes all the instances that were also released during the
Practice stage; so, it is not needed to combine both datasets.
Finally, remember that the CodaLab competition is open to submit your
results with the development dataset provided. This dataset is also
available in the same section as the training dataset.
Best regards,
The FinancES 2023 organizing committee
References
-
Bowles, S. (2004). Microeconomics: Behavior, institutions, and
evolution. Princeton University Press.
Important dates
-
Release of development corpora: Feb 13, 2023
-
Release of training corpora: Mar 13, 2023
-
Release of test corpora and start of evaluation campaign: Apr 17, 2023
-
End of evaluation campaign (deadline for runs submission): May 3, 2023
-
Publication of official results: May 5, 2023
-
Paper submission: May 28, 2023
-
Review notification: Jun 16, 2023
-
Camera ready submission: Jul 6, 2023
-
IberLEF Workshop (SEPLN 2023): Sep 26, 2023
-
Publication of proceedings: Sep ??, 2023
Organizing committee
-
José Antonio García-Díaz (UMUTeam,, Universidad de Murcia)
-
Ángela Almela Sánchez-Lafuente (UMUTeam, Universidad de Murcia)
-
Francisco García-Sánchez (UMUTeam, Universidad de Murcia)
-
Gema Alcaraz-Mármol (UMUTeam, Universidad de Castilla La Mancha)
-
María José Marín (UMUTeam, Universidad de Murcia)
-
Rafael Valencia-García (UMUTeam, Universidad de Murcia)
The Chair of Data Science and Natural Language Processing (Prof. Siegfried Handschuh) invites applications for a PhD position as part of the recently granted Swiss National Science Foundation (SNF) research project "Conversational AI: Dialogue-based Adaptive Argumentative Writing Support". You will contribute to its successful implementation, as well as the chair's varied activities in teaching and outreach.
Our research at the Data Science and NLP Chair at ICS-HSG focuses on the cutting-edge field of Natural Language Processing (NLP) and Natural Language Understanding (NLU). Our group delves into various aspects, including conversational AI, Large Language Models (LLM), intricate language analysis, Knowledge Graphs and more. Utilising sophisticated methods and algorithms, we aim to extract deeper knowledge and understanding from vast amounts of textual and auditory data. Our research not only delves into the core principles of NLP but also explores its practical applications across various industries.
Details of the post and how to apply: https://bit.ly/phd_conversational_ai
HSG: PhD in Conversational AI (m/f/d)<https://bit.ly/phd_conversational_ai>
You have a university-level master degree in Computer Science, Computational Linguistics, Data Science or related disciplines. You have a strong background in Machine Learning and Natural Language Processing; knowledge of Deep Learning architectures (e.g., Transformer, BERT) and frameworks (e.g., PyTorch, Tensorflow) is a plus. You have good programming skills in Python. Desirable qualifications include one or more of the following areas: Chatbots, Argument Mining and Text Generation. You have excellent written and verbal communication skills in English. You have a strong analytical, structured and independent working style, as well as first experience in writing scientific papers.
bit.ly
--
Prof. Dr. Siegfried Handschuh
Full Professor of Data Science and Natural Language Processing
Director, Institute of Computer Science
University of St.Gallen
E-mail: siegfried.handschuh(a)unisg.ch
Hi,
this is an invitation to attend the NLP challenge day organized by CERIST,
Algeria on March 29, 2023.
The link to attend the event is:
https://visioconf.cerist.dz/CERISTNLPChallenge
The program is available at:
http://www.nlpchallenge.cerist.dz/
Thank you.
Best regards.
Hassina Aliane.
*Dr. Hassina Aliane, Direcctor of Research*
*Head of Natural Language Processing and Digital Content Team,*
*Director of the Digital Humanities R&D laboratory, *
*Editor of the Information Processing at The Digital Age Review. *
*Research Center on Scientific and Technical Information.*
The 6th ASAIL workshop, focused on Natural Language Processing for legal texts and co-located with ICAIL 2023 in Braga, Portugal, is coming up soon.
We would like to invite you to submit papers on, and demonstrations of, original work on automated detection, extraction and analysis of semantic information in legal texts.
Submission deadline: 26th April 2023
Workshop date: 23rd June 2023
We are accepting three tiers of (two column format) papers: long (10 pages); short (6 pages); and position (2 pages).
Since we are very interested in sparking discussion around ideas and work in their early stages, we welcome short and position papers as particularly suitable for this ambition.
You can find more information, including the full call for papers, at our website: https://sites.google.com/view/asail/asail-2023-call-for-papers
Best wishes,
Daphne Odekerken
On behalf of the ASAIL Organising Committee