Tootfinder

I’m rewriting my logic language code in Haskell because I got frustrated with Rust’s verbosity and having to deal with garbage collection. I didn’t feel like it was adding enough, and I started to rethink my reasoning for using Rust (so it can be embedded anywhere). I don’t know if this language is going anywhere, maybe it’s fine if I have to rewrite it once it’s popular. It may never be.

Ooh! From the Makers of Psychonauts...
▶️ Keeper: Double Fine’s Otherworldly Adventure, Arriving October 17  - Xbox Wire
https://news.xbox.com/en-us/2025/06/08/keeper-double-fine-xbox-games-showcase/

Double Fine’s Otherworldly Adventure, Arriving October 17  - Xbox Wire
Keeper is a third-person adventure filled with exploration, puzzle solving, and unexpected departures from reality, coming October 17, 2025.

WGLE:Backdoor-free and Multi-bit Black-box Watermarking for Graph Neural Networks
Tingzhi Li, Xuefeng Liu
https://arxiv.org/abs/2506.08602 https://

WGLE:Backdoor-free and Multi-bit Black-box Watermarking for Graph Neural Networks
Graph Neural Networks (GNNs) are increasingly deployed in graph-related applications, making ownership verification critical to protect their intellectual property against model theft. Fingerprinting and black-box watermarking are two main methods. However, the former relies on determining model similarity, which is computationally expensive and prone to ownership collisions after model post-processing such as model pruning or fine-tuning. The latter embeds backdoors, exposing watermarked model…

DEKC: Data-Enable Control for Tethered Space Robot Deployment in the Presence of Uncertainty via Koopman Operator Theory
Ao Jin, Qinyi Wang, Sijie Wen, Ya Liu, Ganghui Shen, Panfeng Huang, Fan Zhang
https://arxiv.org/abs/2506.08319

DEKC: Data-Enable Control for Tethered Space Robot Deployment in the Presence of Uncertainty via Koopman Operator Theory
This work focuses the deployment of tethered space robot in the presence of unknown uncertainty. A data-enable framework called DEKC which contains offline training part and online execution part is proposed to deploy tethered space robot in the presence of uncertainty. The main idea of this work is modeling the unknown uncertainty as a dynamical system, which enables high accuracy and convergence of capturing uncertainty. The core part of proposed framework is a proxy model of uncertainty, whi…

Pureformer-VC: Non-parallel Voice Conversion with Pure Stylized Transformer Blocks and Triplet Discriminative Training
Wenhan Yao, Fen Xiao, Xiarun Chen, Jia Liu, YongQiang He, Weiping Wen
https://arxiv.org/abs/2506.08348

Pureformer-VC: Non-parallel Voice Conversion with Pure Stylized Transformer Blocks and Triplet Discriminative Training
As a foundational technology for intelligent human-computer interaction, voice conversion (VC) seeks to transform speech from any source timbre into any target timbre. Traditional voice conversion methods based on Generative Adversarial Networks (GANs) encounter significant challenges in precisely encoding diverse speech elements and effectively synthesising these elements into natural-sounding converted speech. To overcome these limitations, we introduce Pureformer-VC, an encoder-decoder frame…

This https://arxiv.org/abs/2506.05673 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery
The development of modern Artificial Intelligence (AI) models, particularly diffusion-based models employed in computer vision and image generation tasks, is undergoing a paradigmatic shift in development methodologies. Traditionally dominated by a "Model Centric" approach, in which performance gains were primarily pursued through increasingly complex model architectures and hyperparameter optimization, the field is now recognizing a more nuanced "Data-Centric" approach. This emergent framework…

I've been having a lot of fun at Furality, but the best moments by far have been the ones I spent with friends. Sure, going crazy at the club and watching panels with strangers is also fun, but sharing these experiences with them really makes a difference :neofox_floof_happy:

So all in all, this seems like a pretty normal set of WWDC announcements. A nice cosmetic redesign, which will be fun to play around with; the rest are daily quality of life improvements, and the artificial intelligence stuff seems like modest incremental gains that seem realistic, and maybe even somewhat useful.
Not the pie in the sky bullshit that ended up never shipping last year.
#WWDC25

Falcons' Darnell Mooney fine with missing 1,000-yard receiving mark in 2024: 'I came here to win games' https://www.nfl.com/news/falcons-darnell-mooney-fine-with-missing-1-000-yard-receiving-mark-in…

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization
Zhican Wang, Guanghui He, Dantong Liu, Lingjun Gao, Shell Xu Hu, Chen Zhang, Zhuoran Song, Nicholas Lane, Wayne Luk, Hongxiang Fan
https://arxiv.org/abs/2506.07069

Accelerating 3D Gaussian Splatting with Neural Sorting and Axis-Oriented Rasterization
3D Gaussian Splatting (3DGS) has recently gained significant attention for high-quality and efficient view synthesis, making it widely adopted in fields such as AR/VR, robotics, and autonomous driving. Despite its impressive algorithmic performance, real-time rendering on resource-constrained devices remains a major challenge due to tight power and area budgets. This paper presents an architecture-algorithm co-design to address these inefficiencies. First, we reveal substantial redundancy cause…