Dear All,
We are the guest editors of the special issue “Mathematical and Computational Modeling of Language and Social Behaviors” in Mathematics<https://www.mdpi.com/journal/mathematics> (IF=2.592, Q1).
We would like to call for papers to the above special issue from people whose research interest include computational linguistics and the related areas. Deadline for manuscript submissions: 30 June 2023.
The aim of the special issue is to highlight the contributions of quantitative modeling and NLP technology to understanding collective human behaviors and to help resolve some of the greatest challenges of our time. We welcome new or improved methods to model linked data from heterogeneous sources and their computational application to solve some real-world problems relating to languages and social behaviors. Topics of interest include such as Sentiment and/or Emotion Analysis, fake news detection, FinNLP and Medical Informatics.
Check the details about the special issue through the link: https://www.mdpi.com/si/mathematics/Mathe_Compu_NLP
We look forward to your submissions and contribution to this special issue. Thank you very much!
Best,
Clara
(on behalf of the Guest Editors)
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Due to multiple requests, we are *extending* the deadline to August 20, 2022
=============================
Last call for paper: submission deadline August 20, 2022
=============================
*Apologies if you received multiple copies of this CFP*
Location: Gyeongju, Republic of Korea
Workshop Date: October 16-17, 2022
Workshop link: https://healthlanguageprocessing.org/smm4h-2022/
Submission link: https://www.softconf.com/coling2022/7thSMM4H/
The workshop will include two components — a standard workshop and a shared
task
Workshop
The Social Media Mining for Health Applications (#SMM4H) workshop serves as
a venue for bringing together researchers interested in automatic methods
for the collection, extraction, representation, analysis, and validation of
social media data (e.g., Twitter, Reddit, Facebook) for health informatics.
The 7th #SMM4H Workshop, co-located at COLING 2022 (
https://coling2022.org/index), invites 4-page paper (unlimited references
in standard COLING format) submissions on original, unpublished research in
all aspects at the intersection of social media mining and health. Topics
of interest include, but are not limited to:
Methods for the automatic detection and extraction of
health-related concept mentions in social media
Mapping of health-related mentions in social media to standardized
vocabularies
Deriving health-related trends from social media
Information retrieval methods for obtaining relevant social media
data
Geographic or demographic data inference from social media discourse
Virus spread monitoring using social media
Mining health-related discussions in social media
Drug abuse and alcoholism incidence monitoring through social media
Disease incidence studies using social media
Sentinel event detection using social media
Semantic methods in social media analysis
Classifying health-related messages in social media
Automatic analysis of social media messages for disease
surveillance and patient education
Methods for validation of social media-derived hypotheses and
datasets
Shared task
The workshop organizers this year are hosting 10 shared tasks i.e. NLP
challenges as part of the workshop. Participating teams will be provided
with a set of annotated posts for developing systems, followed by a
three-day window during which they will run their systems on unlabeled test
data and upload it to Codalab for evaluation. For additional details about
the tasks and information about registration, data access, paper
submissions, and presentations, go to
https://healthlanguageprocessing.org/smm4h-2022/
Task 1 – Classification, detection, and normalization of Adverse Events
(AE) mentions in tweets (in English)
Task 2 – Classification of stance and premise in tweets about health
mandates related to COVID-19 (in English)
Task 3 – Classification of changes in medication treatments in tweets
and WebMD reviews (in English)
Task 4 – Classification of tweets self-reporting exact age (in English)
Task 5 – Classification of tweets containing self-reported COVID-19
symptoms (in Spanish)
Task 6 – Classification of tweets which indicate self-reported COVID-19
vaccination status (in English)
Task 7 – Classification of self-reported intimate partner violence on
Twitter (in English)
Task 8 – Classification of self-reported chronic stress on Twitter (in
English)
Task 9 – Classification of Reddit posts self-reporting exact age (in
English)
Task 10 – Detection of disease mentions in tweets – SocialDisNER (in
Spanish)
Organizing Committee
Graciela Gonzalez-Hernandez, Cedars-Sinai Medical Center, USA
