Dear list members,
We are excited to announce that the AIGC corpus - The aiTECCL
Corpus, is now available to all members of the research community. The
aiTECCL Corpus was compiled by Jiajin Xu and Mingchen Sun of the Corpus
Research Group of the National Research Centre for Foreign Language
Education at Beijing Foreign Studies University.
The corpus consisting of two million words generated by the GPT-3.5
model, using identical writing prompts to those employed in *the TECCL
Corpus* <http://corpus.bfsu.edu.cn/info/1070/1449.htm>, aims to serve as a
reference corpus that exhibits a native-like linguistic quality. The corpus
is made available online on 9 August, 2023.
URL: http://114.251.154.212/cqp/
Username: test
Password: test
Please cite: Xu, Jiajin & Mingchen Sun. 2023. aiTECCL: An AIGC
English Essay Corpus. Beijing: National Research Centre for Foreign
Language Education, Beijing Foreign Studies University. Available online:
http://corpus.bfsu.edu.cn/info/1082/1913.htm
*Justifying the concept of "AIGC Corpus" (Artificial Intelligence Generated
Content Corpus) or Generative Corpus*
The creation of the AIGC Corpus helps expand the concept of
"corpus". In the classic definition of a corpus, the included materials
must be language samples that are authentically or naturally occurring in
real-life communication. Clearly, generative texts do not fall under this
category. We believe that the rationale for the generative corpus can be
viewed from at least three aspects:
1. The so-called principle of "authenticity" itself is a matter of
degree. For example, whether essays written by learners under exam
conditions belong to genuine communication is questionable. In existing
research, some elicited data also has authenticity issues similar to those
found in learners' interlanguage. Therefore, from the perspective of
existing corpora, there are texts with varying degrees of authenticity.
2. The generative corpus can serve as an essential complement to
existing corpora. The emergence of the generative corpus can reconcile the
distinction between "probable language" and "possible language." For
linguistic instances that have not yet appeared in reality, they can be
generated using large language models.
3. Creating a corpus using artificial intelligence technology is a
second-to-best solution under the current conditions for building specific
types of corpora. For example, the aiTECCL corpus simulates a reference
corpus of approximately 10,000 essays, close to the English native speaker
language quality, and written on the same topics as Chinese learners.
Without the use of artificial intelligence methods for generation, it might
be impossible to obtain a reference corpus of such quality and
comparability. Similarly, for corpus construction of languages from
least-developed countries or countries with extremely small populations,
without generative technology, it would be impossible to establish in the
short term.
Further details about the prompt and the Python script we utilised
to create the corpus will be provided on the site soon
<http://corpus.bfsu.edu.cn/info/1082/1913.htm>.
Best wishes,
Jiajin Xu
Ph.D., Professor
National Research Centre for Foreign Language Education
Beijing Foreign Studies University, China
Apologies for the multiple postings.
----
*Indian Language Summarization (ILSUM 2023)*
Website: https://ilsum.github.io/
To be organized in conjunction with FIRE 2023 (fire.irsi.res.in)
15th-18th December 2023, Goa, India
-------------------------------------------------------
The second shared task on Indian Language Summarization (ILSUM) aims at
creating an evaluation benchmark dataset for Indian Languages. This
year ILSUM consists of two subtasks
Subtask 1: This task builds upon the task from ILSUM 2022. In the
first edition, we covered two major Indian languages Hindi and
Gujarati alongside Indian English, a widely recognized dialect of the
English Language. This year's edition adds the Bengali language and an
expanded dataset for the languages from last year. Further, we will
provide abstractive summaries for a subset of each language (~1000 per
language) apart from the headlines which are semi-extractive summaries
in nature.
Like the previous edition, this will be a classic summarization task,
where we will provide
~15,000 article-summary pairs for each language and the participants are
expected to generate a fixed-length summary.
