Tootfinder

Deaths by domain of protest over 12 Bolivian presidencies.
Same data, same graphing technique, but sorting the categories (by which occurs across the most bins) brings visual order to this data visualization. #dataviz #rstats

This https://arxiv.org/abs/2311.14590 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Stability of domain walls with inflationary fluctuations under potential bias, and gravitational wave signatures
A recent study has shown that domain walls with inflationary initial fluctuations exhibit remarkable stability against population bias due to long-range correlations, challenging the claims of prior research. In this paper, we study the dynamics of these domain walls in the presence of potential bias and show that they collapse with a lifetime several times longer than that due to thermal fluctuations. This is interpreted as a difference in the average distance between domain walls, leading us …

The Hourglass Simulation: A Catalog for the Roman High-Latitude Time-Domain Core Community Survey
B. M. Rose, M. Vincenzi, R. Hounsell, H. Qu, L. Aldoroty, D. Scolnic, R. Kessler, P. Macias, D. Brout, M. Acevedo, R. C. Chen, S. Gomez, E. Peterson, D. Rubin, M. Sako
https://arxiv.org/abs/2506.05161

The Hourglass Simulation: A Catalog for the Roman High-Latitude Time-Domain Core Community Survey
We present a simulation of the time-domain catalog for the Nancy Grace Roman Space Telescope's High-Latitude Time-Domain Core Community Survey. This simulation, called the Hourglass simulation, uses the most up-to-date spectral energy distribution models and rate measurements for ten extra-galactic time-domain sources. We simulate these models through the design reference Roman Space Telescope survey: four filters per tier, a five day cadence, over two years, a wide tier of 19 deg$^2$ and a dee…

This https://arxiv.org/abs/2411.06842 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

DRIFTS: Optimizing Domain Randomization with Synthetic Data and Weight Interpolation for Fetal Brain Tissue Segmentation
Fetal brain tissue segmentation in magnetic resonance imaging (MRI) is a crucial tool that supports understanding of neurodevelopment, yet it faces challenges due to the heterogeneity of data coming from different scanners and settings, as well as data scarcity. Recent approaches based on domain randomization, like SynthSeg, have shown great potential for single-source domain generalization by simulating images with randomized contrast and image resolution from the label maps. In this work, we …

This https://arxiv.org/abs/2505.02515 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

FedSDAF: Leveraging Source Domain Awareness for Enhanced Federated Domain Generalization
Traditional domain generalization approaches predominantly focus on leveraging target domain-aware features while overlooking the critical role of source domain-specific characteristics, particularly in federated settings with inherent data isolation. To address this gap, we propose the Federated Source Domain Awareness Framework (FedSDAF), the first method to systematically exploit source domain-aware features for enhanced federated domain generalization (FedDG). The FedSDAF framework consists…

This https://arxiv.org/abs/2505.23847 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership. Yet, cross-domain collaboration shatters the unified trust assumptions behind current alignment and containment techniques. An agent benign in isolation may, when receiving messages from an untrusted peer, leak secrets or viola…

Fishing for the Optimal Roman High Latitude Time Domain Survey: Cosmological Constraints for 1,000 Possible Surveys
David Rubin, Greg Aldering, Andy Fruchter, Lluis Galbany, Rebekah Hounsell, Rick Kessler, Saul Perlmutter, Ben Rose, Masao Sako, Dan Scolnic, Jannik Truong, the Roman Supernova Cosmology Project Infrastructure Team
https://

Fishing for the Optimal Roman High Latitude Time Domain Survey: Cosmological Constraints for 1,000 Possible Surveys
The upcoming Nancy Grace Roman Space Telescope is set to conduct a generation-defining SN Ia cosmology measurement with its High Latitude Time Domain Survey (HLTDS). However, between optical elements, exposure times, cadences, and survey areas, there are many survey parameters to consider. This work was part of a Roman Project Infrastructure Team effort to help the Core Community Survey (CCS) Committee finalize the HLTDS recommendation to the Roman Observations Time Allocation Committee. We sim…

I just did the generic "Applications Engineer" job test for City of SF and it definitely was written by someone who hasn't moved past domain controllers and 2005. I got a "15.0", whatever that means for the rule of the list.

