Tootfinder

Multi-Loco: Unifying Multi-Embodiment Legged Locomotion via Reinforcement Learning Augmented Diffusion
Shunpeng Yang, Zhen Fu, Zhefeng Cao, Guo Junde, Patrick Wensing, Wei Zhang, Hua Chen
https://arxiv.org/abs/2506.11470

Multi-Loco: Unifying Multi-Embodiment Legged Locomotion via Reinforcement Learning Augmented Diffusion
Generalizing locomotion policies across diverse legged robots with varying morphologies is a key challenge due to differences in observation/action dimensions and system dynamics. In this work, we propose Multi-Loco, a novel unified framework combining a morphology-agnostic generative diffusion model with a lightweight residual policy optimized via reinforcement learning (RL). The diffusion model captures morphology-invariant locomotion patterns from diverse cross-embodiment datasets, improving…

On Universal Deformations of Compressible Cauchy Elastic Solids Reinforced by Inextensible Fibers
Arash Yavari
https://arxiv.org/abs/2506.11203 https://

On Universal Deformations of Compressible Cauchy Elastic Solids Reinforced by Inextensible Fibers
Universal deformations are those that can be maintained in the absence of body forces and by applying only boundary tractions, for all materials within a given constitutive class. We study the universal deformations of compressible isotropic Cauchy elastic solids reinforced by a single family of inextensible fibers. We consider straight fibers parallel to the Cartesian Z-axis in the reference configuration and derive the universality constraints. The principal invariants of the right Cauchy-Gre…

"Conspiracy thinking is also a trap because it contains feedback loops of positive reinforcement. If you reject authoritative sources of information as part of a conspiracy, then you will likely reject any information that can disprove the conspiracy. Any information that contradicts the conspiracy, or lack of information that would prove the conspiracy, are part of the conspiracy."

"The [Tesla] owners are demanding that their lease contracts be terminated and reimbursed for the accrued legal costs."
☑️ Tesla Drivers Sue Elon Musk for Turning Their Cars Into "Extreme" Right-Wing Symbols
https://futurism.com/the-byte/tesla-dr

Tesla Drivers Sue Elon Musk for Turning Their Cars Into "Extreme" Right-Wing Symbols
Tesla drivers in France are suing Elon Musk's EV maker for turning their vehicles into what they characterize as "extreme-right" symbols.

TongSearch-QR: Reinforced Query Reasoning for Retrieval
Xubo Qin, Jun Bai, Jiaqi Li, Zixia Jia, Zilong Zheng
https://arxiv.org/abs/2506.11603 https://

TongSearch-QR: Reinforced Query Reasoning for Retrieval
Traditional information retrieval (IR) methods excel at textual and semantic matching but struggle in reasoning-intensive retrieval tasks that require multi-hop inference or complex semantic understanding between queries and documents. One promising solution is to explicitly rewrite or augment queries using large language models (LLMs) to elicit reasoning-relevant content prior to retrieval. However, the widespread use of large-scale language models like GPT-4 or LLaMA3-70B remains impractical …

Nach einer Woche renovieren, möchte ich sagen: traut Euch an Lehm ran, sieht fantastisch aus auf Wänden und ist super fürs Raumklima. Konkret Z.B. Conluto Flächenspachtel, damit kann man sogar auf Dispersionsfarbe arbeiten. Neue Erkenntnis: Galerieschienen sind eine wirklich gute Erfindung.

Vane rheology of a fiber-reinforced granular material
Ladislas Wierzchalek, Georges Gauthier, Baptiste Darbois-Texier
https://arxiv.org/abs/2506.11762 http…

Vane rheology of a fiber-reinforced granular material
The addition of a small quantity of flexible fibers in a granular material is an efficient technique to increase the yield stress of the material. While the influence of fiber addition on the mechanical strength of granular media has been studied, much less is known about the flow properties of grain-fiber mixtures. In this article, we explore the effect of flexible fibers on the flow behavior of grain-fiber mixtures above the yield stress. We use a vane geometry to study the rheology of a dry …

Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning
Mohammadamin Moradi, Runyu Jiang, Yingzi Liu, Malvern Madondo, Tianming Wu, James J. Sohn, Xiaofeng Yang, Yasmin Hasan, Zhen Tian
https://arxiv.org/abs/2506.11957…

Automated Treatment Planning for Interstitial HDR Brachytherapy for Locally Advanced Cervical Cancer using Deep Reinforcement Learning
High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual treatment planning expertise. The objective of this study is to develop a fully automated HDR brachytherapy planning framework that integrates reinforcement learning (RL) and dose-based optimization to generate clinically acceptable treatment plans with improved consistency and efficiency. We propose a hierarchical two-stage autoplanning framework.…

Poutine: Vision-Language-Trajectory Pre-Training and Reinforcement Learning Post-Training Enable Robust End-to-End Autonomous Driving
Luke Rowe, Rodrigue de Schaetzen, Roger Girgis, Christopher Pal, Liam Paull
https://arxiv.org/abs/2506.11234

Poutine: Vision-Language-Trajectory Pre-Training and Reinforcement Learning Post-Training Enable Robust End-to-End Autonomous Driving
We present Poutine, a 3B-parameter vision-language model (VLM) tailored for end-to-end autonomous driving in long-tail driving scenarios. Poutine is trained in two stages. To obtain strong base driving capabilities, we train Poutine-Base in a self-supervised vision-language-trajectory (VLT) next-token prediction fashion on 83 hours of CoVLA nominal driving and 11 hours of Waymo long-tail driving. Accompanying language annotations are auto-generated with a 72B-parameter VLM. Poutine is obtained …

CIRO7.2: A Material Network with Circularity of -7.2 and Reinforcement-Learning-Controlled Robotic Disassembler
Federico Zocco, Monica Malvezzi
https://arxiv.org/abs/2506.11748

CIRO7.2: A Material Network with Circularity of -7.2 and Reinforcement-Learning-Controlled Robotic Disassembler
The competition over natural reserves of minerals is expected to increase in part because of the linear-economy paradigm based on take-make-dispose. Simultaneously, the linear economy considers end-of-use products as waste rather than as a resource, which results in large volumes of waste whose management remains an unsolved problem. Since a transition to a circular economy can mitigate these open issues, in this paper we begin by enhancing the notion of circularity based on compartmental dynam…