Subtask 2: The task is centred around identifying factual errors in
machine-generated summaries. With the recent implosion of Large
Language models, . While these LLMs are very good at summarization,
among other NLP tasks, they are often prone to hallucinations. This
means the model generates information that is not accurate, not based
on its training data, or is completely made up but looks accurate and
reliable. Further, such tools can be misused to generate misleading or
outright incorrect information. Identifying such inaccuracies can be a
challenging task.
Through this subtask, we aim to address the problem of identifying
factually incorrect information in LLM-generated summaries.
Participants will be provided with an article and its corresponding
machine-generated summary. The objective is to identify the presence
of factual incorrectness in the summaries if any, and classify them in
one of the predefined categories.
*Tentative Timeline*
-------------
7st August - Training Data Released and Registrations open
10th September - Test Data Release
20th September - Run Submission Deadline
25th September - Results Declared
10th October - Working notes due
25th October - Reviews Due
30th October - Camera Ready Submissions due
15th-18th December - FIRE 2023 at Goa, India
*Organisers*
----------------
Jagrat Patel, LDRP-ITR, Gandhinagar, India
Jaivin Barot, LDRP-ITR, Gandhinagar, India
Tanishka Gaur, LDRP-ITR, Gandhinagar, India
Shrey Satapara, Indian Institute of Technology, Hyderabad, India
Sandip Modha, LDRP-ITR, Gandhinagar, India
Parth Mehta, Parmonic, USA
Debasis Ganguly, University of Glasgow, Scotland
*For regular updates subscribe to our mailing list: **ilsum(a)googlegroups.com**
SECOND CALL FOR PAPERS
The 10th Workshop on Argument Mining @ EMNLP 2023
December 7, 2023
https://argmining-org.github.io/2023/
The 10th Workshop on Argument Mining will be held on December 7, 2023 in Singapore together with EMNLP 2023. This will be a hybrid event.
The Workshop on Argument Mining provides a regular forum for the presentation and discussion of cutting-edge research in argument mining (a.k.a argumentation mining) to both academic and industry researchers. By continuing a series of nine successful previous workshops, this edition will welcome the submission of long, short, and demo papers. It will feature two shared tasks, a panel on the last ten years of Argument Mining, and a keynote talk.
IMPORTANT DATES
- Direct paper submission deadline (Softconf): September 1, 2023
- Paper commitment from ARR: September 15, 2023
- Notification of acceptance: October 7, 2023
- Camera-ready submission: October 18, 2023
- Workshop: December 7, 2023
TOPICS OF INTEREST
The topics for submissions include but are not limited to:
- Automatic identification of argument components (e.g., premises and conclusions), the structure in which they form an argument, and relations between arguments and counterarguments (e.g., support and attack) in as well as across documents
- Automatic assessment of arguments and argumentation with respect to various properties, such as stance, clarity, and persuasiveness
- Automatic generation of arguments and their components, including the consideration of discourse goals (e.g., stages of a critical discussion or rhetorical strategies)
- Creation and evaluation of argument annotation schemes, relationships to linguistic and discourse annotations, (semi-) automatic argument annotation methods and tools, and creation of argumentation corpora
- Argument mining in specific genres and domains (e.g., social media, education, law, and scientific writing), each with a unique style (e.g., short informal text, highly structured writing, and long-form documents)
- Argument mining and generation from multi-modal and/or multilingual data
- Integration of commonsense and domain knowledge into argumentation models for mining and generation
- Combination of information retrieval methods with argument mining, e.g., in order to build the next generation of argumentative (web) search engines
- Real-world applications, including argument web search, opinion analysis in customer reviews, argument analysis in meetings, misinformation detection
- Perspectivist approaches to subjective argument mining tasks for which multiple ”ground truths” may exist, including multi-perspective machine learning and the creation of non-aggregated datasets
- Reflection on the ethical aspects and societal impact of argument mining methods
- Reflection on the future of argument mining in light of the fast advancement of large language models (LLMs).