Heute vor 65 Jahren: Am 7. Juni 1960 explodierte ein Heliumtank und beschädigte die Treibstofftanks einer USAF BOMARC-A Flugabwehrrakete auf der McGuire Air Force Base, New Jersey. Der Brand zerstörte die Rakete mit #Nuklearsprengkopf und kontaminierte die umliegende Gegend.

Domain Adaptation Method and Modality Gap Impact in Audio-Text Models for Prototypical Sound Classification
Emiliano Acevedo, Mart\'in Rocamora, Magdalena Fuentes
https://arxiv.org/abs/2506.04376

Domain Adaptation Method and Modality Gap Impact in Audio-Text Models for Prototypical Sound Classification
Audio-text models are widely used in zero-shot environmental sound classification as they alleviate the need for annotated data. However, we show that their performance severely drops in the presence of background sound sources. Our analysis reveals that this degradation is primarily driven by SNR levels of background soundscapes, and independent of background type. To address this, we propose a novel method that quantifies and integrates the contribution of background sources into the classifi…

This https://arxiv.org/abs/2502.00698 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models
IQ testing has served as a foundational methodology for evaluating human cognitive capabilities, deliberately decoupling assessment from linguistic background, language proficiency, or domain-specific knowledge to isolate core competencies in abstraction and reasoning. Yet, artificial intelligence research currently lacks systematic benchmarks to quantify these critical cognitive capabilities in multimodal systems. To address this crucial gap, we propose MM-IQ, a comprehensive evaluation framew…

Fresnel reflection coefficients in the Fourier domain for a planar surface in uniform motion parallel to its interface
St\'ephane Azar, Sebastian Golat, Francisco J. Rodr\'iguez-Fortu\~no
https://arxiv.org/abs/2506.04417

Fresnel reflection coefficients in the Fourier domain for a planar surface in uniform motion parallel to its interface
The optical reflection coefficient of a dielectric medium moving uniformly in the plane spanned by its surface is rigorously calculated using classical electrodynamics and special relativity, and expressed in the Fourier domain, as a function of the incident frequency and wavevector, valid in both the far- and near-field regimes. It is found that cross-polarisation appears as a consequence of the motion, except when it is directed along the plane of incidence. As an example, using a Drude model…

This https://arxiv.org/abs/2504.09748 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Level-set topology optimisation with unfitted finite elements and automatic shape differentiation
In this paper we develop automatic shape differentiation techniques for unfitted discretisations and link these to recent advances in shape calculus for unfitted methods. We extend existing analytic shape calculus results to the case where the domain boundary intersects with the boundary of the background domain. We further show that we can recover these analytic derivatives to machine precision regardless of the mesh size using the developed automatic shape differentiation techniques, drastica…

Automatic Multi-level Feature Tree Construction for Domain-Specific Reusable Artifacts Management
Dongming Jin, Zhi Jin, Nianyu Li, Kai Yang, Linyu Li, Suijing Guan
https://arxiv.org/abs/2506.03946

Automatic Multi-level Feature Tree Construction for Domain-Specific Reusable Artifacts Management
With the rapid growth of open-source ecosystems (e.g., Linux) and domain-specific software projects (e.g., aerospace), efficient management of reusable artifacts is becoming increasingly crucial for software reuse. The multi-level feature tree enables semantic management based on functionality and supports requirements-driven artifact selection. However, constructing such a tree heavily relies on domain expertise, which is time-consuming and labor-intensive. To address this issue, this paper pr…

