Tootfinder

Calgary-based GeologicAI, which uses AI and sensors to help capture data in rock and core samples faster, raised a $44M Series B led by Blue Earth Capital (Alex Riehl/BetaKit)
https://betakit.com/geologicai-cashes-in-on-data-centre-boom-with-60-5-…

GeologicAI cashes in on data centre boom with $60.5-million CAD Series B
Mining tech startup will use funding to scale globally as demand for critical minerals intensifies.

Human Motion Capture from Loose and Sparse Inertial Sensors with Garment-aware Diffusion Models
Andela Ilic, Jiaxi Jiang, Paul Streli, Xintong Liu, Christian Holz
https://arxiv.org/abs/2506.15290

Human Motion Capture from Loose and Sparse Inertial Sensors with Garment-aware Diffusion Models
Motion capture using sparse inertial sensors has shown great promise due to its portability and lack of occlusion issues compared to camera-based tracking. Existing approaches typically assume that IMU sensors are tightly attached to the human body. However, this assumption often does not hold in real-world scenarios. In this paper, we present a new task of full-body human pose estimation using sparse, loosely attached IMU sensors. To solve this task, we simulate IMU recordings from an existing…

Ukraine raises flags in villages near Dnipropetrovsk Oblast's borders, refuting Russia's claims of capture: https://benborges.xyz/2025/07/18/ukraine-raises-flags-in-villages.html

AI summaries of meetings always read a bit like meeting minutes that say "Executive Session" when what actually happened was an off the record discussion that was nearly met with fisticuffs. Like it's not _wrong_ but it doesn't usually capture the sentiment.

Mollissez pas, je compte bien faire une capture d'écran au passage du million. #DuplombDansLAile

SiriusXM launches SiriusXM Play, its first ad-supported subscription plan, currently available on a limited basis for less than $7 per month (Lillian Rizzo/CNBC)
https://www.cnbc.com/2025/07/15/sirius-bets-on-advertising-to-capture-new-listeners.html

Sirius, long commercial-free in cars, is betting on advertising to capture new listeners
SiriusXM, long known as a commercial-free satellite option for car radios, is betting an ad-supported option can boost its business.

Pour écrire en français, j’apprécierais bien un peu de l’aide de l’autocorrection.
L’autocorrection:

MoCap2GT: A High-Precision Ground Truth Estimator for SLAM Benchmarking Based on Motion Capture and IMU Fusion
Zichao Shu, Shitao Bei, Jicheng Dai, Lijun Li, Zetao Chen
https://arxiv.org/abs/2507.12920

MoCap2GT: A High-Precision Ground Truth Estimator for SLAM Benchmarking Based on Motion Capture and IMU Fusion
Marker-based optical motion capture (MoCap) systems are widely used to provide ground truth (GT) trajectories for benchmarking SLAM algorithms. However, the accuracy of MoCap-based GT trajectories is mainly affected by two factors: spatiotemporal calibration errors between the MoCap system and the device under test (DUT), and inherent MoCap jitter. Consequently, existing benchmarks focus primarily on absolute translation error, as accurate assessment of rotation and inter-frame errors remains c…

"How Apple Created a Custom iPhone Camera for F1
Mounted on Formula One cars and used at real events, the special module used an iPhone camera sensor and A-series chip to help capture the new movie's racing scenes."
via @…

First-passage time to capture for diffusion in a 3D harmonic potential
Tianyu Yuan, Ivan Surovtsev, Megan C. King, Simon G. J. Mochrie
https://arxiv.org/abs/2506.14658

First-passage time to capture for diffusion in a 3D harmonic potential
We determine the survival probability and first-passage time (FPT) to capture for a harmonically trapped particle, diffusing outside an absorbing spherical boundary by directly solving the differential equation for the survival probability. This solution, obtained as an infinite sum over the relevant eigenfunctions, corrects previously published results [D. S. Grebenkov, J. Phys. A 48, 013001 (2014)]. To verify our calculations, we perform simulations of the survival probability, that accuratel…

#Windows11's new #StickyNotes app (a thinly disguised #OneNote) is fucking annoying. Since it is so-called "smart", and it attempts to provide context around the "source" of your note, its window is…

Backed by #Japan, governments across #Southeast Asia are turning to #carbon capture and sequestration (#CCS) to hit their

Protect your privacy – Start now with Signal
 
Autocracies always implement broad surveillance methods in order to identify and punish resistance. Surveillance can take many forms including the capture of your social media posts and email, monitoring your connections to web sites, and preventing the use of private communications through encryption back-doors and other means.
 
Take action now to create ways to communicate privately with your family, friends and colleague…

I find it funny that Gap's retail brands capture the US so well: Old Navy, Banana Republic, Gap...

Ukrainian forces 'steadfastly' holding defenses near Pokrovsk, commander-in-chief says: https://benborges.xyz/2025/07/18/ukrainian-forces-steadfastly-holding-defenses.html

Fractal dimensions of complex networks: advocating for a topological approach
Rayna Andreeva, Hayde\'e Contreras-Peruyero, Sanjukta Krishnagopal, Nina Otter, Maria Antonietta Pascali, Elizabeth Thompson
https://arxiv.org/abs/2506.15236

Fractal dimensions of complex networks: advocating for a topological approach
Topological Data Analysis (TDA) uses insights from topology to create representations of data able to capture global and local geometric and topological properties. Its methods have successfully been used to develop estimations of fractal dimensions for metric spaces that have been shown to outperform existing techniques. In a parallel line of work, networks are ubiquitously used to model a variety of complex systems. Higher-order interactions, i.e., simultaneous interactions between more than …

A generalised discrete mixture model to better capture preference heterogeneity in discrete choice data
Thomas O. Hancock, John Buckell
https://arxiv.org/abs/2506.14094

A generalised discrete mixture model to better capture preference heterogeneity in discrete choice data
Arguably the key issue in modelling discrete choice data is capturing preference heterogeneity. This can be through observed characteristics, and/or using techniques for capturing random heterogeneity across respondents. On the latter, in health economics, the two main approaches are the mixed multinomial logit (MMNL) and the latent class (LC) model. In this paper, we revisit the discrete mixture (DM) model as a third alternative to these. The DM model is similar to LC but allows for any combin…

Recursive Variational Autoencoders for 3D Blood Vessel Generative Modeling
Paula Feldman, Miguel Fainstein, Viviana Siless, Claudio Delrieux, Emmanuel Iarussi
https://arxiv.org/abs/2506.14914

Recursive Variational Autoencoders for 3D Blood Vessel Generative Modeling
Anatomical trees play an important role in clinical diagnosis and treatment planning. Yet, accurately representing these structures poses significant challenges owing to their intricate and varied topology and geometry. Most existing methods to synthesize vasculature are rule based, and despite providing some degree of control and variation in the structures produced, they fail to capture the diversity and complexity of actual anatomical data. We developed a Recursive variational Neural Network…

