*Call for Papers: *The First Workshop on Natural Language Argument-Based
Explanations (ArgNLE - https://argnle.github.io/ECAI-ArgNLE/)
Co-located with ECAI 2024 (https://www.ecai2024.eu/). Universidad de
Santiago de Compostela, Spain.
*Workshop description*
Explainability and Computational Argumentation have usually been
approached as separate, independent research topics, which neglects many
aspects arising from considering the interdependencies between them. To
be effective for human users, explanations are required to be formulated
in natural language, possibly in an argumentative fashion. A workshop on
exploring Natural language Argument-based Explanations is proposed to
investigate this challenging topic, at the crossroad of these different
research fields. Providing high quality explanations for AI predictions
based on machine learning is a challenging and complex task. To work
well it requires, among other factors: selecting a proper level of
generality/specificity of the explanation; considering assumptions about
the familiarity of the explanation beneficiary with the AI task under
consideration; referring to specific elements that have contributed to
the decision; making use of additional knowledge (e.g., metadata) which
might not be part of the prediction process; selecting appropriate
examples; providing evidence supporting negative hypothesis. Finally,
the system needs to formulate the explanation in a clearly
interpretable, and possibly convincing, way.
Given these considerations, the workshop welcomes contributions showing
an integrated vision of Explainable AI (XAI), where low level
characteristics of the deep learning process are combined with higher
level schemas proper of the human argumentation capacity. These
integrated vision relies on three main considerations: i) In neural
architectures the correlation between internal states of the network and
the justification of the network classification outcome is not well
studied; ii) High quality explanations are crucially based on
argumentation mechanisms (e.g., provide supporting examples and rejected
alternatives); iii) In real settings, providing explanations is
inherently an interactive process involving the system and the user.
Accordingly, the workshop calls for cross-disciplinary contributions in
three areas, i.e., deep learning, argumentation and interactivity, to
support a broader and innovative view of explainable AI. More precisely,
the workshop is intended to discuss research challenges that will allow
to advance the state of the art in explainable AI. Providing
explanations to support a certain conclusion has been largely studied in
logic, as a fundamental characteristic of human reasoning. As a result,
both theoretical and computational models of human argumentation are
investigated. The recent resurgence of AI highlighted the idea that low
level system behaviors not only need to be interpretable (e.g., showing
those elements that most contributed to the system decision), but also
need to fit high level human schemas to produce convincing arguments.
**
*Topics of interest*
* Natural language argument-based explanations
* Dialectical, dialogical and conversational explanations
* AI methods to support argumentative explainability
* User-acceptance and evaluation of argumentation-based explanations
* Tools that provide argumentation-based explanations
* Use of argument-based explanations for research from the social
sciences, digital humanities, and related fields
* Real-world applications
The workshop solicits the submission of three types of contributions
relevant to the workshop topics and suitable to generate discussion:
* Original, unpublished contributions
* Dataset related submissions (presenting a dataset or a corpus
related to the workshop topics, that has been or is currently under
development. These papers may have already been published in another
venue).
* Projects related submissions (presenting funded projects or lines of
work within the topics of the workshop, both academic and industrial).
*Invited speaker*
Professor Francesca Toni, Faculty of Engineering, Department of
Computing, Imperial College London, UK.
(https://www.imperial.ac.uk/people/f.toni)
*Important Dates
*
* Paper submission: 31 May 2024
* Notification of acceptance: 1 July 2024
* Camera-ready papers: 31 July 2024
* ArgNLE workshop: 19 or 20 October 2024
*Submission Instructions
*Papers must be written in English, be prepared for double-blind review
using the ECAI LaTeX template, and not exceed 7 pages (not including
references). The ECAI LaTeX Template can be found at
https://ecai2024.eu/download/ecai-template.zip. Papers should be
submitted via EasyChair: https://easychair.org/conferences/?conf=argnle2024
*Workshop Organizers:*
* Rodrigo Agerri <https://ragerri.github.io/> - HiTZ Center - Ixa,
University of the Basque Country UPV/EHU, Spain
* Elena Cabrio <https://www-sop.inria.fr/members/Elena.Cabrio/> -
Université Côte d’Azur, Inria, CNRS, I3S, France
* Serena Villata <https://webusers.i3s.unice.fr/~villata/Home.html> -
Université Côte d’Azur, Inria, CNRS, I3S, France
* Marcin Lewinski <https://ifilnova.pt/en/people/marcin-lewinski/> -
IFILNOVA, Universidade Nova de Lisboa, Portugal
* Bernardo Magnini <http://hlt.fbk.eu/people/magnini> - Fondazione
Bruno Kessler, Italy
* Marie-Francine Moens <https://people.cs.kuleuven.be/~sien.moens/> -
KU Leuven, Belgium
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