Tootfinder

The Intrinsic Riemannian Proximal Gradient Method for Nonconvex Optimization
Ronny Bergmann, Hajg Jasa, Paula John, Max Pfeffer
https://arxiv.org/abs/2506.09775

The Intrinsic Riemannian Proximal Gradient Method for Nonconvex Optimization
We consider the proximal gradient method on Riemannian manifolds for functions that are possibly not geodesically convex. Starting from the forward-backward-splitting, we define an intrinsic variant of the proximal gradient method that uses proximal maps defined on the manifold and therefore does not require or work in the embedding. We investigate its convergence properties and illustrate its numerical performance, particularly for nonconvex or nonembedded problems that are hence out of reach …

PotentRegion4MalDetect: Advanced Features from Potential Malicious Regions for Malware Detection
Rama Krishna Koppanati, Monika Santra, Sateesh Kumar Peddoju
https://arxiv.org/abs/2507.06723

PotentRegion4MalDetect: Advanced Features from Potential Malicious Regions for Malware Detection
Malware developers exploit the fact that most detection models focus on the entire binary to extract the feature rather than on the regions of potential maliciousness. Therefore, they reverse engineer a benign binary and inject malicious code into it. This obfuscation technique circumvents the malware detection models and deceives the ML classifiers due to the prevalence of benign features compared to malicious features. However, extracting the features from the potential malicious regions enha…

Friends from English-speaking countries that say "zed" instead of "zee":
What is the last verse of the alphabet song?
The US version ends "now I know my A B Cs, next time won't you sing with me." Which therefore rhymes with "zee".
But it wouldn't rhyme with "zed". So what do you say instead? Or does it just not rhyme as well?

Found a case of party poppers and cap gun caps in the storage room from previous years' pranks.
Order of mousetraps, monofilament line, and metal stakes for securing tripwires should be here by the evening.
Let's see how these raccoons like what I have in store for them...

The Republican shell game on tax cuts
Republicans continue to profess deep concern about the federal debt -- even as their top priority is to pass a bill that will increase it by trillions of dollars.
They have multiple rationalizations for this behavior,
which might work psychologically but do not mathematically.

Thus they claim that the deficit reflects runaway spending rather than insufficient revenue
and that reducing that revenue is therefore nothing to w…

The Republican shell game on tax cuts
Expiring tax cuts are yesterday’s news for deficit scorekeepers, but an exciting new policy in campaign pitches.

Modeling Membrane Degradation in PEM Electrolyzers with Physics-Informed Neural Networks
Alejandro Polo-Molina, Jose Portela, Luis Alberto Herrero Rozas, Rom\'an Cicero Gonz\'alez
https://arxiv.org/abs/2507.02887

Modeling Membrane Degradation in PEM Electrolyzers with Physics-Informed Neural Networks
Proton exchange membrane (PEM) electrolyzers are pivotal for sustainable hydrogen production, yet their long-term performance is hindered by membrane degradation, which poses reliability and safety challenges. Therefore, accurate modeling of this degradation is essential for optimizing durability and performance. To address these concerns, traditional physics-based models have been developed, offering interpretability but requiring numerous parameters that are often difficult to measure and cal…

MultiGen: Using Multimodal Generation in Simulation to Learn Multimodal Policies in Real
Renhao Wang, Haoran Geng, Tingle Li, Feishi Wang, Gopala Anumanchipalli, Philipp Wu, Trevor Darrell, Boyi Li, Pieter Abbeel, Jitendra Malik, Alexei A. Efros
https://arxiv.org/abs/2507.02864

MultiGen: Using Multimodal Generation in Simulation to Learn Multimodal Policies in Real
Robots must integrate multiple sensory modalities to act effectively in the real world. Yet, learning such multimodal policies at scale remains challenging. Simulation offers a viable solution, but while vision has benefited from high-fidelity simulators, other modalities (e.g. sound) can be notoriously difficult to simulate. As a result, sim-to-real transfer has succeeded primarily in vision-based tasks, with multimodal transfer still largely unrealized. In this work, we tackle these challenge…

ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting
Daniel Wang, Patrick Rim, Tian Tian, Alex Wong, Ganesh Sundaramoorthi
https://arxiv.org/abs/2506.05480

ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting
We present ODE-GS, a novel method that unifies 3D Gaussian Splatting with latent neural ordinary differential equations (ODEs) to forecast dynamic 3D scenes far beyond the time span seen during training. Existing neural rendering systems - whether NeRF- or 3DGS-based - embed time directly in a deformation network and therefore excel at interpolation but collapse when asked to predict the future, where timestamps are strictly out-of-distribution. ODE-GS eliminates this dependency: after learning…

Explainer-guided Targeted Adversarial Attacks against Binary Code Similarity Detection Models
Mingjie Chen (Zhejiang University), Tiancheng Zhu (Huazhong University of Science,Technology), Mingxue Zhang (The State Key Laboratory of Blockchain,Data Security, Zhejiang University,Hangzhou High-Tech Zone), Yiling He (University College London), Minghao Lin (University of Southern California), Penghui Li (Columbia University), Kui Ren (The State Key Laboratory of Blockchain,Data Security, Z…

Explainer-guided Targeted Adversarial Attacks against Binary Code Similarity Detection Models
Binary code similarity detection (BCSD) serves as a fundamental technique for various software engineering tasks, e.g., vulnerability detection and classification. Attacks against such models have therefore drawn extensive attention, aiming at misleading the models to generate erroneous predictions. Prior works have explored various approaches to generating semantic-preserving variants, i.e., adversarial samples, to evaluate the robustness of the models against adversarial attacks. However, the…

TACS-Graphs: Traversability-Aware Consistent Scene Graphs for Ground Robot Indoor Localization and Mapping
Jeewon Kim, Minho Oh, Hyun Myung
https://arxiv.org/abs/2506.14178

TACS-Graphs: Traversability-Aware Consistent Scene Graphs for Ground Robot Indoor Localization and Mapping
Scene graphs have emerged as a powerful tool for robots, providing a structured representation of spatial and semantic relationships for advanced task planning. Despite their potential, conventional 3D indoor scene graphs face critical limitations, particularly under- and over-segmentation of room layers in structurally complex environments. Under-segmentation misclassifies non-traversable areas as part of a room, often in open spaces, while over-segmentation fragments a single room into overla…