Adaptive feature capture method for solving partial differential equations with low regularity solutions
Yangtao Deng, Qiaolin He, Xiaoping Wang
https://arxiv.org/abs/2507.12941

Adaptive feature capture method for solving partial differential equations with low regularity solutions
Partial differential equations (PDEs) with low-regularity solutions pose significant challenges for traditional numerical methods, particularly in complex geometries where mesh generation and adaptive refinement become computationally expensive. While deep-learning-based approaches, such as Physics-Informed Neural Networks (PINNs) and the Random Feature Method (RFM), offer mesh-free alternatives, they often lack adaptive resolution in critical regions, limiting their accuracy for solutions with…

Beyond ensemble averaging: Parallelized single-shot readout of hole capture in diamond
Richard Monge, Yuki Nakamura, Olaf Bach, Jason Shao, Artur Lozovoi, Alexander A. Wood, Kento Sasaki, Kensuke Kobayashi, Tom Delord, Carlos A. Meriles
https://arxiv.org/abs/2507.11722

Beyond ensemble averaging: Parallelized single-shot readout of hole capture in diamond
Understanding the generation, transport and capture of charge carriers in semiconductors is of fundamental technological importance. However, the ensemble measurement techniques ubiquitous in electronics offer limited insight into the nanoscale environment that is crucial to the operation of modern quantum-electronic devices. Here, we combine widefield optical microscopy with precision spectroscopy to examine the capture of photogenerated holes by negatively charged nitrogen vacancy (NV-) cente…

Metasurfaces-Integrated Doubly-Dispersive MIMO: Channel Modeling and Optimization
Kuranage Roche Rayan Ranasinghe, Hyeon Seok Rou, Iv\'an Alexander Morales Sandoval, Giuseppe Thadeu Freitas de Abreu, George C. Alexandropoulos
https://arxiv.org/abs/2506.14985

Metasurfaces-Integrated Doubly-Dispersive MIMO: Channel Modeling and Optimization
The doubly-dispersive (DD) channel structure has played a pivotal role in wireless communications, particularly in high-mobility scenarios and integrated sensing and communications (ISAC), due to its ability to capture the key fading effects experienced by a transmitted signal as it propagates through a dynamic medium. However, extending the DD framework to multiple-input multiple-output (MIMO) systems, especially in environments artificially enhanced by reconfigurable intelligent surfaces (RIS…

Reassessing the gallium anomaly using exact electron wave functions
M. Cadeddu, N. Cargioli, G. Carotenuto, F. Dordei, L. Ferro, C. Giunti
https://arxiv.org/abs/2507.13103

Reassessing the gallium anomaly using exact electron wave functions
The gallium anomaly, a persistent discrepancy exceeding $4σ$ in the $^{71}$Ga neutrino capture rates from $^{51}$Cr and $^{37}$Ar calibration sources by the GALLEX, SAGE, and recently BEST experiments, has challenged particle physics and nuclear theory for over three decades. We present a new calculation for the neutrino capture cross-section, abandoning the conventional leading-order approximation for electronic wave functions by numerically solving the Dirac-Coulomb equation for both bound a…

Gamma rays as a signature of r-process producing supernovae: remnants and future Galactic explosions
Zhenghai Liu, Evan Grohs, Kelsey A. Lund, G. C. McLaughlin, M. Reichert, Ian U. Roederer, Rebecca Surman, Xilu Wang
https://arxiv.org/abs/2506.14991

Gamma rays as a signature of r-process producing supernovae: remnants and future Galactic explosions
We consider the question of whether core-collapse supernovae (CCSNe) can produce rapid neutron capture process (r-process) elements and how future MeV gamma-ray observations could address this. Rare types of CCSNe characterized by substantial magnetic fields and rotation, known as magnetorotational supernovae (MR-SNe), are theoretically predicted to produce these elements, although direct observational evidence is lacking. We suggest that this critical question be addressed through the study of…

SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning
Anuradha Chopra, Abhinaba Roy, Dorien Herremans
https://arxiv.org/abs/2506.15154 http…

SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning
Detailed captions that accurately reflect the characteristics of a music piece can enrich music databases and drive forward research in music AI. This paper introduces a multi-task music captioning model, SonicVerse, that integrates caption generation with auxiliary music feature detection tasks such as key detection, vocals detection, and more, so as to directly capture both low-level acoustic details as well as high-level musical attributes. The key contribution is a projection-based architec…

Gravitational waves from b-EMRIs: Doppler shift and beaming, resonant excitation, helicity oscillations and self-lensing
Jo\~ao S. Santos, Vitor Cardoso, Jos\'e Nat\'ario, Maarten van de Meent
https://arxiv.org/abs/2506.14868

Gravitational waves from b-EMRIs: Doppler shift and beaming, resonant excitation, helicity oscillations and self-lensing
We study gravitational waves from a stellar-mass binary orbiting a spinning supermassive black hole, a system referred to as a binary extreme mass ratio inspiral (b-EMRI). We use Dixon's formalism to describe the stellar-mass binary as a particle with internal structure, and keep terms up to quadrupole order to capture the generation of gravitational waves by the inner motion of the stellar-mass binary. The problem of emission and propagation of waves is treated from first principles using blac…

EqualMotion: Accessible Motion Capture for the Creative Industries
Clarice Hilton, Kat Hawkins, Phill Tew, Freddie Collins, Seb Madgwick, Dominic Potts, Tom Mitchell
https://arxiv.org/abs/2507.08744

EqualMotion: Accessible Motion Capture for the Creative Industries
Motion capture technologies are increasingly used in creative and performance contexts but often exclude disabled practitioners due to normative assumptions in body modeling, calibration, and avatar representation. EqualMotion introduces a body-agnostic, wearable motion capture system designed through a disability-centred co-design approach. By enabling personalised calibration, integrating mobility aids, and adopting an inclusive visual language, EqualMotion supports diverse body types and mov…

Slip flows of a Bingham fluid in curved channels
S. J. Cox, S. M. Taghavi
https://arxiv.org/abs/2506.15303 https://arxiv.org/pdf/2506…

Slip flows of a Bingham fluid in curved channels
Motivated by the treatment of varicose veins with aqueous foams, we determine the velocity profiles and yield surface positions for pressure-driven flows of a Bingham fluid in curved channels, incorporating Navier wall slip to capture the slip behavior of aqueous foams. Assuming a constant pressure gradient -- consistent with syringe-driven injection in sclerotherapy -- we reproduce a closed-form analytic solution for the flow in a straight channel, and extend this to a uniformly curved channel…

Enhancing the prediction of publications' long-term impact using early citations, readerships, and non-scientific factors
Giovanni Abramo, Tindaro Cicero, Ciriaco Andrea D'Angelo
https://arxiv.org/abs/2506.15040

Enhancing the prediction of publications' long-term impact using early citations, readerships, and non-scientific factors
This study aims to improve the accuracy of long-term citation impact prediction by integrating early citation counts, Mendeley readership, and various non-scientific factors, such as journal impact factor, authorship and reference list characteristics, funding and open-access status. Traditional citation-based models often fall short by relying solely on early citations, which may not capture broader indicators of a publication's potential influence. By incorporating non-scientific predictors, …

Scientists Capture Sharpest Images Ever of Sun's Corona | PetaPixel https://petapixel.com/2025/05/30/scientists-capture-sharpest-images-ever-of-suns-corona/
There's video in there you might want to full-screen.

