Email Gateway (Jun 03 2025 at 11:18): Email Gateway (Jun 03 2025 at 11:18):From: Besik Dundua <bdundua@gmail.com>
# 1st International Workshop on Logic, Statistical and Neural AI (LoStaN
2025)
Updates here: <https://lostan-workshop.github.io/2025/>
Organized by:
Elena Umili, Sapienza University of
Rome, Italy
Federico Sabbatini, University of
Urbino, Italy
Giovanni Ciatto, University of
Bologna, Italy
Matteo Magnini, University of Bologna,
Italy
Yves Lesperance, York University, Canada
The LoStaN workshop aims to bring together researchers and practitioners
interested in bridging the gap between two traditionally distinct paradigms
in Artificial Intelligence:
symbolic reasoning based on logical knowledge,
and data-driven approaches grounded in statistics and (deep)
machine learning.
During its history, AI has seen tremendous progress from both ends of this
spectrum.
Symbolic methods offer interpretability, generalizability, and the ability
to incorporate structured domain knowledge,
while neural and statistical techniques excel in learning from vast amounts
of data, dealing with uncertainty,
and scaling to complex tasks.
However, unifying these paradigms remains a grand challenge.
The workshop aims to foster a research community that sees logical
reasoning and statistical learning not as competing paradigms,
but as complementary facets of intelligent behavior, and their integration
not only as a technical challenge but rather as a transformative
opportunity.
LoStaN provides a forum for discussing foundational questions, novel
methodologies, and practical applications that seek to integrate logical
and statistical AI,
with the aim to energize this interdisciplinary space, promote
collaboration between research communities, and inspire innovative
solutions to AI.
Paper submission deadline: July 11th, 2025, AoE
Author Notification: July 25th, 2025, AoE
Workshop Date: __TBD__, in any case between September 1st and 5th, 2025,
__GET__
* main conference dates: <https://viam.science.tsu.ge/jelia2025/dates>
Camera-ready Submission: __TBD__, in any case _after the workshop_, and
only for authors who are willing to publish their paper in post-preceedings.
Authors are invited to submit original papers in PDF format to ___[link to
OpenReview to be defined]___.
Further information will be available on the CFP page soon.
We invite the following types of contribution:
__Full__ or __short__ papers about approaches involving logic,
statistical and neural models, and their combination/integration.
Full papers should be limited to __14 pages__, while short papers should be
limited to __7 pages__ _(excluding references)_.
__Position papers__ concerning the application of logic, statistical and
neural models in specific fields.
Position papers should be limited to __7 pages__ _(excluding references)_.
__Survey papers__, concerning any of the above. Survey papers should be
limited to __14 pages__ _(excluding references)_.
__Extended abstracts__, providing an overview of recently published
papers regarding the workshop topics. Extended abstract should be limited
to __3 pages__ _(excluding references)_.
We welcome contributions on theoretical foundations, practical
applications, and interdisciplinary approaches combining symbolic,
statistical, and neural methods in AI.
Topics of interest include, but are not limited to:
Integration of logic and statistics into machine learning models
Explainable AI (XAI) and interpretable machine learning via symbolic
methods
Symbolic knoweldge extraction and injection from/into machine learning
models
Neuro-symbolig approaches to AI
Statistical relational learning and probabilistic logic
Learning symbolic representations from data
Inductive Logic Programming (ILP) and relational learning
Causal reasoning and logic-based causal discovery
Neuro-symbolic integration and hybrid AI systems
Fairness, accountability, and transparency in hybrid AI systems
Logic and learning for multi-agent systems
Human-centric AI: reasoning, learning, and interaction
Deep learning and knowledge extraction
Formal methods for the verification of neural networks
Benchmarking and evaluation of hybrid AI systems
Applications in robotics, natural language understanding, bioinformatics,
etc.
Toolkits and platforms for integrating logic, statistics, and neural
networks
Submissions should be in __CEUR Workshop Proceedings__ style;
Submissions must be exported in __PDF format__;
_Camera-ready_ versions shall include the LaTeX __source files__;
Submissions are not anonymous __(single-blind)__.
Each submission will undergo a traditional single-blind review process.
This phase applies to all papers, regardless of type, and will determine
the final acceptance or rejection decision.
Accepted contributions are presented at the workshop, and authors may
collect further comments and insights.
After that, authors who are willing to publish their contribution to the
workshop proceedings will be requested to produce a final version of the
paper,
addressing the reviewers’ suggestions and possibly integrating comments and
insights from the workshop.
All papers will undergo the standard assessment in which reviewers will be
asked to consider the submission focusing on its:
__significance__: is the idea proposed in the paper meaningful for the
LoStaN community? Are the results relevant?
__soundness__: is the approach proposed in the paper correct and robust?
Are experiments (if any) well-designed?
__clarity__: is the paper clear and well organized? Is the discussion
complete?
__contextualization__: is relevant background and related literature
being adequately referenced?
__novelty__: is the contribution novel either from a conceptual or
technical perspective?
Furthermore, the reviews will take into account the specific
characteristics of the submitted contributions
(see submission types above)
to obtain their final decision.
The workshop will publish its own proceedings onto Scopus-indexed
repositories, such as CEUR-WS.
__Important note:__ Accepted papers will be included in the workshop
proceedings __only if__ the authors explicitly agree to do so.
In this way, works which are not mature enough for publication, as well as
works which have already been published elsewhere can be presented and
discussed at the workshop.
A selection of the best papers presented at the workshop will be invited to
submit an extended version to a special issue in a journal (TBD).
We are negotiating with several journals, and we will update this CfP as
soon as we have more information.
Last updated: Jun 20 2025 at 16:26 UTC