This https://arxiv.org/abs/2505.10033 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Evaluating Robustness of Deep Reinforcement Learning for Autonomous Surface Vehicle Control in Field Tests
Despite significant advancements in Deep Reinforcement Learning (DRL) for Autonomous Surface Vehicles (ASVs), their robustness in real-world conditions, particularly under external disturbances, remains insufficiently explored. In this paper, we evaluate the resilience of a DRL-based agent designed to capture floating waste under various perturbations. We train the agent using domain randomization and evaluate its performance in real-world field tests, assessing its ability to handle unexpected…

Any email address is a valid email address once it has at least one character before the @, one character after the @ and a character after the full stop (.)
You should _not_ be doing any checks beyond that. (Unless the domain name is a known spammy domain/TLD, of course, but that doesn't appear to be the case here)
My email address is a 1 character before the @, 2 characters after the @ and 2 letters after the full stop(.)
It is valid.
#noxp

This https://arxiv.org/abs/2504.09200 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

A Datagram Extension to DNS over QUIC: Proven Resource Conservation in the Internet of Things
In this paper, we investigate the Domain Name System (DNS) over QUIC (DoQ) and propose a non-disruptive extension, which can greatly reduce DoQ's resource consumption. This extension can benefit all DNS clients - especially Internet of Things (IoT) devices. This is important because even resource-constrained IoT devices can generate dozens of DNS requests every hour. DNS is a crucial service that correlates IP addresses and domain names. It is traditionally sent as plain-text, favoring low-late…

This https://arxiv.org/abs/2503.17464 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Other Examples of Principal Ideal Domains that are not Euclidean Domains
It is a well-known and easily established fact that every Euclidean domain is also a principal ideal domain. However, the converse statement is not true, and this is usually shown by exhibiting as a counterexample the ring of algebraic integers in a certain, very specific quadratic field, and the proof that this works is quite unnatural and technical. In this article, we will present a family of counterexamples constructed using real closed fields.

This https://arxiv.org/abs/2409.03686 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Numerical spectral analysis of Cauchy-type inverse problems: A probabilistic approach
We investigate the inverse Cauchy and data completion problems for elliptic partial differential equations in a bounded domain $D \subset \mathbb{R}^d$, $d \ge 2$, with a special emphasis on the steady-state heat conduction in anisotropic media. More precisely, boundary conditions are prescribed on an accessible part of the boundary $\varnothing \neq Γ_0 \subsetneqq \partial{D}$ and/or internal conditions are available inside the domain $D$ and the aim is to reconstruct the solution to these i…

This https://arxiv.org/abs/2505.16764 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Can a domain-specific language improve program structure comprehension of data pipelines? A mixed-methods study
In many application domains, domain-specific languages can allow domain experts to contribute to collaborative projects more correctly and efficiently. To do so, they must be able to understand program structure from reading existing source code. With high-quality data becoming an increasingly important resource, the creation of data pipelines is an important application domain for domain-specific languages. We execute a mixed-method study consisting of a controlled experiment and a follow-up…

Thermal Property Microscopy with Compressive Sensing Frequency-Domain Thermoreflectance
Haobo Yang, Zhenguo Zhu, Zhongnan Xie, Jinhong Du, Shuo Bai, Hong Guo, Te-Huan Liu, Ronggui Yang, Xin Qian
https://arxiv.org/abs/2506.04728

Thermal Property Microscopy with Compressive Sensing Frequency-Domain Thermoreflectance
Spatial mapping of thermal properties is critical for unveiling the structure-property relation of materials, heterogeneous interfaces, and devices. These property images can also serve as datasets for training artificial intelligence models for material discoveries and optimization. Here we introduce a high-throughput thermal property imaging method called compressive sensing frequency domain thermoreflectance (CS-FDTR), which can robustly profile thermal property distributions with micrometer…

This https://arxiv.org/abs/2503.06474 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

ROGRAG: A Robustly Optimized GraphRAG Framework
Large language models (LLMs) commonly struggle with specialized or emerging topics which are rarely seen in the training corpus. Graph-based retrieval-augmented generation (GraphRAG) addresses this by structuring domain knowledge as a graph for dynamic retrieval. However, existing pipelines involve complex engineering workflows, making it difficult to isolate the impact of individual components. It is also challenging to evaluate the retrieval effectiveness due to the overlap between the pretra…