SUBMISSIONS
The organizing committee welcomes the submission of long papers, short papers, and demo descriptions. Accepted papers will be presented either via oral or poster presentations. They will be included in the EMNLP proceedings as workshop papers.
- Long paper submissions must describe substantial, original, completed, and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included. Long papers must be no longer than eight pages, including title, text, figures and tables. An unlimited number of pages is allowed for references. Two additional pages are allowed for appendices, and an extra page is allowed in the final version to address reviewers’ comments.
- Short paper submissions must describe original and unpublished work. Please note that a short paper is not a shortened long paper. Instead, short papers should have a point that can be made in a few pages, such as a small, focused contribution; a negative result; or an interesting application nugget. Short papers must be no longer than four pages, including title, text, figures and tables. An unlimited number of pages is allowed for references. One additional page is allowed for the appendix, and an extra page is allowed in the final version to address reviewers’ comments.
- Demo descriptions must be no longer than four pages, including title, text, examples, figures, tables, and references. A separate one-page document should be provided to the workshop organizers for demo descriptions, specifying furniture and equipment needed for the demo.
Multiple Submissions
ArgMining 2023 will not consider any paper that is under review in a journal or another conference or workshop at the time of submission, and submitted papers must not be submitted elsewhere during the review period.
ArgMining 2023 will also accept submissions of ARR-reviewed papers, provided that the ARR reviews and meta-reviews are available by the ARR commitment deadline (September 15). However, ArgMining 2023 will not accept direct submissions that are actively under review in ARR, or that overlap significantly (>25%) with such submissions.
Submission Format
All long, short, and demonstration submissions must follow the two-column EMNLP 2023 format. Authors are expected to use the LaTeX or Microsoft Word style template (https://2023.emnlp.org/calls/style-and-formatting/). Submissions must conform to the official EMNLP style guidelines, which are contained in these templates. Submissions must be electronic, in PDF format.
Submission Link and Deadline For Direct Submissions
Authors have to fill in the submission form in the START system and upload a PDF of their paper before September 1, 2023, 11:59 pm UTC-12h (anywhere on earth).
https://softconf.com/emnlp2023/ArgMining2023/
For the ARR commitment process, we will provide details in our second call for paper later in the summer.
Double Blind Review
ArgMining 2023 will follow the ACL policies for preserving the integrity of double-blind review for long and short paper submissions. Papers must not include authors’ names and affiliations. Furthermore, self-references or links (such as github) that reveal the author’s identity, e.g., “We previously showed (Smith, 1991) …” must be avoided. Instead, use citations such as “Smith previously showed (Smith, 1991) …” Papers that do not conform to these requirements will be rejected without review. Papers should not refer, for further detail, to documents that are not available to the reviewers. For example, do not omit or redact important citation information to preserve anonymity. Instead, use third person or named reference to this work, as described above (“Smith showed” rather than “we showed”). If important citations are not available to reviewers (e.g., awaiting publication), these paper/s should be anonymised and included in the appendix. They can then be referenced from the submission without compromising anonymity. Papers may be accompanied by a resource (software and/or data) described in the paper, but these resources should also be anonymized.
Unlike long and short papers, demo descriptions will not be anonymous. Demo descriptions should include the authors’ names and affiliations, and self-references are allowed.
ANONYMITY PERIOD (taken from the EMNLP call for papers in verbatim for the most part)
The following rules and guidelines are meant to protect the integrity of double-blind review and ensure that submissions are reviewed fairly. The rules make reference to the anonymity period, which runs from 1 month before the direct submission deadline (starting August 1, 2023) up to the date when your paper is accepted or rejected (October 7, 2023). For papers committed from ARR, the anonymity period starts August 15, 2023. Papers that are withdrawn during this period will no longer be subject to these rules.
You may not make a non-anonymized version of your paper available online to the general community (for example, via a preprint server) during the anonymity period. Versions of the paper include papers having essentially the same scientific content but possibly differing in minor details (including title and structure) and/or in length.