Scientists Capture Sharpest Images Ever of Sun's Corona
You've never seen the Sun like this.

Astronomers capture the birth of planets around a baby sun outside our solar system (Marcia Dunn/Associated Press)
https://apnews.com/article/solar-system-planet-formation-e668251436f90af0fc9462e208550187
http://www.memeorandum.com/250716/p178#a250716p178

Optical Control of Fluorescence Spatial Hole Burning Effect in Monolayer WS2
Yichun Pan, Liqing Zhu, Zheng Wang, Weihang Zhou
https://arxiv.org/abs/2506.15287

Optical Control of Fluorescence Spatial Hole Burning Effect in Monolayer WS2
Doping plays a crucial role in both electrical and optical properties of semiconductors. In this work, we report observation, as well as optical control, of fluorescence spatial hole burning effect in monolayer WS2. We demonstrate that the pronounced exciton-exciton annihilation process, in combination with the efficient capture of holes by intrinsic sulfur vacancy defects, induces significant photo-doping effect and eventually leads to fluorescence spatial hole burning. By means of a dual-beam…

FocalClick-XL: Towards Unified and High-quality Interactive Segmentation
Xi Chen, Hengshuang Zhao
https://arxiv.org/abs/2506.14686 https://

FocalClick-XL: Towards Unified and High-quality Interactive Segmentation
Interactive segmentation enables users to extract binary masks of target objects through simple interactions such as clicks, scribbles, and boxes. However, existing methods often support only limited interaction forms and struggle to capture fine details. In this paper, we revisit the classical coarse-to-fine design of FocalClick and introduce significant extensions. Inspired by its multi-stage strategy, we propose a novel pipeline, FocalClick-XL, to address these challenges simultaneously. Fol…

"Carbon Capture ‘Not Going to Happen,’ Top Fossil Fuel Advocate Predicts"
#CarbonCapture #Emissions #Climate

Carbon Capture ‘Not Going to Happen,’ Top Fossil Fuel Advocate Predicts
In audio obtained by DeSmog, Bjorn Lomborg told a Fraser Institute event in Vancouver that the technology is way too expensive to be viable.

A Logic For Fresh Labelled Transition Systems
Mohamed H Bandukara, Nikos Tzevelekos
https://arxiv.org/abs/2506.14538 https://arxiv.or…

A Logic For Fresh Labelled Transition Systems
We introduce a Hennessy-Milner logic with recursion for Fresh Labelled Transition Systems (FLTSs). These are nominal labelled transition systems which keep track of the history, i.e. of data values seen so far, and can capture fresh data generation. In particular, FLTSs generalise the computations of Fresh-Register Automata, which in turn are one of the simplest classes of history-dependent automata operating on infinite input alphabets. Each automaton comes equipped with a finite set of regist…

GEMMAS: Graph-based Evaluation Metrics for Multi Agent Systems
Jisoo Lee, Raeyoung Chang, Dongwook Kwon, Harmanpreet Singh, Nikhil Verma
https://arxiv.org/abs/2507.13190

GEMMAS: Graph-based Evaluation Metrics for Multi Agent Systems
Multi-agent systems built on language models have shown strong performance on collaborative reasoning tasks. However, existing evaluations focus only on the correctness of the final output, overlooking how inefficient communication and poor coordination contribute to redundant reasoning and higher computational costs. We introduce GEMMAS, a graph-based evaluation framework that analyzes the internal collaboration process by modeling agent interactions as a directed acyclic graph. To capture col…

This https://arxiv.org/abs/2502.06830 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Prediction
Accurate and reliable probabilistic prediction of intraday electricity prices is essential to manage market uncertainties and support robust trading strategies. However, current methods rely heavily on domain feature extraction and fail to capture the dynamics between buy and sell orders, limiting the ability to form rich representations of the orderbook. Furthermore, these methods often require training separate models for different quantiles and introduce additional procedures-such as post-ho…

The Economic Value of Depth
Pedro Afonso Fernandes
https://arxiv.org/abs/2506.15354 https://arxiv.org/pdf/2506.15354

The Economic Value of Depth
The main goal of this article is to introduce an economic perspective in the social logic of space. Firstly, we describe the economic model of a linear city to show how depth can generate value by creating local monopolies in less integrated spaces. Then, a new syntactic measure, the d-value, is proposed to capture the relation between the depth of some space from outside and the mean depth of all spaces from outside. An application to a public housing estate suggests that economic activities a…

Haha, Gmail has gotten dumber
I ordered a pizza (for takeout !)
and Gmail offered to "track your packages"

from my link log —
Lambda calculus cooked N ways: Benchmarks for capture-avoiding substitution.
https://github.com/sweirich/lambda-n-ways
saved 2025-06-14

GitHub - sweirich/lambda-n-ways: Benchmarks for capture-avoiding substitution
Benchmarks for capture-avoiding substitution. Contribute to sweirich/lambda-n-ways development by creating an account on GitHub.

🫨 Scientists capture slow-motion earthquake in action
#earth

Scientists capture slow-motion earthquake in action
Scientists for the first time have detected a slow slip earthquake in motion during the act of releasing tectonic pressure on a major fault zone at the bottom of the ocean.