Davy Weissenbacher, Cedars-Sinai Medical Center, USA
Arjun Magge, University of Pennsylvania, USA
Ari Z. Klein, University of Pennsylvania, USA
Ivan Flores, Cedars-Sinai Medical Center, USA
Karen O’Connor, University of Pennsylvania, USA
Raul Rodriguez-Esteban, Roche Pharmaceuticals, Switzerland
Lucia Schmidt, Roche Pharmaceuticals, Switzerland
Juan M. Banda, Georgia State University, USA
Abeed Sarker, Emory University, USA
Yuting Guo, Emory University, USA
Yao Ge, Emory University, USA
Elena Tutubalina, Insilico Medicine, Hong Kong
Luis Gasco, Barcelona Supercomputing Center, Spain
Darryl Estrada, Barcelona Supercomputing Center, Spain
Martin Krallinger, Barcelona Supercomputing Center, Spain
Program Committee
Cecilia Arighi, University of Delaware, USA
Natalia Grabar, French National Center for Scientific Research, France
Thierry Hamon, Paris-Nord University, France
Antonio Jimeno Yepes, Royal Melbourne Institute of Technology, Australia
Jin-Dong Kim, Database Center for Life Science, Japan
Corrado Lanera, University of Padova, Italy
Robert Leaman, US National Library of Medicine, USA
Kirk Roberts, University of Texas Health Science Center at Houston, USA
Yutaka Sasaki, Toyota Technological Institute, Japan
Pierre Zweigenbaum, French National Center for Scientific Research, France
Contact
All questions should be emailed to Davy Weissenbacher (
davy.weissenbacher(a)cshs.org)
Dear colleagues,
We are pleased to invite you to the North Africans in ML affinity group
workshop <https://sites.google.com/view/northafricansinml/cfp>, which will
take place at NeurIPS 2022. The workshop will include talks, poster
sessions, as well as a shared task relating to ML in North Africa. We will
have both archival and non-archival tracks and invited talks. Junior
researchers and students interested in NLP from North African institutions
and beyond (academia and industry) are welcome to present their new work as
well as completed or ongoing research projects or ideas.
All nationalities are welcome! Authors of non-archival papers can choose to
have their abstracts, bios, and posters posted on our website. NeurIPS D&I
will provide some travel grants and registration fee waivers to the
participants. Please note that all participants are encouraged to apply for
NeurIPS registration fee waivers.
We welcome submissions related to any topic of Machine Learning, including
(but not limited to):
- Machine Learning Applications for North Africa
- Theoretical Machine Learning
- Natural Language Processing and Information Retrieval
- Computer Vision and Computer Graphics
- Reinforcement Learning
- Applications of Machine Learning for the Environment and Climate
- Geometric Deep learning
You can visit our website: https://sites.google.com/view/northafricansinml/.
Twitter https://twitter.com/NorthAfricansML
Best regards,
The organisers.
Apologies for cross-posting!
************************************************************************************
URL: https://emw.ku.edu.tr/case-2022/
Sep 7, 2022: Submission deadline on Softconf
Jul 15, 2022: Latest ARR submission deadline for ARR
Oct 2, 2022: Latest ARR commitment deadline
Oct 9, 2022: Notification of Acceptance
Oct 16, 2022: Camera-ready papers due
Workshop dates: Dec 7-8, 2021
Location: Hybrid -> Abu Dhabi & Online
Please see below for the important dates of the shared tasks.
There are two options for submissions that are i) Softconf page of the
workshop: https:// <https://www.softconf.com/m/icspcc2022>
softconf.com/emnlp2022/case2022 and ii) ACL Rolling review (ARR):
https://aclrollingreview.org/dates.
************************************************************************************
Nowadays, the unprecedented quantity of easily accessible data on social,
political, and economic processes offers ground-breaking potential in
guiding data-driven analysis in social and human sciences and in driving
informed policy-making processes. Governments, multilateral organizations,
and local and global NGOs present an increasing demand for high-quality
information about a wide variety of events ranging from political violence,
environmental catastrophes, and conflict, to international economic and
health crises (Coleman et al. 2014; Porta and Diani, 2015) to prevent or
resolve conflicts, provide relief for those that are afflicted, or improve
the lives of and protect citizens in a variety of ways. Black Lives Matter
protests (http://protestmap.raceandpolicing.com) and conflicts in Syria (
https://www.cartercenter.org/peace/conflict_resolution/syria-conflict-resol…)
are only two examples where we must understand, analyze, and improve
real-life situations using such data. Finally, these efforts respond to
“growing public interest in up-to-date information on crowds” as well (
https://sites.google.com/view/crowdcountingconsortium/faqs).