If you have posted a non-anonymized version of your paper online before the start of the anonymity period, you may submit an anonymized version to the conference. The submitted version must not refer to the non-anonymized version, and you must inform the programme chairs that a non-anonymized version exists.
You may not update the non-anonymized version during the anonymity period, and we ask you not to advertise it on social media or take other actions that would further compromise double-blind reviewing during the anonymity period.
You may make an anonymized version of your paper available (for example, on OpenReview), even during the anonymity period.
For arXiv submissions, August 1, 2023 11:59pm UTC-12h (anywhere on earth) is the latest time the paper can be uploaded if you plan a direct submission to the workshop (or August 15, 2023 for papers from ARR committed to the workshops on September 15, 2023).
BEST PAPER AWARDS
In order to recognize significant advancements in argument mining science and technology, ArgMining 2023 will include best paper awards. All papers at the workshop are eligible for the best paper awards and a selection committee consisting of prominent researchers in the fields of interest will select the recipients of the awards.
SHARED TASKS (Submission closed!)
We will be hosting two shared tasks this year:
- ImageArg-Shared-Task-2023: The First Shared Task in Multimodal Argument Mining
- PragTag-2023: The First Shared Task on Pragmatic Tagging of Peer Reviews
ArgMining 2023 ORGANIZING COMMITTEE
Milad Alshomary, Leibniz University Hannover, Germany
Chung-Chi Chen, National Institute of Advanced Industrial Science and Technology, Japan
Smaranda Muresan, Columbia University, USA
Joonsuk Park, University of Richmond, USA
Julia Romberg, Heinrich Heine University of Duesseldorf, Germany
*FinCausal 2023: Financial Document Causality Detection*
We are glad to announce that the Training Dataset for both English and
Spanish is released and ready on Codalab in this link:
https://codalab.lisn.upsaclay.fr/competitions/14596
Please register on CodaLab and get to the FInCausal.2023 Competition.
Under Participate, you will find the Training Datasets together with a
Starting Kit to guide you through the Task.
###### *Task Description and Important Links *#######
*FinCausal-2023 Shared Task: “Financial Document Causality Detection” *is
organised within the *5th Financial Narrative Processing Workshop (FNP
2023)* taking place in the 2023 IEEE International Conference on Big Data
(IEEE BigData 2023) <http://bigdataieee.org/BigData2023/>, Sorrento, Italy,
15-18 December 2023. It is a *one-day event*.
Workshop URL: https://wp.lancs.ac.uk#####cfie/fincausal2023/
<https://wp.lancs.ac.uk/cfie/fincausal2023/>
###### *Additional Information *#######
*Shared Task Description:*
Financial analysis needs factual data and an explanation of the variability
of these data. Data state facts but need more knowledge regarding how these
facts materialised. Furthermore, understanding causality is crucial in
studying decision-making processes.
The *Financial Document Causality Detection Task* (FinCausal) aims at
identifying elements of cause and effect in causal sentences extracted from
financial documents. Its goal is to evaluate which events or chain of
events can cause a financial object to be modified or an event to occur,
regarding a given context. In the financial landscape, identifying cause
and effect from external documents and sources is crucial to explain why a
transformation occurs.
Two subtasks are organised this year. *English FinCausal subtask *and* Spanish
FinCausal subtask*. This is the first year where we introduce a subtask in
Spanish.
*Objective*: For both tasks, participants are asked to identify, given a
causal sentence, which elements of the sentence relate to the cause, and
which relate to the effect. Participants can use any method they see fit
(regex, corpus linguistics, entity relationship models, deep learning
methods) to identify the causes and effects.
*English FinCausal subtask*
- *Data Description: *The dataset has been sourced from various 2019
financial news articles provided by Qwam, along with additional SEC data
from the Edgar Database. Additionally, we have augmented the dataset from
FinCausal 2022, adding 500 new segments. Participants will be provided with
a sample of text blocks extracted from financial news and already labelled.