"At the end of the day - who cares what you choose. Just choose something. Stop looking at it as 'blogging' or trying to 'capture an audience'."
Great piece by @… from a few years back on the importance of brain dumps and blogging:

Biles, SGA, Eagles capture top honors at ESPYS https://www.espn.com/espn/story/_/id/45759152/biles-gilgeous-alexander-eagles-win-top-honors-2025-espys

Bridging the Gap: Leveraging Retrieval-Augmented Generation to Better Understand Public Concerns about Vaccines
Muhammad Javed, Sedigh Khademi Habibabadi, Christopher Palmer, Hazel Clothier, Jim Buttery, Gerardo Luis Dimaguila
https://arxiv.org/abs/2507.12840

Bridging the Gap: Leveraging Retrieval-Augmented Generation to Better Understand Public Concerns about Vaccines
Vaccine hesitancy threatens public health, leading to delayed or rejected vaccines. Social media is a vital source for understanding public concerns, and traditional methods like topic modelling often struggle to capture nuanced opinions. Though trained for query answering, large Language Models (LLMs) often miss current events and community concerns. Additionally, hallucinations in LLMs can compromise public health communication. To address these limitations, we developed a tool (VaxPulse Quer…

Rel-HNN: Split Parallel Hypergraph Neural Network for Learning on Relational Databases
Md. Tanvir Alam, Md. Ahasanul Alam, Md Mahmudur Rahman, Md. Mosaddek Khan
https://arxiv.org/abs/2507.12562

Rel-HNN: Split Parallel Hypergraph Neural Network for Learning on Relational Databases
Relational databases (RDBs) are ubiquitous in enterprise and real-world applications. Flattening the database poses challenges for deep learning models that rely on fixed-size input representations to capture relational semantics from the structured nature of relational data. Graph neural networks (GNNs) have been proposed to address this, but they often oversimplify relational structures by modeling all the tuples as monolithic nodes and ignoring intra-tuple associations. In this work, we prop…

There is little about Scott Jennings,
or the words that come out of his mouth,
that corresponds to reality.
A decade into Trump’s capture of the Republican Party, Jennings is the premier crossover enabler.
He is perhaps CNN’s most recognizable face alongside its primetime anchors,
and he is feted on jokey, tough-talk shows like Bill Maher. 
But Jennings is a representation of our own malady,
a projection of a country whose political culture is now…

Scott Jennings in the Hyperreal and the Myth of the Escape Hatch
Jennings is like a simulation of a Trump enabler.

scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data
Ping Xu, Zhiyuan Ning, Pengjiang Li, Wenhao Liu, Pengyang Wang, Jiaxu Cui, Yuanchun Zhou, Pengfei Wang
https://arxiv.org/abs/2505.12626

scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data
Single-cell RNA sequencing (scRNA-seq) reveals cell heterogeneity, with cell clustering playing a key role in identifying cell types and marker genes. Recent advances, especially graph neural networks (GNNs)-based methods, have significantly improved clustering performance. However, the analysis of scRNA-seq data remains challenging due to noise, sparsity, and high dimensionality. Compounding these challenges, GNNs often suffer from over-smoothing, limiting their ability to capture complex biol…

Since I have found that installing #linux has become easier and easier the last few years, I decided to conduct an experiment. I gave my 10 year old daughter a usb stick and had her install it on a Dell laptop from 2011.
I recorded the whole thing (recorded her on my phone while a capture card recorded her screen). And for the most part, it went well. There was an issue about the corre…

{purrr} has some lesser known functions that make handling of failing function calls easier: safely, quietly, possibly: #rstats…

Wrap a function to capture errors — safely
Creates a modified version of .f that always succeeds. It returns a list with components result and error. If the function succeeds, result contains the returned value and error is NULL. If an error occurred, error is an error object and result is either NULL or otherwise.

movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps

Energy-consistent dynamic fracture phase field models: unilateral constraints and finite element simulations
Md Mamun Miah, Ryuhei Wakida, Masato Kimura
https://arxiv.org/abs/2506.14788

Energy-consistent dynamic fracture phase field models: unilateral constraints and finite element simulations
Phase field models have emerged as a powerful and flexible framework for simulating complex interface-driven phenomena across a wide range of scientific and engineering applications. In fracture mechanics, the phase field approach--formulated as a gradient flow of the Griffith fracture energy with Ambrosio-Tortorelli regularization--has gained significant attention for its ability to capture complex crack topologies. In this study, we propose a dynamic fracture phase field model (DF-PFM) based …

A break from the norm? Parametric representations of preference heterogeneity for discrete choice models in health
John Buckell, Alice Wreford, Matthew Quaife, Thomas O. Hancock
https://arxiv.org/abs/2506.14099

A break from the norm? Parametric representations of preference heterogeneity for discrete choice models in health
Background: Any sample of individuals has its own, unique distribution of preferences for choices that they make. Discrete choice models try to capture these distributions. Mixed logits are by far the most commonly used choice model in health. A raft of parametric model specifications for these models are available. We test a range of alternatives assumptions, and model averaging, to test if or how model outputs are impacted. Design: Scoping review of current modelling practices. Seven alternat…

On the existence of consistent adversarial attacks in high-dimensional linear classification
Matteo Vilucchio, Lenka Zdeborov\'a, Bruno Loureiro
https://arxiv.org/abs/2506.12454

On the existence of consistent adversarial attacks in high-dimensional linear classification
What fundamentally distinguishes an adversarial attack from a misclassification due to limited model expressivity or finite data? In this work, we investigate this question in the setting of high-dimensional binary classification, where statistical effects due to limited data availability play a central role. We introduce a new error metric that precisely capture this distinction, quantifying model vulnerability to consistent adversarial attacks -- perturbations that preserve the ground-truth l…

A foundation model to predict and capture human cognition.
https://www.nature.com/articles/s41586-025-09215-4
And the reaction and criticism,

A foundation model to predict and capture human cognition - Nature
A computational model called Centaur, developed by fine-tuning a language model on a huge dataset called Psych-101, can predict and simulate human nature in experiments expressible in natural language, even in previously unseen situations.

Opus: A Prompt Intention Framework for Complex Workflow Generation
Th\'eo Fagnoni, Mahsun Altin, Chia En Chung, Phillip Kingston, Alan Tuning, Dana O. Mohamed, In\`es Adnani
https://arxiv.org/abs/2507.11288

Opus: A Prompt Intention Framework for Complex Workflow Generation
This paper introduces the Opus Prompt Intention Framework, designed to improve complex Workflow Generation with instruction-tuned Large Language Models (LLMs). We propose an intermediate Intention Capture layer between user queries and Workflow Generation, implementing the Opus Workflow Intention Framework, which consists of extracting Workflow Signals from user queries, interpreting them into structured Workflow Intention objects, and generating Workflows based on these Intentions. Our results…

Fare Game: A Mean Field Model of Stochastic Intensity Control in Dynamic Ticket Pricing
Burak Aydin, Emre Parmaksiz, Ronnie Sircar
https://arxiv.org/abs/2506.13088

Fare Game: A Mean Field Model of Stochastic Intensity Control in Dynamic Ticket Pricing
We study the dynamic pricing of discrete goods over a finite selling horizon. One way to capture both the elastic and stochastic reaction of purchases to price is through a model where sellers control the intensity of a counting process, representing the number of sales thus far. The intensity describes the probabilistic likelihood of a sale, and is a decreasing function of the price a seller sets. A classical model for ticket pricing, which assumes a single seller and infinite time horizon, is…

Weekend #Plankton Factoid 🦠🦐
Mating by copepods is a complicated process since they are always at risk of predation by other plankton or fishes. Male #copepods carefully mechanically and chemically track a receptive female, capture them, and deposit an adhesive spermatophore near the genital open…