Event extraction has long been a challenge for the natural language
processing (NLP) community as it requires sophisticated methods in defining
event ontologies, creating language resources, domain specific grammars,
developing Machine Learning models and other algorithmic approaches for
various event-detection- specific tasks, such entity detection, semantic
labeling, event classification and clustering and others (Pustojevsky et
al. 2003; Boroş, 2018; Chen et al. 2021). Social and political scientists
have been working to create socio-political event (SPE) databases such as
ACLED, EMBERS, GDELT, ICEWS, MMAD, PHOENIX, POLDEM, SPEED, TERRIER, and
UCDP following similar steps for decades. These projects and the new ones
increasingly rely on machine learning (ML), deep learning (DL), and NLP
methods to deal better with the vast amount and variety of data in this
domain (Hürriyetoğlu et al. 2020). Unfortunately, automated approaches
suffer from major issues like bias, limited generalizability, class
imbalance, training data limitations, and ethical issues that have the
potential to affect the results and their use drastically (Lau and Baldwin
2020; Bhatia et al. 2020; Chang et al. 2019). Moreover, the results of the
automated systems for SPE information collection have neither been
comparable to each other nor been of sufficient quality (Wang et al. 2016;
Schrodt 2020). SPEs are varied and nuanced. Both the political context and
the local language used may affect whether and how they are reported.
We invite contributions from researchers in computer science, NLP, ML, DL,
AI, socio-political sciences, conflict analysis and forecasting, peace
studies, as well as computational social science scholars involved in the
collection and utilization of SPE data.
Academic workshops specific to tackling event information in general or for
analyzing text in specific domains such as health, law, finance, and
biomedical sciences have significantly accelerated progress in these topics
and fields, respectively. However, there has not been a comparable effort
for handling SPEs. We fill this gap. We invite work on all aspects of
automated coding and analysis of SPEs and events in general from mono- or
multi-lingual text sources. This includes (but is not limited to) the
following topics
1) Extracting events in and beyond a sentence, event coreference
resolution,
2) New datasets, training data collection, and annotation for event
information,
3) Event-event relations, e.g., subevents, main events, causal relations,
4) Event dataset evaluation in light of reliability and validity metrics,
5) Defining, populating, and facilitating event schemas and ontologies,
6) Automated tools and pipelines for event collection related tasks,
7) Lexical, syntactic, discursive, and pragmatic aspects of event
manifestation,
8) Methodologies for development, evaluation, and analysis of event
datasets,
9) Applications of event databases, e.g. early warning, conflict
prediction, policymaking,
10) Estimating what is missing in event datasets using internal and
external information,
11) Detection of new SPE types, e.g. creative protests, cyberactivism,
COVID19 related,
12) Release of new event datasets,
13) Bias and fairness of the sources and event datasets,
14) Ethics, misinformation, privacy, and fairness concerns pertaining to
event datasets, and
15) Copyright issues on event dataset creation, dissemination, and sharing.
16) We encourage submissions of new system description papers on our
available benchmarks (ProtestNews @ CLEF 2019, AESPEN @ LREC 2020, and CASE
@ 2021). Please contact the organizers if you would like to access the
data.
The proceedings of the previous editions should be indicative of what we
cover: ProtestNews @ CLEF 2019 (http://ceur-ws.org/Vol-2380/), AESPEN @ ACL
2020 (https://aclanthology.org/volumes/2020.aespen-1/), CASE @ ACL-IJCNLP
2021 (https://aclanthology.org/volumes/2021.case-1/).
