Tootfinder

Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model
Yisen Gao, Jiaxin Bai, Yi Huang, Xingcheng Fu, Qingyun Sun, Yangqiu Song
https://arxiv.org/abs/2510.11462

Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model
Deductive and abductive reasoning are two critical paradigms for analyzing knowledge graphs, enabling applications from financial query answering to scientific discovery. Deductive reasoning on knowledge graphs usually involves retrieving entities that satisfy a complex logical query, while abductive reasoning generates plausible logical hypotheses from observations. Despite their clear synergistic potential, where deduction can validate hypotheses and abduction can uncover deeper logical patte…

#rijeka #croatia
https://ostblog.hypotheses.org/8288

#Windows zu #Linux von einem nicht-technichen Wissenschaftler

Por que é hora de colocar a ética e a humanidade no centro da educação em engenharia
#etica #filosofia

Por que é hora de colocar a ética e a humanidade no centro da educação em engenharia
Milad Haghani, Stephan Winter e Abbas Rajabifard HAGHANI, Milad; WINTER, Stephan; RAJABIFARD, Abbas. Por que é hora de colocar a ética e a humanidade no centro da educação em engenharia. (trad. Marcio Miotto e...

AI Agents as Universal Task Solvers
Alessandro Achille, Stefano Soatto
https://arxiv.org/abs/2510.12066 https://arxiv.org/pdf/2510.12066

AI Agents as Universal Task Solvers
AI reasoning agents are already able to solve a variety of tasks by deploying tools, simulating outcomes of multiple hypotheses and reflecting on them. In doing so, they perform computation, although not in the classical sense -- there is no program being executed. Still, if they perform computation, can AI agents be universal? Can chain-of-thought reasoning solve any computable task? How does an AI Agent learn to reason? Is it a matter of model size? Or training dataset size? In this work, w…