A few notes on iPadOS 26 audio and video capture
https://sixcolors.com/post/2025/06/a-few-notes-on-ipados-26-audio-and-video-capture/

Hierarchical Rectified Flow Matching with Mini-Batch Couplings
Yichi Zhang, Yici Yan, Alex Schwing, Zhizhen Zhao
https://arxiv.org/abs/2507.13350 https://

Hierarchical Rectified Flow Matching with Mini-Batch Couplings
Flow matching has emerged as a compelling generative modeling approach that is widely used across domains. To generate data via a flow matching model, an ordinary differential equation (ODE) is numerically solved via forward integration of the modeled velocity field. To better capture the multi-modality that is inherent in typical velocity fields, hierarchical flow matching was recently introduced. It uses a hierarchy of ODEs that are numerically integrated when generating data. This hierarchy …

Comparing classical and machine learning force fields for modeling deformation of solid sorbents relevant for direct air capture
Logan M. Brabson, Andrew J. Medford, David S. Sholl
https://arxiv.org/abs/2506.09256

Comparing classical and machine learning force fields for modeling deformation of solid sorbents relevant for direct air capture
Direct air capture (DAC) with solid sorbents such as metal-organic frameworks (MOFs) is a promising approach for negative carbon emissions. Computational materials screening can help identify promising materials from the vast chemical space of potential sorbents. Experiments have shown that MOF framework flexibility and deformation induced by adsorbate molecules can drastically affect adsorption properties such as capacity and selectivity. Force field (FF) models are commonly used as surrogates…

FacialMotionID: Identifying Users of Mixed Reality Headsets using Abstract Facial Motion Representations
Adriano Castro, Simon Hanisch, Matin Fallahi, Thorsten Strufe
https://arxiv.org/abs/2507.11138

FacialMotionID: Identifying Users of Mixed Reality Headsets using Abstract Facial Motion Representations
Facial motion capture in mixed reality headsets enables real-time avatar animation, allowing users to convey non-verbal cues during virtual interactions. However, as facial motion data constitutes a behavioral biometric, its use raises novel privacy concerns. With mixed reality systems becoming more immersive and widespread, understanding whether face motion data can lead to user identification or inference of sensitive attributes is increasingly important. To address this, we conducted a stu…

Optimal and Suboptimal Decoders under Finite-Alphabet Interference: A Mismatched Decoding Perspective
Sibo Zhang, Bruno Clerckx
https://arxiv.org/abs/2506.12646

Optimal and Suboptimal Decoders under Finite-Alphabet Interference: A Mismatched Decoding Perspective
Interference widely exists in communication systems and is often not optimally treated at the receivers due to limited knowledge and/or computational burden. Evolutions of receivers have been proposed to balance complexity and spectral efficiency, for example, for 6G, while commonly used performance metrics, such as capacity and mutual information, fail to capture the suboptimal treatment of interference, leading to potentially inaccurate performance evaluations. Mismatched decoding is an infor…

If you're trying to do the trick that was shared for #nintendoswitch2 where you can use a USB HDMI capture dongle HDMI to USB-C cable to use your iPhone as a camera - don't use the True Visage app mentioned in the video
That will rely on screen sharing mirroring and you'll potentially get an aspect ratio mismatch and see the dynamic island floating in your view
I'd personally suggest the free "Blackmagic Camera" app instead, and then go to:
Settings->Monitor->HDMI Out
Switch from Mirror Display to Video Feed and it will cleanly output your camera. Works for a Lightning to HDMI out adapter for older phones, too
Then just tap on Lense and FPS and pick which combo you like.
Also, if you're not getting any output signal make sure the capture dongle you're using supports 1080p out - not sure the Switch 2 supports anything higher as camera input

Just wrote a quick blog post about our visit of the #zoo in #Nürnberg where I could capture some ground #squirrels that I found pretty cute.
I hope you like the photos as well.
The blog …

Robustness Requirement Coverage using a Situation Coverage Approach for Vision-based AI Systems
Sepeedeh Shahbeigi, Nawshin Mannan Proma, Victoria Hodge, Richard Hawkins, Boda Li, Valentina Donzella
https://arxiv.org/abs/2507.12986

Robustness Requirement Coverage using a Situation Coverage Approach for Vision-based AI Systems
AI-based robots and vehicles are expected to operate safely in complex and dynamic environments, even in the presence of component degradation. In such systems, perception relies on sensors such as cameras to capture environmental data, which is then processed by AI models to support decision-making. However, degradation in sensor performance directly impacts input data quality and can impair AI inference. Specifying safety requirements for all possible sensor degradation scenarios leads to unm…

Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation
Farid Mafi (University of Waterloo, Waterloo, Canada), Ladan Khoshnevisan (University of Waterloo, Waterloo, Canada), Mohammad Pirani (University of Ottawa, Ottawa, Canada), Amir Khajepour (University of Waterloo, Waterloo, Canada)

Bridging Data-Driven and Physics-Based Models: A Consensus Multi-Model Kalman Filter for Robust Vehicle State Estimation
Vehicle state estimation presents a fundamental challenge for autonomous driving systems, requiring both physical interpretability and the ability to capture complex nonlinear behaviors across diverse operating conditions. Traditional methodologies often rely exclusively on either physics-based or data-driven models, each with complementary strengths and limitations that become most noticeable during critical scenarios. This paper presents a novel consensus multi-model Kalman filter framework t…

How Warm-Glow Alters the Usability of Technology
Antonios Saravanos (New York University)
https://arxiv.org/abs/2506.14720 https://ar…

How Warm-Glow Alters the Usability of Technology
As technology increasingly aligns with users' personal values, traditional models of usability, focused on functionality and specifically effectiveness, efficiency, and satisfaction, may not fully capture how people perceive and evaluate it. This study investigates how the warm-glow phenomenon, the positive feeling associated with doing good, shapes perceived usability. An experimental approach was taken in which participants evaluated a hypothetical technology under conditions designed to evok…

Reliable Noninvasive Glucose Sensing via CNN-Based Spectroscopy
El Arbi Belfarsi, Henry Flores, Maria Valero
https://arxiv.org/abs/2506.13819 https://

Reliable Noninvasive Glucose Sensing via CNN-Based Spectroscopy
In this study, we present a dual-modal AI framework based on short-wave infrared (SWIR) spectroscopy. The first modality employs a multi-wavelength SWIR imaging system coupled with convolutional neural networks (CNNs) to capture spatial features linked to glucose absorption. The second modality uses a compact photodiode voltage sensor and machine learning regressors (e.g., random forest) on normalized optical signals. Both approaches were evaluated on synthetic blood phantoms and skin-mimicking…

Moment-enhanced shallow water equations for non-slip boundary conditions
Shiping Zhou, Juntao Huang, Andrew J. Christlieb
https://arxiv.org/abs/2506.14785 …

