Tootfinder

“Yikes”: Internal emails reveal Ticketmaster helped scalpers jack up prices, FTC says - Ars Technica https://share.google/ukrEc6jZFaKueb6N6

“Yikes”: Internal emails reveal Ticketmaster helped scalpers jack up prices, FTC says
FTC sued Ticketmaster and Live Nation for turning “blind eye” to scalpers.

Brian Schottenheimer: We Feed Off the Energy | Dallas Cowboys 2025 https://www.youtube.com/watch?v=yWHZ8U47ACw

Aligning Moments in Time using Video Queries
Yogesh Kumar, Uday Agarwal, Manish Gupta, Anand Mishra
https://arxiv.org/abs/2508.15439 https://arxiv.org/pdf/…

Aligning Moments in Time using Video Queries
Video-to-video moment retrieval (Vid2VidMR) is the task of localizing unseen events or moments in a target video using a query video. This task poses several challenges, such as the need for semantic frame-level alignment and modeling complex dependencies between query and target videos. To tackle this challenging problem, we introduce MATR (Moment Alignment TRansformer), a transformer-based model designed to capture semantic context as well as the temporal details necessary for precise moment …

Investigation of D-Wave quantum annealing for training Restricted Boltzmann Machines and mitigating catastrophic forgetting
Abdelmoula El-Yazizi, Yaroslav Koshka
https://arxiv.org/abs/2508.15697

Investigation of D-Wave quantum annealing for training Restricted Boltzmann Machines and mitigating catastrophic forgetting
Modest statistical differences between the sampling performances of the D-Wave quantum annealer (QA) and the classical Markov Chain Monte Carlo (MCMC), when applied to Restricted Boltzmann Machines (RBMs), are explored to explain, and possibly address, the absence of significant and consistent improvements in RBM trainability when the D-Wave sampling was used in previous investigations. A novel hybrid sampling approach, combining the classical and the QA contributions, is investigated as a prom…

🇺🇦 #NowPlaying on BBCRadio3's #NightTracks
Todd Baker:
🎵 Kora Lullaby
#ToddBaker
https://open.spotify.com/track/1ySKouj0avSMv9OU5wC5Gq

🇺🇦 #NowPlaying on KEXP's #SonicReducer
Ramones:
🎵 The Crusher
#Ramones
https://jrdnandtheswitchblades.bandcamp.com/track/the-crusher
https://open.spotify.com/track/1yWz1AZo5g18ZQXYuAVOqr

Masimo sues US CBP, saying CBP exceeded its authority in an Aug. 1 internal advice ruling that enabled Apple to reactivate a Watch blood oxygen tracking feature (Christopher Yasiejko/Bloomberg Law)
https://news.bloomberglaw.com/daily-la

Masimo Sues US Customs Over Apple Restoring Watch’s Oxygen Tool
US Customs and Border Protection unlawfully let Apple Inc. reactivate a blood-oxygen tracking feature on Apple Watches that infringes patents for the technology, Masimo Corp. said in a federal lawsuit.

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[1/6]:
- Action is the primary key: a categorical framework for episodic memories and logical reasoning
Yoshiki Fukada

ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation
Yiran Wu, Mauricio Velazco, Andrew Zhao, Manuel Ra\'ul Mel\'endez Luj\'an, Srisuma Movva, Yogesh K Roy, Quang Nguyen, Roberto Rodriguez, Qingyun Wu, Michael Albada, Julia Kiseleva, Anand Mudgerikar
https://arxiv.org/abs/2507.14201

ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation
We present ExCyTIn-Bench, the first benchmark to Evaluate an LLM agent x on the task of Cyber Threat Investigation through security questions derived from investigation graphs. Real-world security analysts must sift through a large number of heterogeneous alert signals and security logs, follow multi-hop chains of evidence, and compile an incident report. With the developments of LLMs, building LLM-based agents for automatic thread investigation is a promising direction. To assist the developme…

Transfer learning optimization based on evolutionary selective fine tuning
Jacinto Colan, Ana Davila, Yasuhisa Hasegawa
https://arxiv.org/abs/2508.15367 https://

Transfer learning optimization based on evolutionary selective fine tuning
Deep learning has shown substantial progress in image analysis. However, the computational demands of large, fully trained models remain a consideration. Transfer learning offers a strategy for adapting pre-trained models to new tasks. Traditional fine-tuning often involves updating all model parameters, which can potentially lead to overfitting and higher computational costs. This paper introduces BioTune, an evolutionary adaptive fine-tuning technique that selectively fine-tunes layers to enh…