**** Shared tasks ****
Task 1- Multilingual protest news detection: This is the same shared task
organized at CASE 2021 (For more info:
https://aclanthology.org/2021.case-1.11/) But this time there will be
additional data and languages at the evaluation stage. Contact person: Ali
Hürriyetoğlu (ali.hurriyetoglu(a)gmail.com). Github:
https://github.com/emerging-welfare/case-2022-multilingual-event
Task 2- Automatically replicating manually created event datasets: The
participants of Task 1 will be invited to run the systems they will develop
to tackle Task 1 on a news archive (For more info
https://aclanthology.org/2021.case-1.27/). Contact person: Hristo Tanev (
htanev(a)gmail.com). Github:
https://github.com/emerging-welfare/case-2022-multilingual-event
Task 3- Event causality identification: Causality is a core cognitive
concept and appears in many natural language processing (NLP) works that
aim to tackle inference and understanding. We are interested to study event
causality in news, and therefore, introduce the Causal News Corpus. The
Causal News Corpus consists of 3,559 event sentences, extracted from
protest event news, that have been annotated with sequence labels on
whether it contains causal relations or not. Subsequently, causal sentences
are also annotated with Cause, Effect, and Signal spans. Our two subtasks
(Sequence Classification and Span Detection) work on the Causal News
Corpus, and we hope that accurate, automated solutions may be proposed for
the detection and extraction of causal events in news. Contact person:
Fiona Anting Tan (tan.f(a)u.nus.edu). Github:
https://github.com/tanfiona/CausalNewsCorpus
**** Deadlines for the Shared tasks ****
** Task 1 & 2:
Training data available: The training data from CASE 2021 is used.
New test data available: Sept 15, 2022
Test end: Sep 25, 2022
System Description Paper submissions due: Oct 2, 2022
Notification to authors after review: Oct 09, 2022
Camera-ready: Oct 16, 2022
** Task 3:
Training data available: Apr 15, 2022
Validation data available: Apr 15, 2022
Validation labels available: Aug 01, 2022
Test data available: Aug 01, 2022
Test start: Aug 01, 2022
Test end: extended from Aug 15 to Aug 31, 2022
System Description Paper submissions due: Sep 07, 2022
Notification to authors after review: Oct 09, 2022
Camera ready: Oct 16, 2022
*** Keynotes ***
Three prominent scholars have accepted our invitation as keynote speakers:
i) J. Craig Jenkins (https://sociology.osu.edu/people/jenkins.12) is
Academy Professor Emeritus of Sociology at The Ohio State University. He
directed the Mershon Center for International Security Studies from 2011 to
2015 and is now senior research scientist.
ii) Scott Althaus (https://pol.illinois.edu/directory/profile/salthaus) is
Merriam Professor of Political Science, Professor of Communication, and
Director of the Cline Center for Advanced Social Research at the University
of Illinois Urbana-Champaign.
iii) Thien Huu Nguyen (https://ix.cs.uoregon.edu/~thien/) is an assistant
professor in the Department of Computer and Information Science at the
University of Oregon. Thien is the director of the NSF IUCRC Center for Big
Learning (CBL) at the University of Oregon.
**** Submissions *****
This call solicits short and long papers reporting original and unpublished
research on the topics listed above. The papers should emphasize obtained
results rather than intended work and should indicate clearly the state of
completion of the reported results. The page limits and content structure
announced at ACL ARR page (https://aclrollingreview.org/cfp) should be
followed for both short and long papers.
Papers should be submitted on the START page of the workshop (
http://softconf.com/emnlp2022/case2022) or on ARR page (TBA on the workshop
website) in PDF format, in compliance with the ACL publication author
guidelines for ACL publications
https://acl-org.github.io/ACLPUB/formatting.html
The reviewing process will be double-blind and papers should not include
the author's names and affiliations. Each submission will be reviewed by at
least three members of the program committee. The workshop proceedings will
be published on ACL Anthology.
The IRLab at the University of Amsterdam (https://irlab.science.uva.nl/)
seeks a postdoc or PhD student to work on fairness-aware learning to rank.
Algorithmic hiring is on the rise and rapidly becoming necessary in some
sectors, but these systems run the risk of reproducing and amplifying
discriminatory biases. In the context of the interdisciplinary FINDHR EU
project on Fairness and Intersectional Non-Discrimination in Human
Recommendation, the successful postdoc or PhD student will design and
evaluate fairness-aware ranking algorithms. In contrast with fairness-aware
ranking in contexts where click feedback is immediate, the algorithmic
hiring use case raises new challenges of learning from delayed rewards,
leveraging complex feedback, and supporting optional positive actions.
Interested candidates are invited to apply by 25 August, 2022.
For more details and to apply, see
https://vacatures.uva.nl/UvA/job/Postdoctoral-Researcher-or-PhD-Position-in…
Our team has a strong collaborative and collegial atmosphere. We strongly
encourage applications coming from a unique perspective. Tell us how your
background fits with the focus of this position, even if your profile is
slightly different from the profile / requirements written in the official
vacancy text linked to above.