Moment-enhanced shallow water equations for non-slip boundary conditions
The shallow water equations often assume a constant velocity profile along the vertical axis. However, this assumption does not hold in many practical applications. To better approximate the vertical velocity distribution, models such as the shallow water moment expansion models have been proposed. Nevertheless, under non-slip bottom boundary conditions, both the standard shallow water equation and its moment-enhanced models struggle to accurately capture the vertical velocity profile due to th…

XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
Ke Wang, Bo Pan, Yingchaojie Feng, Yuwei Wu, Jieyi Chen, Minfeng Zhu, Wei Chen
https://arxiv.org/abs/2506.13782

XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
Graph-based Retrieval-Augmented Generation (RAG) has shown great capability in enhancing Large Language Model (LLM)'s answer with an external knowledge base. Compared to traditional RAG, it introduces a graph as an intermediate representation to capture better structured relational knowledge in the corpus, elevating the precision and comprehensiveness of generation results. However, developers usually face challenges in analyzing the effectiveness of GraphRAG on their dataset due to GraphRAG's …

Cross-World Assumption and Refining Prediction Intervals for Individual Treatment Effects
Juraj Bodik, Yaxuan Huang, Bin Yu
https://arxiv.org/abs/2507.12581

Cross-World Assumption and Refining Prediction Intervals for Individual Treatment Effects
While average treatment effects (ATE) and conditional average treatment effects (CATE) provide valuable population- and subgroup-level summaries, they fail to capture uncertainty at the individual level. For high-stakes decision-making, individual treatment effect (ITE) estimates must be accompanied by valid prediction intervals that reflect heterogeneity and unit-specific uncertainty. However, the fundamental unidentifiability of ITEs limits the ability to derive precise and reliable individua…

Exploring Cultural Variations in Moral Judgments with Large Language Models
Hadi Mohammadi, Efthymia Papadopoulou, Yasmeen F. S. S. Meijer, Ayoub Bagheri
https://arxiv.org/abs/2506.12433

Exploring Cultural Variations in Moral Judgments with Large Language Models
Large Language Models (LLMs) have shown strong performance across many tasks, but their ability to capture culturally diverse moral values remains unclear. In this paper, we examine whether LLMs can mirror variations in moral attitudes reported by two major cross-cultural surveys: the World Values Survey and the PEW Research Center's Global Attitudes Survey. We compare smaller, monolingual, and multilingual models (GPT-2, OPT, BLOOMZ, and Qwen) with more recent instruction-tuned models (GPT-4o,…

Multi-loop spectra in general scalar EFTs and CFTs
Johan Henriksson, Franz Herzog, Stefanos R. Kousvos, Jasper Roosmale Nepveu
https://arxiv.org/abs/2507.12518

Multi-loop spectra in general scalar EFTs and CFTs
We consider the most general effective field theory (EFT) Lagrangian with scalar fields and derivatives, and renormalise it to substantially higher loop order than existing results in the literature. EFT Lagrangians have phenomenological applications, for example by encoding corrections to the Standard Model from unknown new physics. At the same time, scalar EFTs capture the spectrum of Wilson--Fisher conformal field theories (CFTs) in $4-\varepsilon$ dimensions. Our results are enabled by a mo…

from my link log —
PostgreSQL replication slots: preventing WAL bloat and other production issues.
https://www.morling.dev/blog/mastering-postgres-replication-slots/
saved 2025-07-08

ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving
Yuhang Lu, Jiadong Tu, Yuexin Ma, Xinge Zhu
https://arxiv.org/abs/2507.12499 https:/…

ReAL-AD: Towards Human-Like Reasoning in End-to-End Autonomous Driving
End-to-end autonomous driving has emerged as a promising approach to unify perception, prediction, and planning within a single framework, reducing information loss and improving adaptability. However, existing methods often rely on fixed and sparse trajectory supervision, limiting their ability to capture the hierarchical reasoning process that human drivers naturally employ. To bridge this gap, we propose ReAL-AD, a Reasoning-Augmented Learning framework that structures decision-making in aut…

MERba: Multi-Receptive Field MambaVision for Micro-Expression Recognition
Xinglong Mao, Shifeng Liu, Sirui Zhao, Tong Xu, Enhong Chen
https://arxiv.org/abs/2506.14468

MERba: Multi-Receptive Field MambaVision for Micro-Expression Recognition
Micro-expressions (MEs) are brief, involuntary facial movements that reveal genuine emotions, holding significant potential in psychological diagnosis and criminal investigations. Despite notable advances in automatic ME recognition (MER), existing methods still struggle to jointly capture localized muscle activations and global facial dependencies, both critical for recognizing subtle emotional cues. To tackle this challenge, we propose MERba, a novel multi-receptive field architecture tailore…

🪤 A California dairy tried to capture its methane, and it worked
#dairy

A California dairy tried to capture its methane, and it worked
A giant, balloon-like tarp stretches over a lagoon of manure on a Central Valley dairy farm, concealing a quiet but remarkable transformation. Methane, a potent climate-warming gas, is being captured and cleaned instead of released into the atmosphere.

Capture Stage Environments: A Guide to Better Matting
Hannah Dr\"oge, Janelle Pfeifer, Saskia Rabich, Markus Plack, Reinhard Klein, Matthias B. Hullin
https://arxiv.org/abs/2507.07623

Capture Stage Environments: A Guide to Better Matting
Capture stages are high-end sources of state-of-the-art recordings for downstream applications in movies, games, and other media. One crucial step in almost all pipelines is the matting of images to isolate the captured performances from the background. While common matting algorithms deliver remarkable performance in other applications like teleconferencing and mobile entertainment, we found that they struggle significantly with the peculiarities of capture stage content. The goal of our work …

Pathology-Guided Virtual Staining Metric for Evaluation and Training
Qiankai Wang, James E. D. Tweel, Parsin Haji Reza, Anita Layton
https://arxiv.org/abs/2507.12624

Pathology-Guided Virtual Staining Metric for Evaluation and Training
Virtual staining has emerged as a powerful alternative to traditional histopathological staining techniques, enabling rapid, reagent-free image transformations. However, existing evaluation methods predominantly rely on full-reference image quality assessment (FR-IQA) metrics such as structural similarity, which are originally designed for natural images and often fail to capture pathology-relevant features. Expert pathology reviews have also been used, but they are inherently subjective and ti…

Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network
Yanjun Dai, Haoyang Feng, Yuan Gao
https://arxiv.org/abs/2506.13787

Analysis of Anonymous User Interaction Relationships and Prediction of Advertising Feedback Based on Graph Neural Network
While online advertising is highly dependent on implicit interaction networks of anonymous users for engagement inference, and for the selection and optimization of delivery strategies, existing graph models seldom can capture the multi-scale temporal, semantic and higher-order dependency features of these interaction networks, thus it's hard to describe the complicated patterns of the anonymous behavior. In this paper, we propose Decoupled Temporal-Hierarchical Graph Neural Network (DTH-GNN), …

"Green roofs shown to capture nearly all microplastics from rainwater"
#Microplastics #Plastic #Plastics

Green roofs shown to capture nearly all microplastics from rainwater
A small team of researchers at Tongji University, working with a colleague from the Shanghai Academy of Landscape Architecture Science and Planning, both in China, has found that growing plants on roofs can serve as an effective way to remove microplastics from the air. In their study, published in the journal Communications Earth & Environment, the group measured the amounts of microplastics found on plants and the soil in which they grow.