This https://arxiv.org/abs/2410.12815 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Expanding Over-the-Air Computation with Frequency Modulations
In this study we introduce Logarithmic Frequency Shift Keying (Log-FSK), a novel frequency modulation for over-the-air computation (AirComp). Log-FSK leverages non-linear signal processing to produce AirComp in the frequency domain, this is, the maximum frequency of the received signal corresponds to the sum of the individual transmitted frequencies. The demodulation procedure relies on the inverse Discrete Cosine Transform (DCT) and the extraction of the maximum frequency component. Log-FSK en…

On the distribution of critical points of the Eisenstein series $E_6$ and monodromy interpretation
Zhijie Chen
https://arxiv.org/abs/2506.03475 https://

On the distribution of critical points of the Eisenstein series $E_6$ and monodromy interpretation
In previous works joint with Lin, we proved that the Eisenstein series $E_4$ (resp. $E_2$) has at most one critical point in every fundamental domain $γ(F_0)$ of $Γ_{0}(2)$, where $γ(F_0)$ are translates of the basic fundamental domain $F_0$ via the Möbius transformation of $γ\inΓ_{0}(2)$. But the method can not work for the Eisenstein series $E_6$. In this paper, we develop a new approach to show that $E_6'(τ)$ has exactly either $1$ or $2$ zeros in every fundamental domain $γ(F_0)$ …

Distribution System State and Impedance Estimation Augmented with Carson's Equations
Marta Vanin, Frederik Geth, Rahmat Heidari, Dirk Van Hertem
https://arxiv.org/abs/2506.04949

Distribution System State and Impedance Estimation Augmented with Carson's Equations
The impedances of cables and lines used in (multi-conductor) distribution networks are usually unknown or approximated, and may lead to problematic results for any physics-based power system calculation, e.g., (optimal) power flow. Learning parameters from time series data is one of the few available options to obtain improved impedance models. This paper presents an approach that combines statistical learning concepts with the exploitation of domain knowledge, in the form of Carson's equations…

This https://arxiv.org/abs/2406.18322 has been replaced.
initial toot: https://mastoxiv.page/@…

A new quadrature for the generalized hydrodynamics equation and absence of shocks in the Lieb-Liniger model
In conventional fluids, it is well known that Euler-scale equations are plagued by ambiguities and instabilities. Smooth initial conditions may develop shocks, and weak solutions, such as for domain wall initial conditions (the paradigmatic Riemann problem of hydrodynamics), are not unique. The absence of shock formation experimentally observed in quasi-one-dimensional cold-atomic gases, which are described by the Lieb-Liniger model, provides perhaps the strongest pointer to a modification of t…

This https://arxiv.org/abs/2411.04900 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Modular domain walls and gravitational waves
We discuss modular domain walls and gravitational waves in a class of supersymmetric models where quark and lepton flavour symmetry emerges from modular symmetry. In such models a single modulus field $τ$ is often assumed to be stabilised at or near certain fixed point values such as $τ= {\rm i}$ and $τ= ω$ (the cube root of unity), in its fundamental domain. We show that, in the global supersymmetry limit of certain classes of potentials, the vacua at these fixed points may be degenerate, …

Heute vor 63 Jahren: Am 06.06.1962 zündeten die #USA im Rahmen von Operation Nougat die 36. Atombombe "Packrat". Nougat war eine Serie von #Kernwaffentests bei der 61/62 insgesamt 45 Bomben im Testgebiet in #Nevada

Cosmology Constraints from Type Ia Supernova Simulations of the Nancy Grace Roman Space Telescope Strategy Recommended by the High Latitude Time Domain Survey Definition Committee
Richard Kessler, Rebekah Hounsell, Bhavin Joshi, David Rubin, Masao Sako, Rebecca Chen, Vivian Miranda, Benjamin. M. Rose
https://arxiv.org/abs/2506.0…

