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CausalNeSy Call for papers: Deadline March 6, 2025
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Utkarshani Jaimini
Jan 6, 2025, 9:23:51 PMJan 6
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Call for Papers - CausalNeSy: Workshop on Causal Neuro-symbolic AI
@ Extended Semantic Web Conference (ESWC) 2025, Portoroz, Slovania
Website: https://sites.google.com/view/causalnesy/=========
Highlights
=========
Submission Deadline: 6th March 2025The workshop on Causal Neuro-symbolic AI (CausalNeSy) aims to bring together researchers and practitioners from academia and industry to share their experiences and insights on applying causality and neuro-symbolic AI techniques to real-world problems.This workshop is archival and all submitted manuscripts will be peer-reviewed and will be published in CEUR proceedings.===============
Topics of interest
===============
We invite researchers, practitioners, and industry experts to submit original research papers, surveys, and case studies addressing the following themes (including but not limited to):1. Core Methods and Frameworks
Causal Knowledge Representation: Approaches for representing causal knowledge using neuro-symbolic AI methods.
Causal Reasoning in Neuro-symbolic Systems: Methods for implementing causal reasoning within neuro- symbolic frameworks.
Neuro-symbolic Methods for Causal Structure Learning: Techniques for learning causal structures within neuro- symbolic frameworks.
Causal Representation Learning: Approaches to causal representation learning using neuro-symbolic AI.
2. Integration of Techniques and Paradigms
Causal Knowledge Graph Embeddings: Utilizing embeddings of causal knowledge for graph completion and causal discovery.
Causal Reasoning and Neural Networks: Techniques for harmonizing causal symbolic reasoning with neural net- works to enhance AI interpretability and robustness.
Integration of Causality, Logic, and Probability: Approaches that combine causality, logic, and probabilities in neuro-symbolic AI.
Causal Generative Models: Development and application of causal generative models for machine learning.
Causal Neuro-Symbolic AI in Large Language Models (LLMs): Integration of causality in LLMs for enhanced reasoning capabilities.
Causal Foundation Models: Development of causal foundation models within neuro-symbolic AI.
3. Explanation, Trust, Fairness, and Accountability
Neuro-symbolic Methods for Causal Explanation: Techniques for explaining causes and their effects using neuro-symbolic methods.
Fairness, Accountability, Transparency, and Explainability: Ensuring fairness, accountability, transparency, and explainability in Causal Neuro-symbolic AI systems.
Trustworthiness, Grounding, Instruct-ability, and Alignment: Addressing issues related to the trustworthiness, grounding, instruct-ability, and alignment of Causal Neuro-symbolic AI systems.
4. Applications
Causal Discovery in Complex Environments: Strategies for discovering causal relationships in complex environments using neuro-symbolic AI.
Causal Neuro-symbolic AI in Use: Real-world applications of causal and neuro-symbolic AI methods in domains such as healthcare, finance, autonomous systems, natural language processing, etc
===========
Submissions
===========
We invite authors to submit unpublished original papers. Submitted papers should not have been previously published or accepted for publication in substantially similar form in any peer-reviewed venue, such as journals, conferences, or workshops.
More information is available at https://sites.google.com/view/causalnesy/==============
Important Dates
==============
Paper submission deadline: 6th March 2025
Author notification: 3rd April 2025
Camera-ready submission deadline: 17 April 2025
Workshop: June 1-2 2025
All deadlines must be considered at 23:59 AoE.===========
Useful Links
===========
Website: https://sites.google.com/view/causalnesy/
Submission: https://openreview.net/group?id=eswc-conferences.org/ESWC/2025/Workshop/Causal-NeSy#tab-your-consoles
Contact: ujai...@email.sc.edu
@ Extended Semantic Web Conference (ESWC) 2025, Portoroz, Slovania
Website: https://sites.google.com/view/causalnesy/=========
Highlights
=========
Submission Deadline: 6th March 2025The workshop on Causal Neuro-symbolic AI (CausalNeSy) aims to bring together researchers and practitioners from academia and industry to share their experiences and insights on applying causality and neuro-symbolic AI techniques to real-world problems.This workshop is archival and all submitted manuscripts will be peer-reviewed and will be published in CEUR proceedings.===============
Topics of interest
===============
We invite researchers, practitioners, and industry experts to submit original research papers, surveys, and case studies addressing the following themes (including but not limited to):1. Core Methods and Frameworks
Causal Knowledge Representation: Approaches for representing causal knowledge using neuro-symbolic AI methods.
Causal Reasoning in Neuro-symbolic Systems: Methods for implementing causal reasoning within neuro- symbolic frameworks.
Neuro-symbolic Methods for Causal Structure Learning: Techniques for learning causal structures within neuro- symbolic frameworks.
Causal Representation Learning: Approaches to causal representation learning using neuro-symbolic AI.
2. Integration of Techniques and Paradigms
Causal Knowledge Graph Embeddings: Utilizing embeddings of causal knowledge for graph completion and causal discovery.
Causal Reasoning and Neural Networks: Techniques for harmonizing causal symbolic reasoning with neural net- works to enhance AI interpretability and robustness.
Integration of Causality, Logic, and Probability: Approaches that combine causality, logic, and probabilities in neuro-symbolic AI.
Causal Generative Models: Development and application of causal generative models for machine learning.
Causal Neuro-Symbolic AI in Large Language Models (LLMs): Integration of causality in LLMs for enhanced reasoning capabilities.
Causal Foundation Models: Development of causal foundation models within neuro-symbolic AI.
3. Explanation, Trust, Fairness, and Accountability
Neuro-symbolic Methods for Causal Explanation: Techniques for explaining causes and their effects using neuro-symbolic methods.
Fairness, Accountability, Transparency, and Explainability: Ensuring fairness, accountability, transparency, and explainability in Causal Neuro-symbolic AI systems.
Trustworthiness, Grounding, Instruct-ability, and Alignment: Addressing issues related to the trustworthiness, grounding, instruct-ability, and alignment of Causal Neuro-symbolic AI systems.
4. Applications
Causal Discovery in Complex Environments: Strategies for discovering causal relationships in complex environments using neuro-symbolic AI.
Causal Neuro-symbolic AI in Use: Real-world applications of causal and neuro-symbolic AI methods in domains such as healthcare, finance, autonomous systems, natural language processing, etc
===========
Submissions
===========
We invite authors to submit unpublished original papers. Submitted papers should not have been previously published or accepted for publication in substantially similar form in any peer-reviewed venue, such as journals, conferences, or workshops.
More information is available at https://sites.google.com/view/causalnesy/==============
Important Dates
==============
Paper submission deadline: 6th March 2025
Author notification: 3rd April 2025
Camera-ready submission deadline: 17 April 2025
Workshop: June 1-2 2025
All deadlines must be considered at 23:59 AoE.===========
Useful Links
===========
Website: https://sites.google.com/view/causalnesy/
Submission: https://openreview.net/group?id=eswc-conferences.org/ESWC/2025/Workshop/Causal-NeSy#tab-your-consoles
Contact: ujai...@email.sc.edu
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