In August 2022, our team will move into a brand new, sustainable,
energy-neutral, and circular building in Amsterdam Science Park. Come and
join us!
Final call for papers
Third workshop on Resources for African Indigenous Language (RAIL)
https://bit.ly/rail2022
The South African Centre for Digital Language Resources (SADiLaR) is
organising the 3rd RAIL workshop in the field of Resources for African
Indigenous Languages. This workshop aims to bring together researchers
who are interested in showcasing their research and thereby boosting
the field of African indigenous languages. This provides an overview of
the current state-of-the-art and emphasizes availability of African
indigenous language resources, including both data and tools.
Additionally, it will allow for information sharing among researchers
interested in African indigenous languages and also start discussions
on improving the quality and availability of the resources. Many
African indigenous languages currently have no or very limited
resources available and, additionally, they are often structurally
quite different from more well-resourced languages, requiring the
development and use of specialized techniques. By bringing together
researchers from different fields (e.g., (computational) linguistics,
sociolinguistics, language technology) to discuss the development of
language resources for African indigenous languages, we hope to boost
research in this field.
The RAIL workshop is an interdisciplinary platform for researchers
working on resources (data collections, tools, etc.) specifically
targeted towards African indigenous languages. It aims to create the
conditions for the emergence of a scientific community of practice that
focuses on data, as well as tools, specifically designed for or applied
to indigenous languages found in Africa.
Suggested topics include the following:
* Digital representations of linguistic structures
* Descriptions of corpora or other data sets of African indigenous
languages
* Building resources for (under resourced) African indigenous languages
* Developing and using African indigenous languages in the digital age
* Effectiveness of digital technologies for the development of African
indigenous languages
* Revealing unknown or unpublished existing resources for African
indigenous languages
* Developing desired resources for African indigenous languages
* Improving quality, availability and accessibility of African
indigenous language resources
The 3rd RAIL workshop 2022 will be co-located with the 10th Southern
African Microlinguistics Workshop (
https://sites.google.com/nwulettere.co.za/samwop-10/home). This will be
an in-person event located in Potchefstroom, South Africa. Registration
will be free.
RAIL 2022 submission requirements:
* RAIL asks for full papers from 4 pages to 8 pages (plus more pages
for references if needed), which must strictly follow the Journal of
the Digital Humanities Association of Southern Africa style guide (
https://upjournals.up.ac.za/index.php/dhasa/libraryFiles/downloadPublic/30
).
* Accepted submissions will be published in JDHASA, the Journal of the
Digital Humanities Association of Southern Africa (
https://upjournals.up.ac.za/index.php/dhasa/).
* Papers will be double blind peer-reviewed and must be submitted
through EasyChair (https://easychair.org/my/conference?conf=rail2022).
Important dates
Submission deadline: 28 August 2022
Date of notification: 30 September 2022
Camera ready copy deadline: 23 October 2022
RAIL: 30 November 2022, North-West University - Potchefstroom
SAMWOP: 1 – 3 December 2022, North-West University - Potchefstroom
Organising Committee
Jessica Mabaso
Rooweither Mabuya
Muzi Matfunjwa
Mmasibidi Setaka
Menno van Zaanen
South African Centre for Digital Language Resources (SADiLaR), South
Africa
--
Prof Menno van Zaanen menno.vanzaanen(a)nwu.ac.za
Professor in Digital Humanities
South African Centre for Digital Language Resources
https://www.sadilar.org
________________________________
NWU CORONA VIRUS:
http://www.nwu.ac.za/coronavirus/
NWU PRIVACY STATEMENT:
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________________________________
Dear all,
We are hiring a Research Associate (post-doc) to work in the area of
natural language processing and machine learning, and more specifically
analysis of online misinformation. The main focus of the post-holder will
be research on explainable machine learning methods for detection and
analysis of online misinformation.
This post is for 3 years and the expected start is November 2022 (or
shortly after). The deadline for application is 1st of September.