Cosmology Constraints from Type Ia Supernova Simulations of the Nancy Grace Roman Space Telescope Strategy Recommended by the High Latitude Time Domain Survey Definition Committee
Within the next few years, the upcoming Nancy Grace Roman Space Telescope will be gathering data for the High Latitude Time Domain Survey (HLTDS) that will be used to significantly improve the Type Ia supernova measurement of the dark energy equation of state parameters w0 and wa. Here we generate a catalog-level simulation of the in-guide strategy recommended by the HLTDS definition committee, and determine dark energy parameter constraints using a detailed analysis that includes light curve f…

This https://arxiv.org/abs/2403.04324 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Sublinear expectation structure under countable state space
In this study, we propose the sublinear expectation structure under countable state space. To describe an interesting "nonlinear randomized" trial, based on a convex compact domain, we introduce a family of probability measures under countable state space. Corresponding the sublinear expectation operator introduced by S. Peng, we consider the related notation under countable state space. Within the countable state framework, the sublinear expectation can be explicitly calculated by a novel repe…

This https://arxiv.org/abs/2506.03157 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qbi…

UniSim: A Unified Simulator for Time-Coarsened Dynamics of Biomolecules
Molecular Dynamics (MD) simulations are essential for understanding the atomic-level behavior of molecular systems, giving insights into their transitions and interactions. However, classical MD techniques are limited by the trade-off between accuracy and efficiency, while recent deep learning-based improvements have mostly focused on single-domain molecules, lacking transferability to unfamiliar molecular systems. Therefore, we propose \textbf{Uni}fied \textbf{Sim}ulator (UniSim), which levera…

This https://arxiv.org/abs/2506.00839 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

Neural Path Guiding with Distribution Factorization
In this paper, we present a neural path guiding method to aid with Monte Carlo (MC) integration in rendering. Existing neural methods utilize distribution representations that are either fast or expressive, but not both. We propose a simple, but effective, representation that is sufficiently expressive and reasonably fast. Specifically, we break down the 2D distribution over the directional domain into two 1D probability distribution functions (PDF). We propose to model each 1D PDF using a neur…

This https://arxiv.org/abs/2503.17797 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Enhancing Fourier Neural Operators with Local Spatial Features
Partial Differential Equation (PDE) problems often exhibit strong local spatial structures, and effectively capturing these structures is critical for approximating their solutions. Recently, the Fourier Neural Operator (FNO) has emerged as an efficient approach for solving these PDE problems. By using parametrization in the frequency domain, FNOs can efficiently capture global patterns. However, this approach inherently overlooks the critical role of local spatial features, as frequency-domain…

This https://arxiv.org/abs/2505.21920 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective
The Segment Anything Model (SAM), a vision foundation model, exhibits impressive zero-shot capabilities in general tasks but struggles in specialized domains. Parameter-efficient fine-tuning (PEFT) is a promising approach to unleash the potential of SAM in novel scenarios. However, existing PEFT methods for SAM neglect the domain-invariant relations encoded in the pre-trained model. To bridge this gap, we propose InfoSAM, an information-theoretic approach that enhances SAM fine-tuning by distil…

This https://arxiv.org/abs/2505.21427 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Policy Induction: Predicting Startup Success via Explainable Memory-Augmented In-Context Learning
Early-stage startup investment is a high-risk endeavor characterized by scarce data and uncertain outcomes. Traditional machine learning approaches often require large, labeled datasets and extensive fine-tuning, yet remain opaque and difficult for domain experts to interpret or improve. In this paper, we propose a transparent and data-efficient investment decision framework powered by memory-augmented large language models (LLMs) using in-context learning (ICL). Central to our method is a natu…

@… I can think of ways you might do it by getting people to set a DNS CNAME, for example, so they own the domain *but* authentication is controlled by a service. In theory, this allows ownership because you can replace it with a competitor.
AP is probably harder, but I don't think it's impossible, based on my cursory reading of the …

This https://arxiv.org/abs/2403.15582 has been replaced.
initial toot: https://mastoxiv.page/@…

