{"type":"ScholarlyArticle","title":"Neuro-Symbolic Artificial Intelligence: A Task-Directed Survey in the Black-Box Models Era","authors":[{"name":"Giovanni Pio Delvecchio","slug":"giovanni-pio-delvecchio","given":"Giovanni Pio","family":"Delvecchio","affiliation":""},{"name":"Lorenzo Molfetta","slug":"lorenzo-molfetta","given":"Lorenzo","family":"Molfetta","affiliation":""},{"name":"Gianluca Moro","slug":"gianluca-moro","given":"Gianluca","family":"Moro","affiliation":""}],"abstract":"The integration of symbolic computing with neural networks has intrigued researchers since the first theorizations of Artificial intelligence (AI). The ability of Neuro-Symbolic (NeSy) methods to infer or exploit behavioral schema has been widely considered as one of the possible proxies for human-level intelligence. However, the limited semantic generalizability and the challenges in declining complex domains with pre-defined patterns and rules hinder their practical implementation in real-world scenarios. The unprecedented results achieved by connectionist systems since the last AI breakthrough in 2017 have raised questions about the competitiveness of NeSy solutions, with particular emphasis on the Natural Language Processing and Computer Vision fields. This survey examines task-specific advancements in the NeSy domain to explore how incorporating symbolic systems can enhance explainability and reasoning capabilities. Our findings are meant to serve as a resource for researchers exploring explainable NeSy methodologies for real-life tasks and applications. Reproducibility details and in-depth comments on each surveyed research work are made available at https://github.com/disi-unibo-nlp/task-oriented-neuro-symbolic.git.","doi":"10.24963/ijcai.2025/1157","url":"https://ijcai.org/proceedings/2025/1157","pdf":"https://ijcai.org/proceedings/2025/1157.pdf","markdown":"https://ijcai.org/proceedings/2025/1157.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/1157","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Survey Track","track":"Survey Track","number":1157,"pages":{"first":10418,"last":10426},"keywords":["Machine Learning: ML: Neuro-symbolic methods","Natural Language Processing: NLP: Interpretability and analysis of models for NLP","Computer Vision: CV: Interpretability and transparency","Machine Learning: ML: Explainable/Interpretable machine learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}