Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
Abstract (English) The historical evolution of Artificial Intelligence is approaching a crucial ontological turning point. Moving beyond the mere simulation of Euclidean physics and the computation of dead matter (PINNs) or purely statistical physical mimicry (Generative World Models), SINHRI introduces the Harmonic Intrinsic Alignment (HIA) and the Causal-Energetic Harmonic Manifold (CEHM). This paper defines a fundamental new taxonomy in intelligence research: SINNs (Syntropic-Informed Neural Networks) and the future culmination into SPINNs (Syntropic-Physics Informed Neural Networks). This marks the definitive paradigm shift from pure entropy-based mechanics to a meaning-resonant, intrinsically coherent, and ethically stable Artificial General Intelligence (AGI).
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations of such models.
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
Empirically, PRISM reduces the end-to-end time for data selection and model tuning to just 30% of conventional pipelines, and achieves this efficiency while simultaneously enhancing performance, surpassing models fine-tuned on the full dataset across eight multimodal and three language understanding benchmarks.
Jinhe Bi, Yifan Wang, Danqi Yan et al.· arXiv.org· 73 citations· ⚡4
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
This paper designs Markov decision processes (MDPs) for different combinatorial problems and proposes to train conditional GFlowNets to sample from the solution space and demonstrates that GFlowNet policies can efficiently find high-quality solutions.
Dinghuai Zhang, H. Dai, Esmeralda S. Whitammer et al.· Advances in Neural Informati...· 59 citations· ⚡8
An empirical study on the current state of practice in artificial intelligence ethics is conducted by means of a multiple case study of five case companies, which indicates a gap between research and practice in the area.
Ville Vakkuri, Kai-Kristian Kemell, Joni Kultanen et al.· arXiv.org· 56 citations· ⚡6
