Prépublication
· 2026 arXiv
EN
Significant efforts are currently being directed toward the implementation of large-scale quantum information processors, but realizing useful quantum advantage also requires the development of efficient quantum algorithms. While for many practical problems th...
Andi Gu, Alek H. Kemeny et al.
#quant-ph
Prépublication
· 2026 arXiv
EN
Predicting how the world responds to an action requires more than what can be seen: robots must account for environmental factors that are neither directly observable nor explicitly specified, from physical properties such as friction and mass to human-defined...
Chenyuan Zhou, Yining Hong et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Large language models (LLMs) are expanding from assisting scientific research and engineering to autonomously developing and improving AI systems, advancing AI for AI (AI4AI) as a pathway toward recursive self-improvement (RSI). Workflow-driven machine learnin...
Shangheng Du, Jinxin Shi et al.
#cs.AI
Prépublication
· 2026 arXiv
EN
How can robots autonomously collect the contact-rich experience needed to learn dexterous manipulation? We present DSP: Dexterity from supervised play, a framework in which a robot learns a play policy from minutes of human play through behavior cloning, then...
Botao He, Yiming Dou et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiously during safety evaluations than in real use. Existing work has studied evaluation awareness almost entire...
Trizal Garg, Sibayan Mitra et al.
#cs.AI
Prépublication
· 2026 arXiv
EN
Mutual coupling between elements of low-frequency arrays is a leading systematic for 21 cm cosmology, leaking bright foregrounds into otherwise clean regions of the power spectrum. Many mitigation models describe coupling as a linear combination of uncoupled s...
Vincent MacKay, Robert Pascua et al.
#astro-ph.IM
Prépublication
· 2026 arXiv
EN
Simulating chaotic planetary system evolution requires resolving small time-scales due to close encounters, scattering, collisions, and more. Simulations typically assign fixed timesteps to all particles, however, which is inefficient and wastes compute resour...
David M. Hernandez, Tenri Jinno et al.
#astro-ph.EP
Document numérisé
· 1506 Gallica (BnF)
FR
Document numérisé par la Bibliothèque nationale de France, publié en 1506. Thème : astronomie. Consultable en ligne sur Gallica.
Bibliothèque nationale de France
#Astronomie
Prépublication
· 2026 arXiv
EN
Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors in the real world. However, humanoid control networks are typically obtained through conventional training procedures, while comparatively l...
Huixuan Cheng, Bike Zhang et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Mobile Manipulation (MoMa) is a cornerstone of autonomous robotic systems, yet real-world fine-tuning remains a formidable challenge because of high-dimensional action spaces and intricate coupling between heterogeneous modules. In this paper, we propose HiRe-...
Zhefei Gong, Hefeifei Jiang et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Computer-use agents have demonstrated strong capabilities in interpreting screens and executing keyboard and mouse actions. However, games, with their visually rich worlds and diverse mechanics, remain challenging and offer a demanding next step toward general...
Mingyu Ouyang, Yiran Wang et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
Post-training binds the competence of an LLM agent to the interface it was trained on. Semantics-preserving perturbations of that interface, such as renaming an action or changing the notation, leave the underlying task unchanged yet make the agent worse at it...
Artin Tajdini, Manpreet Kaur et al.
#cs.LG