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Der Abendspaziergang wird immer schattiger ...
#spaziergang #winteriscoming

Beyond Distribution Shifts: Adaptive Hyperspectral Image Classification at Test Time
Xia Yue, Anfeng Liu, Ning Chen, Chenjia Huang, Hui Liu, Zhou Huang, Leyuan Fang
https://arxiv.org/abs/2509.08436

Beyond Distribution Shifts: Adaptive Hyperspectral Image Classification at Test Time
Hyperspectral image (HSI) classification models are highly sensitive to distribution shifts caused by various real-world degradations such as noise, blur, compression, and atmospheric effects. To address this challenge, we propose HyperTTA, a unified framework designed to enhance model robustness under diverse degradation conditions. Specifically, we first construct a multi-degradation hyperspectral dataset that systematically simulates nine representative types of degradations, providing a com…

Composable Score-based Graph Diffusion Model for Multi-Conditional Molecular Generation
Anjie Qiao, Zhen Wang, Chuan Chen, DeFu Lian, Enhong Chen
https://arxiv.org/abs/2509.09451

Composable Score-based Graph Diffusion Model for Multi-Conditional Molecular Generation
Controllable molecular graph generation is essential for material and drug discovery, where generated molecules must satisfy diverse property constraints. While recent advances in graph diffusion models have improved generation quality, their effectiveness in multi-conditional settings remains limited due to reliance on joint conditioning or continuous relaxations that compromise fidelity. To address these limitations, we propose Composable Score-based Graph Diffusion model (CSGD), the first mo…

At the Man vs. Machine hackathon, co-hosted by AI nonprofit METR to test if AI helps people code faster and better, the top prize went to an "AI-supported" team (Kylie Robison/Wired)
https://www.wired.com/story/san-francisco-hackathon-man-vs-machine/

Inside the Man vs. Machine Hackathon
At a weekend hackathon in San Francisco, more than 100 coders gathered to test whether they could beat AI—and win a $12,500 cash prize.

Cowboys, Bengals dubbed possible trade suitors for promising 26-year-old edge rusher https://www.sportingnews.com/us/nfl/dallas-cowboys/news/cowboys-bengals-trade-suitors-edge-rusher-jaelan-phillips/c7e0910c…

MoRoCo: Multi-operator-robot Coordination, Interaction and Exploration under Restricted Communication
Zhuoli Tian, Yuyang Zhang, Jinsheng Wei, Meng Guo
https://arxiv.org/abs/2508.07657

MoRoCo: Multi-operator-robot Coordination, Interaction and Exploration under Restricted Communication
Fleets of autonomous robots are increasingly deployed alongside multiple human operators to explore unknown environments, identify salient features, and perform complex tasks in scenarios such as subterranean exploration, reconnaissance, and search-and-rescue missions. In these contexts, communication is often severely limited to short-range exchanges via ad-hoc networks, posing challenges to coordination. While recent studies have addressed multi-robot exploration under communication constrain…

WarpPINN-fibers: improved cardiac strain estimation from cine-MR with physics-informed neural networks
Felipe \'Alvarez Barrientos, Tom\'as Banduc, Isabeau Sirven, Francisco Sahli Costabal
https://arxiv.org/abs/2509.08872

WarpPINN-fibers: improved cardiac strain estimation from cine-MR with physics-informed neural networks
The contractile motion of the heart is strongly determined by the distribution of the fibers that constitute cardiac tissue. Strain analysis informed with the orientation of fibers allows to describe several pathologies that are typically associated with impaired mechanics of the myocardium, such as cardiovascular disease. Several methods have been developed to estimate strain-derived metrics from traditional imaging techniques. However, the physical models underlying these methods do not inclu…

A few snaps from last week’s trip to Forrest, VIC, in the Otway ranges. Taken on a morning run. #running #straya

Triple-S: A Collaborative Multi-LLM Framework for Solving Long-Horizon Implicative Tasks in Robotics
Zixi Jia, Hongbin Gao, Fashe Li, Jiqiang Liu, Hexiao Li, Qinghua Liu
https://arxiv.org/abs/2508.07421

Triple-S: A Collaborative Multi-LLM Framework for Solving Long-Horizon Implicative Tasks in Robotics
Leveraging Large Language Models (LLMs) to write policy code for controlling robots has gained significant attention. However, in long-horizon implicative tasks, this approach often results in API parameter, comments and sequencing errors, leading to task failure. To address this problem, we propose a collaborative Triple-S framework that involves multiple LLMs. Through In-Context Learning, different LLMs assume specific roles in a closed-loop Simplification-Solution-Summary process, effectivel…