arXiv:2510. 14538v3 Announce Type: replace Abstract: Neuro-symbolic (NeSy) AI aims to develop deep neural networks whose predictions comply with prior knowledge encoding, e.
By Emanuele Marconato, Samuele Bortolotti, Emile van Krieken, Paolo Morettin, Elena Umili, Antonio Vergari, Efthymia Tsamoura, Andrea Passerini, Stefano Teso
arXiv:2407.09693v3 Announce Type: replace
Abstract: The field of Neural-Symbolic (NeSy) systems is growing rapidly. Proposed approaches show great promise in achieving symbiotic unions of neural and...
By Charles Dickens, Connor Pryor, Changyu Gao, Alon Albalak, Eriq Augustine, William Wang, Stephen Wright, Lise Getoor
arXiv:2610.01519v1 Announce Type: cross
Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural networks, ensuring that outputs satisfy specified...
By Samuele Bortolotti, Weixin Chen, Han Zhao, Andrea Passerini, Stefano Teso, Antonio Vergari
arXiv:2608. 10843v1 Announce Type: new Abstract: First-order concept synthesis asks a system to infer one formula that classifies labeled objects consistently across several finite relational structures.
By Serafim Batzoglou
arXiv:2608. 04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention.
By Agnese Chiatti, Michael Cochez, Cristina Cornelio, Sebastijan Dumancic, Artur d'Avila Garcez, Luis C. Lamb, Lia Morra, Mathias Niepert, Robert Peharz, Alberto Speranzon, Maarten Stol, Annette Ten Teije, Thiviyan Thanapalasingam, Frank Van Harmelen, Emile Van Krieken, Antonio Vergari, Benjie Wang
arXiv:2606. 19279v1 Announce Type: new Abstract: Neurosymbolic semantics is fragmented: classical, fuzzy, probabilistic and neural systems each define truth by their own inductive rules.
By Daniel Romero Schellhorn, Till Mossakowski, Bj\"orn Gehrke