More information:
https://www.jobs.ac.uk/job/CSF074/research-associate-in-machine-learning-an…
Kind regards
--
*Carolina Scarton*
Lecturer in Natural Language Processing
Department of Computer Science
University of Sheffield
http://staffwww.dcs.shef.ac.uk/people/C.Scarton/
****Apologies for Cross Posting *****
Dear colleagues,
you are invited to submit a system paper for the first Propaganda Detection
in Arabic shared task held with the 7th Arabic Natural Language Processing
Workshop (WANLP 2022) co-located with the EMNLP2 022 Conference in Abu
Dhabi (Dec 7, 2022).
https://sites.google.com/view/propaganda-detection-in-arabic/
Tasks
Subtask 1: Given only the “text” of a Tweet, identify which of the 20
techniques (https://propaganda.qcri.org/annotations/definitions.html) are
used in it. This is a multilabel classification problem.
Subtask 2: Given only the “text” of a Tweet, identify which of the 20
techniques (https://propaganda.qcri.org/annotations/definitions.html) are
used in it together with the span(s) of text covered by each technique.
This is a sequence tagging task
Important Dates
July 24, 2022: Release of training, dev and dev-test data, and evaluation
scripts.
September 10, 2022: Registration deadline.
September 10, 2022: Release of test data (and final training and dev data).
September 15, 2022: End of the evaluation cycle (test set submission closes)
September 20, 2022: Results released
October 5, 2022: System description paper submissions due.
October 15, 2022: Notification of acceptance.
October 31, 2022: Camera-ready versions due.
December 7, 2022: WANLP 2022 workshop at EMNLP in Abu Dhabi
Lab Registration
Please register here: https://shorturl.at/ftuz9
Datasets
The Datasets are hosted on the Gitlab repository:
https://gitlab.com/arabic-nlp/propaganda-detection/
Organizers
Firoj Alam, Qatar Computing Research Institute, HBKU
Hamdy Mubarak, Qatar Computing Research Institute, HBKU
Wajdi Zaghouani, HBKU
Preslav Nakov, Qatar Computing Research Institute, HBKU
Giovanni Da San Martino, University of Padova
----
*Wajdi Zaghouani, Ph.D.*
*Assistant Professor*
College of Humanities and Social Sciences
P.O. Box 34110 | Education City | Doha, Qatar
tel: +974 4454 5601 | mob: +974 33454992
wzaghouani(a)hbku.edu.qa| Office A141, LAS Building
Dear all,
As part of my research, I am looking for a (preferably Python) library that will take Hebrew text and transliterate it phonetically either to Latin characters, IPA, or Cyrillic characters. (This will be used in a tokenizer; I am happy to share details privately if someone would like to learn more about my project.)
I have already found a solution for restoring the vowels (nikud) in Hebrew text, so that's not an issue.
The ideal case would be to something similar to https://www.alittlehebrew.com/transliterate/ or (less ideal, because it uses non-IPA symbols and is not in Python) https://github.com/charlesLoder/hebrew-transliteration.
To avoid flooding the mailing list, feel free to email me directly at mguzenko(a)outlook.com<mailto:mguzenko@outlook.com>.
Thank you.
Best,
Maria Guzenko
MA Candidate in Technology for Translation and Interpreting
Dear colleagues,
We are delighted to invite you to our public Workshop on Pronouns and Machine Translation, which will be held on-line on 19 August 2022. The workshop features a series of lectures on recent work related to understanding, modelling and evaluating pronouns and other discourse-level phenomena in neural machine translation and a panel discussion. Here is the link to the workshop: https://christianhardmeier.rax.ch/workshop/pronouns-and-mt-2022/
**Registration**
Registration is free. Please sign up with the following link:
https://uu-se.zoom.us/meeting/register/u50rd-qgrjoiGtK8YvlWZ1hecbzHsxp9oBRa
Program:
Time (UTC+2) Speaker
11:00-11:45 Sheila Castilho, ADAPT Centre, Dublin City University
11:45-12:30 Deyi Xiong, Tianjin University
12:30-13:00 Kayo Yin, DeepMind/UC Berkeley
13:00-13:30 Prathyusha Jwalapuram, Nanyang Technological University
13:30-14:00 Panel discussion
14:00-14:30 Break
14:30-15:00 Christian Hardmeier, Uppsala University/IT University of Copenhagen
15:00-15:30 Gongbo Tang, Uppsala University
15:30-16:00 Biao Zhang, University of Edinburgh
Best Regards,
Christian Hardmeier and Gongbo Tang
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