- *Scope: *The* English FinCausal subtask* focuses on detecting causes
and effects when the effects are quantified. The aim is to identify, in
a causal sentence or text block, the causal elements and the consequential
ones. Only one causal element and one effect are expected in each segment.
- *Length of Data fragments: *The* English FinCausal subtask* segments
are made up of up to three sentences.
- *Data format: *CSV files. Datasets for both the English and the
Spanish subtasks will be presented in the same format.
This shared task focuses on determining causality associated with a
quantified fact. An event is defined as the arising or emergence of a new
object or context regarding a previous situation. So, the task will
emphasise the detection of causality associated with the transformation of
financial objects embedded in quantified facts.
*Spanish FinCausal subtask*
- *Data Description: *The dataset has been sourced from a corpus of
Spanish financial annual reports from 2014 to 2018. Participants will be
provided with a sample of text blocks extracted from financial news,
labelled through inter-annotator agreement.
- *Scope: *The *Spanish FinCausal subtask* aims to detect all types of
causes and effects, not necessarily limited to quantified effects. The
aim is to identify, in a paragraph, the causal elements and the
consequential ones. Only one causal element and one effect are expected in
each paragraph.
- *Length of Data fragments: *The *Spanish FinCausal subtask* involves
complete paragraphs.
- *Data format: *CSV files. Datasets for both the English and the
Spanish subtasks will be presented in the same format.
This shared task focuses on determining causality associated with both
events or quantified facts. For this task, a cause can be the justification
for a statement or the reason that explains a result. This task is also a
relation detection task.
Best regards,
FinCausal 2023 Team
Dear all,
We are looking for a Research Assistant/Associate to work on the project Automated Verification of Textual Claims (AVeriTeC), an ERC project led by Prof. Andreas Vlachos at the University of Cambridge starting in January 2024 or as soon as possible thereafter. The position is for two years. The successful candidate will be based in the Natural Language and Information Processing group (http://www.cl.cam.ac.uk/research/nl/) at the Department of Computer Science and Technology. The project focuses on developing approaches enabling the verification of highly complex claims, which require multiple pieces of evidence. Special focus will be paid to accompanying the verdicts with suitable justifications.
Candidates will have completed a Ph.D. (or be close to completing it) in a relevant field such as NLP, Information Retrieval, Artificial Intelligence or Machine Learning and be able to demonstrate a strong track record of independent research and high-quality publications. Essential skills include excellent programming (Python), NLP techniques, Machine Learning, and proven communication skills.
Appointment at research associate level is dependent on having a PhD or having equivalent skills and experience through non-academic routes. Where a PhD has yet to be awarded appointment will initially be made as a research assistant and amended to research associate when the PhD is awarded.
Enquiries concerning this position should be directed to Prof. Andreas Vlachos (av308(a)cam.ac.uk), and applicants are encouraged to contact him regarding the position.
Apply using this link:
https://www.jobs.cam.ac.uk/job/42366/
Thanks,
Andreas
Dear all,
We are organising a free hybrid event (online and in person): Language Data Analysis for Business and Professional Communication.
It will take place on 22 September 2023 10:00 - 15:30 UK time.
More details and registration: https://cass.lancs.ac.uk/mycalendar-events/?event_id1=3470
The ESRC Centre for Corpus Approaches to Social Science, Lancaster University offers a practical training workshop focused on computational analysis of language data for businesses and professional organisations and anyone interested in communication in professional contexts. The data includes social media, newspapers, business reports, marketing materials and other data sources.
The workshop will introduce a new software tool #LancsBox X<https://lancsbox.lancs.ac.uk/> developed at Lancaster University, which can analyse and visualise large amounts of language data (millions and billions of words). Practical examples of uses of #LancsBox X (case studies) will be provided.
