Tootfinder

"Hades", "Monument Valley": Netflix verliert einige seiner beste Spiele
Mehrere der besten Titel im bisherigen Netflix-Portfolio fliegen raus: Bald sind "Hades", "Katana Zero" und "Golden Idol" nicht mehr im Abo enthalten.

Data management software vendor Rubrik agrees to acquire Predibase, which helps with deploying AI models; source: Rubrik plans to pay between $100M and $500M (Jordan Novet/CNBC)
https://www.cnbc.com/2025/06/25/rubrik-agrees-to-bu…

Rubrik agrees to buy AI startup Predibase for over $100 million
Rubrik is seeking to bolster its artificial intelligence capabilities through acquisition.

EASE: Embodied Active Event Perception via Self-Supervised Energy Minimization
Zhou Chen, Sanjoy Kundu, Harsimran S. Baweja, Sathyanarayanan N. Aakur
https://arxiv.org/abs/2506.17516

EASE: Embodied Active Event Perception via Self-Supervised Energy Minimization
Active event perception, the ability to dynamically detect, track, and summarize events in real time, is essential for embodied intelligence in tasks such as human-AI collaboration, assistive robotics, and autonomous navigation. However, existing approaches often depend on predefined action spaces, annotated datasets, and extrinsic rewards, limiting their adaptability and scalability in dynamic, real-world scenarios. Inspired by cognitive theories of event perception and predictive coding, we p…

Your Token Becomes Worthless: Unveiling Rug Pull Schemes in Crypto Token via Code-and-Transaction Fusion Analysis
Hao Wu, Haijun Wang, Shangwang Li, Yin Wu, Ming Fan, Wuxia Jin, Yitao Zhao, Ting Liu
https://arxiv.org/abs/2506.18398

Your Token Becomes Worthless: Unveiling Rug Pull Schemes in Crypto Token via Code-and-Transaction Fusion Analysis
Rug pull scams have emerged as a persistent threat to cryptocurrency, causing significant financial losses. A typical scenario involves scammers deploying honeypot contracts to attract investments, restricting token sales, and draining the funds, which leaves investors with worthless tokens. Current methods either rely on predefined patterns to detect code risks or utilize statistical transaction data to train detection models. However, real-world Rug Pull schemes often involve a complex interp…

Flow-Aware Diffusion for Real-Time VR Restoration: Enhancing Spatiotemporal Coherence and Efficiency
Yitong Zhu, Guanxuan Jiang, Zhuowen Liang, Yuyang Wang
https://arxiv.org/abs/2506.18786

Flow-Aware Diffusion for Real-Time VR Restoration: Enhancing Spatiotemporal Coherence and Efficiency
Cybersickness remains a critical barrier to the widespread adoption of Virtual Reality (VR), particularly in scenarios involving intense or artificial motion cues. Among the key contributors is excessive optical flow-perceived visual motion that, when unmatched by vestibular input, leads to sensory conflict and discomfort. While previous efforts have explored geometric or hardware based mitigation strategies, such methods often rely on predefined scene structures, manual tuning, or intrusive eq…

🇺🇦 #NowPlaying on KEXP's #MorningShow
Pretty Bitter:
🎵 Outer Heaven Dude Ranch
#PrettyBitter
https://prettybitter.bandcamp.com/track/outer-heaven-dude-ranch
https://open.spotify.com/track/32S4UTJzF0XzYwkWApK2TL

ROBBO: An Efficient Method for Pareto Front Estimation with Guaranteed Accuracy
Roberto Boffadossi, Marco Leonesio, Lorenzo Fagiano
https://arxiv.org/abs/2506.18004

ROBBO: An Efficient Method for Pareto Front Estimation with Guaranteed Accuracy
A new method to estimate the Pareto Front (PF) in bi-objective optimization problems is presented. Assuming a continuous PF, the approach, named ROBBO (RObust and Balanced Bi-objective Optimization), needs to sample at most a finite, pre-computed number of PF points. Upon termination, it guarantees that the worst-case approximation error lies within a desired tolerance range, predefined by the decision maker, for each of the two objective functions. Theoretical results are derived, about the wo…

Efficient many-jet event generation with Flow Matching
Enrico Bothmann, Timo Jan{\ss}en, Max Knobbe, Bernhard Schmitzer, Fabian Sinz
https://arxiv.org/abs/2506.18987

Efficient many-jet event generation with Flow Matching
We apply for the first time the Flow Matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator Pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell--Yan and top--antitop…

A workflow for generating synthetic LiDAR datasets in simulation environments
Abhishek Phadke, Shakib Mahmud Dipto, Pratip Rana
https://arxiv.org/abs/2506.17378

A workflow for generating synthetic LiDAR datasets in simulation environments
This paper presents a simulation workflow for generating synthetic LiDAR datasets to support autonomous vehicle perception, robotics research, and sensor security analysis. Leveraging the CoppeliaSim simulation environment and its Python API, we integrate time-of-flight LiDAR, image sensors, and two dimensional scanners onto a simulated vehicle platform operating within an urban scenario. The workflow automates data capture, storage, and annotation across multiple formats (PCD, PLY, CSV), produ…

Wealthfront, which uses AI to build investment portfolios, confidentially files for a US IPO; it was valued at $1.4B in 2022 during a failed acquisition by UBS (Prakhar Srivastava/Reuters)
https://www.reuters.com/technology/wealthf