Video-Guided Text-to-Music Generation Using Public Domain Movie Collections
Haven Kim, Zachary Novack, Weihan Xu, Julian McAuley, Hao-Wen Dong
https://arxiv.org/abs/2506.12573

Video-Guided Text-to-Music Generation Using Public Domain Movie Collections
Despite recent advancements in music generation systems, their application in film production remains limited, as they struggle to capture the nuances of real-world filmmaking, where filmmakers consider multiple factors-such as visual content, dialogue, and emotional tone-when selecting or composing music for a scene. This limitation primarily stems from the absence of comprehensive datasets that integrate these elements. To address this gap, we introduce Open Screen Sound Library (OSSL), a dat…

SAG-AFTRA ends the 300 day video game actors strike after reaching a tentative deal for a new Interactive Media Agreement with the major video game companies (Erik Hayden/The Hollywood Reporter)
https://www.hollywoodreporter.com/business

SAG-AFTRA Suspends Strike Against Video Game Companies, Paving Way for Return to Work
The union had taken a stand on artificial intelligence, among other concerns, as it looked to advocate for voice and performance capture workers.

X-ray Measurements of $^{44}$Ti in Four Supernova Remnants
Tyler E. Hanover, Mark D. Leising
https://arxiv.org/abs/2507.11647 https://

X-ray Measurements of $^{44}$Ti in Four Supernova Remnants
We present the results of a search for scandium K$_α$ X-ray fluorescence resulting from $^{44}$Ti electron capture decay in four young supernova remnants. We analyzed archival XMM-Newton data from Tycho's SNR, Kepler's SNR, Cassiopeia A, and SN 1987A. We fit the X-ray spectra in regions of interest with up to four components, thermal and power-law, as needed to fit the spectrum, and add a gaussian to test for extra Sc emission. While all require the line with modest confidence, none represent …

Dnipropetrovsk village likely contested despite Russia's claim of its capture: https://benborges.xyz/2025/07/08/dnipropetrovsk-village-likely-contested-despite.html

Interpreting Radiologist's Intention from Eye Movements in Chest X-ray Diagnosis
Trong-Thang Pham, Anh Nguyen, Zhigang Deng, Carol C. Wu, Hien Van Nguyen, Ngan Le
https://arxiv.org/abs/2507.12461

Interpreting Radiologist's Intention from Eye Movements in Chest X-ray Diagnosis
Radiologists rely on eye movements to navigate and interpret medical images. A trained radiologist possesses knowledge about the potential diseases that may be present in the images and, when searching, follows a mental checklist to locate them using their gaze. This is a key observation, yet existing models fail to capture the underlying intent behind each fixation. In this paper, we introduce a deep learning-based approach, RadGazeIntent, designed to model this behavior: having an intention t…

A Hierarchical Test Platform for Vision Language Model (VLM)-Integrated Real-World Autonomous Driving
Yupeng Zhou, Can Cui, Juntong Peng, Zichong Yang, Juanwu Lu, Jitesh H Panchal, Bin Yao, Ziran Wang
https://arxiv.org/abs/2506.14100

A Hierarchical Test Platform for Vision Language Model (VLM)-Integrated Real-World Autonomous Driving
Vision-Language Models (VLMs) have demonstrated notable promise in autonomous driving by offering the potential for multimodal reasoning through pretraining on extensive image-text pairs. However, adapting these models from broad web-scale data to the safety-critical context of driving presents a significant challenge, commonly referred to as domain shift. Existing simulation-based and dataset-driven evaluation methods, although valuable, often fail to capture the full complexity of real-world …

Unsupervised Document and Template Clustering using Multimodal Embeddings
Phillipe R. Sampaio, Helene Maxcici
https://arxiv.org/abs/2506.12116 https://

Unsupervised Document and Template Clustering using Multimodal Embeddings
This paper investigates a novel approach to unsupervised document clustering by leveraging multimodal embeddings as input to traditional clustering algorithms such as $k$-Means and DBSCAN. Our method aims to achieve a finer-grained document understanding by not only grouping documents at the type level (e.g., invoices, purchase orders), but also distinguishing between different templates within the same document category. This is achieved by using embeddings that capture textual content, layout…

StorySage: Conversational Autobiography Writing Powered by a Multi-Agent Framework
Shayan Talaei, Meijin Li, Kanu Grover, James Kent Hippler, Diyi Yang, Amin Saberi
https://arxiv.org/abs/2506.14159

StorySage: Conversational Autobiography Writing Powered by a Multi-Agent Framework
Every individual carries a unique and personal life story shaped by their memories and experiences. However, these memories are often scattered and difficult to organize into a coherent narrative, a challenge that defines the task of autobiography writing. Existing conversational writing assistants tend to rely on generic user interactions and pre-defined guidelines, making it difficult for these systems to capture personal memories and develop a complete biography over time. We introduce Story…

Replaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
Free Your Hands: Lightweight Turntable-Based Object Capture Pipeline
htt…

Similarity = Value? Consultation Value Assessment and Alignment for Personalized Search
Weicong Qin, Yi Xu, Weijie Yu, Teng Shi, Chenglei Shen, Ming He, Jianping Fan, Xiao Zhang, Jun Xu
https://arxiv.org/abs/2506.14437

Similarity = Value? Consultation Value Assessment and Alignment for Personalized Search
Personalized search systems in e-commerce platforms increasingly involve user interactions with AI assistants, where users consult about products, usage scenarios, and more. Leveraging consultation to personalize search services is trending. Existing methods typically rely on semantic similarity to align historical consultations with current queries due to the absence of 'value' labels, but we observe that semantic similarity alone often fails to capture the true value of consultation for perso…

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation
Daniya Najiha Abdul Kareem, Abdul Hannan, Mubashir Noman, Jean Lahoud, Mustansar Fiaz, Hisham Cholakkal
https://arxiv.org/abs/2506.12208

InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation
Accurate microscopic medical image segmentation plays a crucial role in diagnosing various cancerous cells and identifying tumors. Driven by advancements in deep learning, convolutional neural networks (CNNs) and transformer-based models have been extensively studied to enhance receptive fields and improve medical image segmentation task. However, they often struggle to capture complex cellular and tissue structures in challenging scenarios such as background clutter and object overlap. Moreove…

