Tootfinder

The Yomiuri Shimbun, Japan's largest newspaper by circulation, sues Perplexity, alleging unauthorized reproduction of its articles, and seeks $14.7M in damages (Andrew Deck/Nieman Lab)
https://www.niemanlab.org/2025/08/japans-l

Japan’s largest newspaper, Yomiuri Shimbun, sues AI startup Perplexity for copyright violations
The Yomiuri Shimbun, Japan’s largest newspaper by circulation, has sued the generative AI startup Perplexity for copyright infringement. The lawsuit, filed in Tokyo District Court on August 7, marks the first copyright challenge by a major Japanese news publisher against an AI company. The fil…

The Yomiuri Shimbun, Japan's largest newspaper by circulation, sues Perplexity, alleging unauthorized reproduction of its articles, and seeks $14.7M in damages (Andrew Deck/Nieman Lab)
https://www.niemanlab.org/2025/08/japans-l

Japan’s largest newspaper, Yomiuri Shimbun, sues AI startup Perplexity for copyright violations
The Yomiuri Shimbun, Japan’s largest newspaper by circulation, has sued the generative AI startup Perplexity for copyright infringement. The lawsuit, filed in Tokyo District Court on August 7, marks the first copyright challenge by a major Japanese news publisher against an AI company. The fil…

Track Any Motions under Any Disturbances
Zhikai Zhang, Jun Guo, Chao Chen, Jilong Wang, Chenghuai Lin, Yunrui Lian, Han Xue, Zhenrong Wang, Maoqi Liu, Huaping Liu, He Wang, Li Yi
https://arxiv.org/abs/2509.13833

Track Any Motions under Any Disturbances
A foundational humanoid motion tracker is expected to be able to track diverse, highly dynamic, and contact-rich motions. More importantly, it needs to operate stably in real-world scenarios against various dynamics disturbances, including terrains, external forces, and physical property changes for general practical use. To achieve this goal, we propose Any2Track (Track Any motions under Any disturbances), a two-stage RL framework to track various motions under multiple disturbances in the rea…

Observation of Fully Flat Bands in a Photonic Dipolar Kagome Lattice
Han-Rong Xia, Ziyao Wang, Yunrui Wang, Zhen Gao, Meng Xiao
https://arxiv.org/abs/2509.12843 https://

Observation of Fully Flat Bands in a Photonic Dipolar Kagome Lattice
Flat bands, characterized by zero group velocity and strong energy localization, enable interaction-enhanced phenomena across both quantum and classical systems. Existing photonic flat-band implementations were limited to evanescent-wave systems, specific lattice symmetries, or complex supercell modulations. A simple, universal, and efficient approach to realizing flat bands without dedicated source excitation is to be explored. Here, inspired by geometrically frustrated configurations, we theo…

Fundamentami przy wyborze konsumenta są "cena, wygoda i moda". Jakiś odsetek zawsze zobaczy "głębiej" i podejmie świadome decyzje, ale reszta to kwestia marketingu, inżynierii społecznej i tych trzech składowych.

Mnie (jak piszemy o nielegalnych rzeczach, które na co dzień występują) np. prześladują telefony próbujące wyłudzić pieniądze z mojego konta bankowego albo sprzedać mi zapewne w ogóle nieistniejący produkt oraz jestem zalewany spamem mailowym z phishingiem i …

MoE-TTS: Enhancing Out-of-Domain Text Understanding for Description-based TTS via Mixture-of-Experts
Heyang Xue, Xuchen Song, Yu Tang, Jianyu Chen, Yanru Chen, Yang Li, Yahui Zhou
https://arxiv.org/abs/2508.11326

MoE-TTS: Enhancing Out-of-Domain Text Understanding for Description-based TTS via Mixture-of-Experts
Description-based text-to-speech (TTS) models exhibit strong performance on in-domain text descriptions, i.e., those encountered during training. However, in real-world applications, the diverse range of user-generated descriptions inevitably introduces numerous out-of-domain inputs that challenge the text understanding capabilities of these systems. To address this issue, we propose MoE-TTS, a description-based TTS model designed to enhance the understanding of out-of-domain text descriptions.…

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Dry Bread:
🎵 Yamar
#DryBread
https://eccentricsoul45s.bandcamp.com/track/yamar
https://open.spotify.com/track/0Rx9XoPyj5WmDa4EtppsAZ

DiTReducio: A Training-Free Acceleration for DiT-Based TTS via Progressive Calibration
Yanru Huo, Ziyue Jiang, Zuoli Tang, Qingyang Hong, Zhou Zhao
https://arxiv.org/abs/2509.09748

DiTReducio: A Training-Free Acceleration for DiT-Based TTS via Progressive Calibration
While Diffusion Transformers (DiT) have advanced non-autoregressive (NAR) speech synthesis, their high computational demands remain an limitation. Existing DiT-based text-to-speech (TTS) model acceleration approaches mainly focus on reducing sampling steps through distillation techniques, yet they remain constrained by training costs. We introduce DiTReducio, a training-free acceleration framework that compresses computations in DiT-based TTS models via progressive calibration. We propose two c…

GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines
Yumeng Fu, Jiayin Zhu, Lingling Zhang, Bo Zhao, Shaoxuan Ma, Yushun Zhang, Yanrui Wu, Wenjun Wu
https://arxiv.org/abs/2508.06226

GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines
Geometry problem solving (GPS) requires models to master diagram comprehension, logical reasoning, knowledge application, numerical computation, and auxiliary line construction. This presents a significant challenge for Multimodal Large Language Models (MLLMs). However, existing benchmarks for evaluating MLLM geometry skills overlook auxiliary line construction and lack fine-grained process evaluation, making them insufficient for assessing MLLMs' long-step reasoning abilities. To bridge these …