Tootfinder

Interesting write-up of the history of Project Xanadu / the history of the Web before the Web
Included quite a few characterizations I wasn't at all aware of.
https://www.astralcodexten.com/p/your-review-project-xanadu-the-internet

Your Review: Project Xanadu - The Internet That Might Have Been
Finalist #12 in the Review Contest

Könnte jemand Ricarda Lang bitten, wenn sie schon bei Threads postet, ihren Kanal zu föderieren, so dass wir interagieren können?
(vielleicht @…)

Scientific Objectives of the Xue-shan-mu-chang 15-meter Submillimeter Telescope
XSMT Project Collaboration Group, Yiping Ao, Jin Chang, Zhiwei Chen, Xiangqun Cui, Kaiyi Du, Fujun Du, Yan Gong, Zhanwen Han, Gregory Herczeg, Luis C. Ho, Jie Hu, Yipeng Jing, Sihan Jiao, Binggang Ju, Jing Li, Xiaohu Li, Xiangdong Li, Lingrui Lin, Zhenhui Lin, Daizhong Liu, Dong Liu, Guoxi Liu, Zheng Lou, Dengrong Lu, Ruiqing Mao, Wei Miao, Yuan Qian, Keping Qiu, Zhiqiang Shen, Yong Shi, Shengcai Shi, Cheng…

Scientific Objectives of the Xue-shan-mu-chang 15-meter Submillimeter Telescope
Submillimeter astronomy is poised to revolutionize our understanding of the Universe by revealing cosmic phenomena hidden from optical and near-infrared observations, particularly those associated with interstellar dust, molecular gas, and star formation. The Xue-shan-mu-chang 15-meter submillimeter telescope (XSMT-15m), to be constructed at a premier high-altitude site (4813 m) in Qinghai, China, marks a major milestone for Chinese astronomy, establishing the China mainland's first independent…

TGPO: Tree-Guided Preference Optimization for Robust Web Agent Reinforcement Learning
Ziyuan Chen, Zhenghui Zhao, Zhangye Han, Miancan Liu, Xianhang Ye, Yiqing Li, Hongbo Min, Jinkui Ren, Xiantao Zhang, Guitao Cao
https://arxiv.org/abs/2509.14172

TGPO: Tree-Guided Preference Optimization for Robust Web Agent Reinforcement Learning
With the rapid advancement of large language models and vision-language models, employing large models as Web Agents has become essential for automated web interaction. However, training Web Agents with reinforcement learning faces critical challenges including credit assignment misallocation, prohibitively high annotation costs, and reward sparsity. To address these issues, we propose Tree-Guided Preference Optimization (TGPO), an offline reinforcement learning framework that proposes a tree-s…

Wan-Animate: Unified Character Animation and Replacement with Holistic Replication
Gang Cheng, Xin Gao, Li Hu, Siqi Hu, Mingyang Huang, Chaonan Ji, Ju Li, Dechao Meng, Jinwei Qi, Penchong Qiao, Zhen Shen, Yafei Song, Ke Sun, Linrui Tian, Feng Wang, Guangyuan Wang, Qi Wang, Zhongjian Wang, Jiayu Xiao, Sheng Xu, Bang Zhang, Peng Zhang, Xindi Zhang, Zhe Zhang, Jingren Zhou, Lian Zhuo

Wan-Animate: Unified Character Animation and Replacement with Holistic Replication
We introduce Wan-Animate, a unified framework for character animation and replacement. Given a character image and a reference video, Wan-Animate can animate the character by precisely replicating the expressions and movements of the character in the video to generate high-fidelity character videos. Alternatively, it can integrate the animated character into the reference video to replace the original character, replicating the scene's lighting and color tone to achieve seamless environmental i…

10:00 AM
The lessons for today:
- Compiling from FreeBSD ports for KDE 6.4.5 is too much
- Gentoo KDE testing doesn't update due to a spaghetti of dependencies
- Updated Tilers edition breaks the SDDM theme (and the margins in Hyprland are a mess)
- Xanmod kernel update on Trixie is held back
It's gonna be a long nuke-and-pave day.

Toronto-based quantum computing company Xanadu says it will go public in the US and Canada via a SPAC, in a deal that values the combined business at ~$3.6B (Josh Scott/BetaKit)
https://betakit.com/xanadu-to-go-public-on-nasdaq-and-tsx-in-3-6-billion-u…

Xanadu to go public on Nasdaq and TSX in $3.6-billion USD SPAC deal
Toronto-based quantum computing firm Xanadu has struck a deal to go public by merging with a SPAC called Crane Harbor Acquisition Corp.

TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
Jiawei Wang, Haowei Sun, Xintao Yan, Shuo Feng, Jun Gao, Henry X. Liu
https://arxiv.org/abs/2509.13164

TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
Safe and scalable deployment of end-to-end (E2E) autonomous driving requires extensive and diverse data, particularly safety-critical events. Existing data are mostly generated from simulators with a significant sim-to-real gap or collected from on-road testing that is costly and unsafe. This paper presents TeraSim-World, an automated pipeline that synthesizes realistic and geographically diverse safety-critical data for E2E autonomous driving at anywhere in the world. Starting from an arbitrar…

SURGIN: SURrogate-guided Generative INversion for subsurface multiphase flow with quantified uncertainty
Zhao Feng, Bicheng Yan, Luanxiao Zhao, Xianda Shen, Renyu Zhao, Wenhao Wang, Fengshou Zhang
https://arxiv.org/abs/2509.13189

SURGIN: SURrogate-guided Generative INversion for subsurface multiphase flow with quantified uncertainty
We present a direct inverse modeling method named SURGIN, a SURrogate-guided Generative INversion framework tailed for subsurface multiphase flow data assimilation. Unlike existing inversion methods that require adaptation for each new observational configuration, SURGIN features a zero-shot conditional generation capability, enabling real-time assimilation of unseen monitoring data without task-specific retraining. Specifically, SURGIN synergistically integrates a U-Net enhanced Fourier Neural…

Energy Efficiency Maximization for Movable Antenna-Enhanced MIMO Downlink System Based on S-CSI
Xintai Chen, Biqian Feng, Yongpeng Wu, Xiang-Gen Xia, Chengshan Xiao
https://arxiv.org/abs/2509.12036

Energy Efficiency Maximization for Movable Antenna-Enhanced MIMO Downlink System Based on S-CSI
This paper presents an innovative movable antenna (MA)-enhanced multi-user multiple-input multiple-output (MIMO) downlink system. We aim to maximize the energy efficiency (EE) under statistical channel state information (S-CSI) through a joint optimization of the precoding matrix and the antenna position vectors (APVs). To solve the resulting stochastic problem, we first resort to deterministic equivalent (DE) tecnology to formulate the deterministic minorizing function of the system EE and the…