Generative AI is revolutionising our society by enabling innovative applications in art, language, healthcare, and more, fundamentally transforming the way we create, communicate, and solve complex problems. This sentence was indeed written by a large language model (LLM) – currently one of the most popular neural approaches that is trained to produce outputs through a sequence modelling objective. LLMs are trained to generate outputs that are statistically plausible, realistic, but not necessarily correct. As such, while the language models can generate fluent text and mimic humans on many tasks, trusting their reasoning is hindered by challenges such as coherence, consistency, and explainability.

Meanwhile, Symbolic AI provides sound and well-understood formal reasoning and explanation via knowledge representation that can be inspected to interpret how decisions are made from data, while lacking flexible generalisation to novel inputs. Neuro-Symbolic AI aims to build rich computational AI models, systems and applications by combining neural and symbolic learning and reasoning. It hopes to create synergies among the strengths of neural and symbolic AI while overcoming their complementary weaknesses.

The GeNeSy workshop aims at gathering researchers in Generative and Neuro-Symbolic AI to combine expertise, perspectives, and pioneering works to lay down the foundations for novel methods and paradigms for Generative Neuro-Symbolic AI. GeNeSy will feature novel and already published papers on NeSy methods for reasoning and explanations in multiple modalities, benchmarks and evaluation methods, challenges like commonsense reasoning and human-AI teaming, and reflection on ethical and social implications of GenAI. To the best of our knowledge, GeNeSy is the first workshop that brings ideas from NeSy and GenAI together, enabling discussions between these two communities and facilitating impact on the future development of AI.