Smartphone Exergames with Real-Time Markerless Motion Capture: Challenges and Trade-offs
Mathieu Phosanarack (LAMIH, UPHF), Laura Wallard (LAMIH, UPHF), Sophie Lepreux (LAMIH, UPHF), Christophe Kolski (LAMIH), Eug\'enie Avril (LAMIH, UPHF)
https://arxiv.org/abs/2507.06669

Smartphone Exergames with Real-Time Markerless Motion Capture: Challenges and Trade-offs
Markerless Motion Capture (MoCap) using smartphone cameras is a promising approach to making exergames more accessible and cost-effective for health and rehabilitation. Unlike traditional systems requiring specialized hardware, recent advancements in AI-powered pose estimation enable movement tracking using only a mobile device. For an upcoming study, a mobile application with real-time exergames including markerless motion capture is being developed. However, implementing such technology intro…

A Hybrid Algorithm for Drift-Kinetic Particle Dynamics within General Relativistic Magnetohydrodynamics Simulations of Black Holes Accretion Flows
Tyler Trent, Dimitrios Psaltis, Feryal \"Ozel
https://arxiv.org/abs/2507.11616

A Hybrid Algorithm for Drift-Kinetic Particle Dynamics within General Relativistic Magnetohydrodynamics Simulations of Black Holes Accretion Flows
Astrophysical plasmas in relativistic spacetimes, such as black hole accretion flows, are often weakly collisional and require kinetic modeling to capture non-local transport and particle acceleration. However, the extreme scale separation between microscopic and macroscopic processes limits the feasibility of fully kinetic simulations. A covariant guiding center formalism has recently been derived to address this challenge in curved spacetimes. We present a new hybrid numerical algorithm based…

Generalized Scattering Matrix Framework for Modeling Implantable Antennas in Multilayered Spherical Media
Chenbo Shi, Xin Gu, Shichen Liang, Jin Pan
https://arxiv.org/abs/2507.13119

Generalized Scattering Matrix Framework for Modeling Implantable Antennas in Multilayered Spherical Media
This paper presents a unified and efficient framework for analyzing antennas embedded in spherically stratified media -- a model broadly applicable to implantable antennas in biomedical systems and radome-enclosed antennas in engineering applications. The proposed method decouples the modeling of the antenna and its surrounding medium by combining the antenna's free-space generalized scattering matrix (GSM) with a set of extended spherical scattering operators (SSOs) that rigorously capture the…

Real-World Summarization: When Evaluation Reaches Its Limits
Patr\'icia Schmidtov\'a, Ond\v{r}ej Du\v{s}ek, Saad Mahamood
https://arxiv.org/abs/2507.11508

Real-World Summarization: When Evaluation Reaches Its Limits
We examine evaluation of faithfulness to input data in the context of hotel highlights: brief LLM-generated summaries that capture unique features of accommodations. Through human evaluation campaigns involving categorical error assessment and span-level annotation, we compare traditional metrics, trainable methods, and LLM-as-a-judge approaches. Our findings reveal that simpler metrics like word overlap correlate surprisingly well with human judgments (Spearman correlation rank of 0.63), often…

Transformer IMU Calibrator: Dynamic On-body IMU Calibration for Inertial Motion Capture
Chengxu Zuo, Jiawei Huang, Xiao Jiang, Yuan Yao, Xiangren Shi, Rui Cao, Xinyu Yi, Feng Xu, Shihui Guo, Yipeng Qin
https://arxiv.org/abs/2506.10580

Transformer IMU Calibrator: Dynamic On-body IMU Calibration for Inertial Motion Capture
In this paper, we propose a novel dynamic calibration method for sparse inertial motion capture systems, which is the first to break the restrictive absolute static assumption in IMU calibration, i.e., the coordinate drift RG'G and measurement offset RBS remain constant during the entire motion, thereby significantly expanding their application scenarios. Specifically, we achieve real-time estimation of RG'G and RBS under two relaxed assumptions: i) the matrices change negligibly in a short tim…

4DSloMo: 4D Reconstruction for High Speed Scene with Asynchronous Capture
Yutian Chen, Shi Guo, Tianshuo Yang, Lihe Ding, Xiuyuan Yu, Jinwei Gu, Tianfan Xue
https://arxiv.org/abs/2507.05163

4DSloMo: 4D Reconstruction for High Speed Scene with Asynchronous Capture
Reconstructing fast-dynamic scenes from multi-view videos is crucial for high-speed motion analysis and realistic 4D reconstruction. However, the majority of 4D capture systems are limited to frame rates below 30 FPS (frames per second), and a direct 4D reconstruction of high-speed motion from low FPS input may lead to undesirable results. In this work, we propose a high-speed 4D capturing system only using low FPS cameras, through novel capturing and processing modules. On the capturing side, …

Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation
Ashkan Shakarami, Azade Farshad, Yousef Yeganeh, Lorenzo Nicole, Peter Schuffler, Stefano Ghidoni, Nassir Navab
https://arxiv.org/abs/2507.12427

Unit-Based Histopathology Tissue Segmentation via Multi-Level Feature Representation
We propose UTS, a unit-based tissue segmentation framework for histopathology that classifies each fixed-size 32 * 32 tile, rather than each pixel, as the segmentation unit. This approach reduces annotation effort and improves computational efficiency without compromising accuracy. To implement this approach, we introduce a Multi-Level Vision Transformer (L-ViT), which benefits the multi-level feature representation to capture both fine-grained morphology and global tissue context. Trained to s…

Hierarchical Group-wise Ranking Framework for Recommendation Models
YaChen Yan, Liubo Li, Ravi Choudhary
https://arxiv.org/abs/2506.12756 https://

Hierarchical Group-wise Ranking Framework for Recommendation Models
In modern recommender systems, CTR/CVR models are increasingly trained with ranking objectives to improve item ranking quality. While this shift aligns training more closely with serving goals, most existing methods rely on in-batch negative sampling, which predominantly surfaces easy negatives. This limits the model's ability to capture fine-grained user preferences and weakens overall ranking performance. To address this, we propose a Hierarchical Group-wise Ranking Framework with two key com…

Tomato Multi-Angle Multi-Pose Dataset for Fine-Grained Phenotyping
Yujie Zhang, Sabine Struckmeyer, Andreas Kolb, Sven Reichardt
https://arxiv.org/abs/2507.11279

Tomato Multi-Angle Multi-Pose Dataset for Fine-Grained Phenotyping
Observer bias and inconsistencies in traditional plant phenotyping methods limit the accuracy and reproducibility of fine-grained plant analysis. To overcome these challenges, we developed TomatoMAP, a comprehensive dataset for Solanum lycopersicum using an Internet of Things (IoT) based imaging system with standardized data acquisition protocols. Our dataset contains 64,464 RGB images that capture 12 different plant poses from four camera elevation angles. Each image includes manually annotate…