Tootfinder

When are safety filters safe? On minimum phase conditions of control barrier functions
Jason J. Choi, Claire J. Tomlin, Shankar Sastry, Koushil Sreenath
https://arxiv.org/abs/2508.07684

When are safety filters safe? On minimum phase conditions of control barrier functions
In emerging control applications involving multiple and complex tasks, safety filters are gaining prominence as a modular approach to enforcing safety constraints. Among various methods, control barrier functions (CBFs) are widely used for designing safety filters due to their simplicity, imposing a single linear constraint on the control input at each state. In this work, we focus on the internal dynamics of systems governed by CBF-constrained control laws. Our key observation is that, althoug…

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment
Sarah Ball, Greg Gluch, Shafi Goldwasser, Frauke Kreuter, Omer Reingold, Guy N. Rothblum
https://arxiv.org/abs/2507.07341

On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment
With the increased deployment of large language models (LLMs), one concern is their potential misuse for generating harmful content. Our work studies the alignment challenge, with a focus on filters to prevent the generation of unsafe information. Two natural points of intervention are the filtering of the input prompt before it reaches the model, and filtering the output after generation. Our main results demonstrate computational challenges in filtering both prompts and outputs. First, we sho…

A Comprehensive Evaluation Framework for the Study of the Effects of Facial Filters on Face Recognition Accuracy
Kagan Ozturk, Louisa Conwill, Jacob Gutierrez, Kevin Bowyer, Walter J. Scheirer
https://arxiv.org/abs/2507.17729

A Comprehensive Evaluation Framework for the Study of the Effects of Facial Filters on Face Recognition Accuracy
Facial filters are now commonplace for social media users around the world. Previous work has demonstrated that facial filters can negatively impact automated face recognition performance. However, these studies focus on small numbers of hand-picked filters in particular styles. In order to more effectively incorporate the wide ranges of filters present on various social media applications, we introduce a framework that allows for larger-scale study of the impact of facial filters on automated …

Bessel beams, propagationally invariant beams, and axicons: An historical and tutorial review
Colin J. R. Sheppard
https://arxiv.org/abs/2509.06354 https://

Bessel beams, propagationally invariant beams, and axicons: An historical and tutorial review
The Bessel beam is discussed, including its historical development. We present the relationship with the Arago Spot, annular pupils, axicons and pupil filters. We also discuss Bessel-Gauss beams; higher order Bessel beams; electromagnetic polarization properties; waveguide and resonator modes; polychromatic and pulsed beams; one-dimensional Airy beams; extended depth of focus; and light sheets and photonic nanojets.

Newton-Flow Particle Filters based on Generalized Cram\'er Distance
Uwe D. Hanebeck
https://arxiv.org/abs/2509.00182 https://arxiv.org/pdf/2509.00182…

Newton-Flow Particle Filters based on Generalized Cramér Distance
We propose a recursive particle filter for high-dimensional problems that inherently never degenerates. The state estimate is represented by deterministic low-discrepancy particle sets. We focus on the measurement update step, where a likelihood function is used for representing the measurement and its uncertainty. This likelihood is progressively introduced into the filtering procedure by homotopy continuation over an artificial time. A generalized Cramér distance between particle sets is der…

JPS: Jailbreak Multimodal Large Language Models with Collaborative Visual Perturbation and Textual Steering
Renmiao Chen, Shiyao Cui, Xuancheng Huang, Chengwei Pan, Victor Shea-Jay Huang, QingLin Zhang, Xuan Ouyang, Zhexin Zhang, Hongning Wang, Minlie Huang
https://arxiv.org/abs/2508.05087

JPS: Jailbreak Multimodal Large Language Models with Collaborative Visual Perturbation and Textual Steering
Jailbreak attacks against multimodal large language Models (MLLMs) are a significant research focus. Current research predominantly focuses on maximizing attack success rate (ASR), often overlooking whether the generated responses actually fulfill the attacker's malicious intent. This oversight frequently leads to low-quality outputs that bypass safety filters but lack substantial harmful content. To address this gap, we propose JPS, \underline{J}ailbreak MLLMs with collaborative visual \underl…

A few more images from Huston-Brumbaugh woods today, playing with focus and light. Pulled out one of the old cheesy Starburst filters from my wedding photography days for the shot of the sunlight through the trees.
#photography #macrophotography

Urban Composition III 🫟
都市构图 III 🫟
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1995
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

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Stochastic Neural Control Barrier Functions
Hongchao Zhang, Manan Tayal, Jackson Cox, Pushpak Jagtap, Shishir Kolathaya, Andrew Clark
https://arxiv.org/abs/2506.21697

Stochastic Neural Control Barrier Functions
Control Barrier Functions (CBFs) are utilized to ensure the safety of control systems. CBFs act as safety filters in order to provide safety guarantees without compromising system performance. These safety guarantees rely on the construction of valid CBFs. Due to their complexity, CBFs can be represented by neural networks, known as neural CBFs (NCBFs). Existing works on the verification of the NCBF focus on the synthesis and verification of NCBFs in deterministic settings, leaving the stochast…

Efficient Sub-pixel Motion Compensation in Learned Video Codecs
Th\'eo Ladune, Thomas Leguay, Pierrick Philippe, Gordon Clare, F\'elix Henry
https://arxiv.org/abs/2507.21926

Efficient Sub-pixel Motion Compensation in Learned Video Codecs
Motion compensation is a key component of video codecs. Conventional codecs (HEVC and VVC) have carefully refined this coding step, with an important focus on sub-pixel motion compensation. On the other hand, learned codecs achieve sub-pixel motion compensation through simple bilinear filtering. This paper offers to improve learned codec motion compensation by drawing inspiration from conventional codecs. It is shown that the usage of more advanced interpolation filters, block-based motion info…