Tootfinder

Is #AI really just dumb statistics? "Olympiad-level physics problem-solving presents a significant challenge for both humans and artificial intelligence (AI), as it requires a sophisticated integration of precise calculation, abstract reasoning, and a fundamental grasp of physical principles," says the (abstract of the) paper https://arxiv.org/abs/2511.10515: "The Chinese Physics Olympiad (CPhO), renowned for its complexity and depth, serves as an ideal and rigorous testbed for these advanced capabilities. In this paper, we introduce LOCA-R (LOgical Chain Augmentation for Reasoning), an improved version of the LOCA framework adapted for complex reasoning, and apply it to the CPhO 2025 theory examination. LOCA-R achieves a near-perfect score of 313 out of 320 points, solidly surpassing the highest-scoring human competitor and significantly outperforming all baseline methods." Oops ...?

Development of Mental Models in Human-AI Collaboration: A Conceptual Framework
Joshua Holstein, Gerhard Satzger
https://arxiv.org/abs/2510.08104 https://ar…

Development of Mental Models in Human-AI Collaboration: A Conceptual Framework
Artificial intelligence has become integral to organizational decision-making and while research has explored many facets of this human-AI collaboration, the focus has mainly been on designing the AI agent(s) and the way the collaboration is set up - generally assuming a human decision-maker to be "fixed". However, it has largely been neglected that decision-makers' mental models evolve through their continuous interaction with AI systems. This paper addresses this gap by conceptualizing how th…

ARMimic: Learning Robotic Manipulation from Passive Human Demonstrations in Augmented Reality
Rohan Walia (Department of Computer Engineering, Munich Institute of Robotics and Machine Intelligence), Yusheng Wang (Department of Precision Engineering, Research into Artifacts, Center for Engineering), Ralf R\"omer (Department of Computer Engineering, Munich Institute of Robotics and Machine Intelligence), Masahiro Nishio (Toyota Motor Corporation, Japan), Angela P. Schoellig (Departm…

ARMimic: Learning Robotic Manipulation from Passive Human Demonstrations in Augmented Reality
Imitation learning is a powerful paradigm for robot skill acquisition, yet conventional demonstration methods--such as kinesthetic teaching and teleoperation--are cumbersome, hardware-heavy, and disruptive to workflows. Recently, passive observation using extended reality (XR) headsets has shown promise for egocentric demonstration collection, yet current approaches require additional hardware, complex calibration, or constrained recording conditions that limit scalability and usability. We pre…

Delay-Augmented Stacked Intelligent Surfaces: Potential, Challenges, and Opportunities
Hibatallah Alwazani, Omran Abbas, Loic Markley, Anas Chaaban
https://arxiv.org/abs/2510.01411

Delay-Augmented Stacked Intelligent Surfaces: Potential, Challenges, and Opportunities
Stacked intelligent surfaces (SIS)s have been proposed recently as an enabling technology for Holographic Multiple Input Multiple Output (HMIMO) and Ultra-massive MIMO (umMIMO) technologies. Their utility can extend beyond spatial wave-domain processing of signals if they are enhanced with strategically-tuned symbol-duration level delays to enable temporal processing as well. In this work, we introduce the idea of a delay-augmented SIS (DA-SIS). We shed light on the feasibility of realizing del…

"If George Boole is the 19th century’s AI scientist, then his contemporary machine learning engineers were Charles Babbage and Ada Lovelace. The Difference Engine, which would be frequently cited as the first example of a (mechanical) programmable digital computer if it had been built at the time, was explicitly designed to _replace_ rather than _augment_ human thought. Just as modern software engineering managers use Jira to avoid thinking about process engineering."

Douglas Hofstadter
You may be worried that I am going to talk about an author of books that are not about programming, and you are correct and incorrect. Correct, in that Hofstadter's books are not about programming (the intellectually hollow like to claim that they are not about anything at all, or that if you think you know what they are about then you did not understand them; this is untrue). Incorrect, in that Hofstadter's books and computer programs themselves are about the same thing.