Best,
Vaclav
Professor Vaclav Brezina
Professor in Corpus Linguistics
Department of Linguistics and English Language
ESRC Centre for Corpus Approaches to Social Science
Faculty of Arts and Social Sciences, Lancaster University
Lancaster, LA1 4YD
Office: County South, room C05
T: +44 (0)1524 510828
[cid:02038f34-9006-4e55-866f-0bc6e77964ba]@vaclavbrezina
[cid:30848364-59cf-4561-a71f-9c3e4ac4519c]<http://www.lancaster.ac.uk/arts-and-social-sciences/about-us/people/vaclav-…>
Dear Colleagues,
I'm delighted to share that The 6th Workshop on Financial Technology and
Natural Language Processing (FinNLP) will be collocated with
IJCNLP-AACL-2023 (http://www.ijcnlp-aacl2023.org/) in Bali, Indonesia
(November 1–4).
The submission due for the main track paper is *Sep. 8th, 2023*. For more
details, please refer to the website:
https://sites.google.com/nlg.csie.ntu.edu.tw/finnlp2023/home
We continue the *ML-ESG shared task* in FinNLP, and share new labels
related to Impact Type Identification. You can also get more details about
the shared task on the FinNLP website. The Registration Form is ready:
https://forms.gle/j6gL5jy1upq5LrKY9
Participants in previous FinNLP share various insights into NLP in FinTech
applications. Please refer to past years' proceedings for more details:
https://aclanthology.org/venues/finnlp/
Feel free to let us know if you have any questions. Looking forward to
seeing you at the 6th FinNLP.
Best Regards,
Chung-Chi
---
陳重吉 (Chung-Chi Chen), Ph.D.
Researcher
Artificial Intelligence Research Center, National Institute of Advanced
Industrial Science and Technology, Japan
E-mail: c.c.chen(a)acm.org <cjchen(a)nlg.csie.ntu.edu.tw>
Website: http://cjchen.nlpfin.com
Dear all,
Forwarding on behalf of the Arizona Linguistics Circle 17 (ALC 17)
<https://sites.google.com/view/arizonalinguisticscircle17/home?authuser=3>
committee:
We are happy to announce the 17th annual ALC conference which will take
place Halloweekend🎃 (October 27 to 29, 2023) at the University of Arizona
in Tucson, Arizona.
The theme for the conference is "Collaborative work in Linguistics:
Communities and Societies." We welcome graduate students, undergraduate
students, and language workers in communities to submit a proposal.
In the coming weeks we will announce our invited plenary speakers for ALC
17.
Please see below for the Call for Papers which can also be found via this
<https://easychair.org/cfp/ALC17>EasyChair <https://easychair.org/cfp/ALC17>
link.
Arizona Linguistics Circle 17
Collaborative work in Linguistics: Communities and Societies
University of Arizona
Tucson, Arizona
October 27 to 29, 2023
Keynote Speakers: TBA
Call for Papers Submissions
We are pleased to invite talk proposals for Arizona Linguistics Circle 17
(ALC 17)
<https://sites.google.com/view/arizonalinguisticscircle17/home?authuser=3>.
ALC 17 is an annual graduate student-run conference held at the University
of Arizona. Our goal is to foster a deeper appreciation for linguistics
while providing a healthy environment for academic discussion, especially
as it concerns graduate student research.
The theme of this year’s conference is Collaborative work in Linguistics,
that is the ways in which we have worked to adapt to the unique challenges
of a pandemic, found new ways to conduct research remotely, and made
ethical considerations in using different modalities. However, abstracts
from all areas of linguistics are welcome and encouraged.
This year, we plan to conduct a hybrid conference, with both in-person and
remote aspects (see Covid contingency)
Abstract Guidelines:
-
Abstract may not exceed 500 words (not including keywords, references,
figures, and tableaux)
-
Presentations will consist of 20-minute talks with 10-minute Q&A
-
Authors are limited to one individual and one joint abstract (not
including workshop submissions)
-
Only anonymized submissions will be accepted
-
Abstract submission deadline Friday, September 1, 2023
Abstract submission is via EasyChair <https://easychair.org/cfp/ALC17>. For
questions regarding abstract submission, please contact the abstract review
manager at azlingcircle17(a)gmail.com. Notification of acceptance will be
sent in late August.
Proceedings
Presenters will be invited to submit their paper for publication in Coyote
Papers <https://coyotepapers.sbs.arizona.edu/>, the conference proceedings
for ALC.
Call for Workshop Submissions
We are also inviting proposals for one- to two-hour long workshops on the
theme of Collaborative work in Linguistics within the realm of
experimentation, fieldwork, and data collection. Example workshops include,
but are not limited to, improving sound quality in remote fieldwork,
getting the most from online crowdsourcing or experimentation platforms,
setting up remote speech collection experiments, and more. Workshop
submissions from students are especially welcome.
Workshop abstracts may not exceed 500 words and must include a title,
detailed description (topic, format, length, and content), technical
prerequisites (hardware, software, or platforms), applicant's areas of
expertise, and why the workshop would be of interest to ALC attendees.
Workshop abstracts are submitted on EasyChair and do not count towards the
limit on paper abstract submissions. Authors of accepted workshops will be
offered modest honoraria.
Covid contingency
Our plan is to enjoy an in-person conference. However, we might consider a
hybrid conference, such that presenters will have the option to present
in-person or remotely. This way, both domestic and international presenters
will have the opportunity to deliver their presentations regardless of the
Covid situation or vaccine availability of their location. We will also
have a contingency plan to move the conference to a virtual format if
Arizona is undergoing a significant Covid outbreak at the time of the
conference.
Please let us know if you have any questions via email:
azlingcircle17(a)gmail.com. We look forward to sharing more information with
you over the coming months as we prepare for ALC 17.
Attentively,
Jesús E. González Franco (ALC 17 co-chair)
--
Dr Heather Froehlich
w // http://hfroehli.ch
t // @heatherfro
Hello,
We are pleased to announce that the University of Geneva will be hosting
the 3rd Symposium on Artificial Intelligence for Industry, Science, and
Society (AI2S2) from 11 to 15 September 2023, at Campus Biotech, Geneva. *Both
in-person and remote-only registration are free*; registration closes soon,
thus we encourage you to register ASAP if you intend to participate.
We will be welcoming several renowned experts from each of the event
pillars (industry, science, and society), and have an exciting schedule
covering a wide variety of topics of interest to the community, including
keynote presentations from the following experts:
- *Alistair Knott*, Professor of AI; Victoria University of Wellington
- *Andrew Wyckoff*, Former Director for Science, Technology, and
Innovation; OECD
- *Ger Janssen*, Principal Scientist for AI & Data Science & Digital
Twin; Philips
- *I**nma Martinez*, Chair of the Multi-Stakeholder Committee; GPAI
- *Juha Heikkilä*, International Advisor for AI; European Commission
- *Laure Soulier*, Professor HDR-ISIR Lab; Sorbonne University
- *Maria Girone*, Head of OpenLab; CERN
- *Michael Bronstein*, DeepMind Professor of AI; Oxford University
- *Philippe Limantour*, Chief Technology and Cybersecurity Officer;
Microsoft France
- *Stephen MacFeely*, Director of Data and Analytics; World Health
Organisation
You can find more information about the event at the following links:
- Main event website: https://ai2s2.org/2023/
- Event timetable/agenda: https://ai2s2.org/2023/event/
- Registration (in person): link
<https://indico.cern.ch/event/1288077/page/29800-general-registration>
- Registration (remote only): link
<https://indico.cern.ch/event/1288077/page/29802-remote-registration>
We hope to see many of you next month!
Best regards,
The AI2S2 2023 organisers