Fast real-time arbitrary waveform generation using graphic processing units
Real-time arbitrary waveform generation (AWG) is essential in various engineering and research applications. This paper introduces a novel AWG architecture using an NVIDIA graphics processing unit (GPU) and a commercially available high-speed digital-to-analog converter (DAC) card, both running on a desktop personal computer (PC). The GPU accelerates the "embarrassingly" data-parallel additive synthesis framework for AWG, and the DAC reconstructs the generated waveform in the analog domain at h…

Novel Benchmark for NER in the Wastewater and Stormwater Domain
Franco Alberto Cardillo, Franca Debole, Francesca Frontini, Mitra Aelami, Nan\'ee Chahinian, Serge Conrad
https://arxiv.org/abs/2506.01938

Novel Benchmark for NER in the Wastewater and Stormwater Domain
Effective wastewater and stormwater management is essential for urban sustainability and environmental protection. Extracting structured knowledge from reports and regulations is challenging due to domainspecific terminology and multilingual contexts. This work focuses on domain-specific Named Entity Recognition (NER) as a first step towards effective relation and information extraction to support decision making. A multilingual benchmark is crucial for evaluating these methods. This study deve…

Evaluating the Impact of Privacy-Preserving Federated Learning on CAN Intrusion Detection
Gabriele Digregorio, Elisabetta Cainazzo, Stefano Longari, Michele Carminati, Stefano Zanero
https://arxiv.org/abs/2506.04978

Evaluating the Impact of Privacy-Preserving Federated Learning on CAN Intrusion Detection
The challenges derived from the data-intensive nature of machine learning in conjunction with technologies that enable novel paradigms such as V2X and the potential offered by 5G communication, allow and justify the deployment of Federated Learning (FL) solutions in the vehicular intrusion detection domain. In this paper, we investigate the effects of integrating FL strategies into the machine learning-based intrusion detection process for on-board vehicular networks. Accordingly, we propose a …

Ich hab inzwischen Ibis-Wiki über meine Domain rabenheist.de laufen und hab angefangen, erste Artikel in meine persönliche Wissensdatenbank einzugeben.
Die Föderation mit der Flagship-Instanz unter ibis.wiki klappt auch, meine Instanz wird inzwischen unter den noch wenigen bestehenden Instanzen geführt.
https://rabenheist.de/

Beware! The AI Act Can Also Apply to Your AI Research Practices
Alina Wernick, Kristof Meding
https://arxiv.org/abs/2506.03218 https://

Beware! The AI Act Can Also Apply to Your AI Research Practices
The EU has become one of the vanguards in regulating the digital age. A particularly important regulation in the Artificial Intelligence (AI) domain is the EU AI Act, which entered into force in 2024. The AI Act specifies -- due to a risk-based approach -- various obligations for providers of AI systems. These obligations, for example, include a cascade of documentation and compliance measures, which represent a potential obstacle to science. But do these obligations also apply to AI researcher…

Our colleague Ebrahim Norouzi is presenting ConExion: Concept Extraction with Large Language Models, yoint work with Sven Hertling. Comprehensive Prompt Engineering Study of LLM-based concept extraction for domain coverage evaluation of ontologies.
arxive version: https://arxiv.org/abs/2504.12915…

ConExion: Concept Extraction with Large Language Models
In this paper, an approach for concept extraction from documents using pre-trained large language models (LLMs) is presented. Compared with conventional methods that extract keyphrases summarizing the important information discussed in a document, our approach tackles a more challenging task of extracting all present concepts related to the specific domain, not just the important ones. Through comprehensive evaluations of two widely used benchmark datasets, we demonstrate that our method improv…

This https://arxiv.org/abs/2506.02197 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution
This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. The goal of this challenge is two fold, (i) restore RAW images with blur and noise degradations, (ii) upscale RAW Bayer images by 2x, considering unknown noise and blur. In the…

This https://arxiv.org/abs/2505.20089 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

Homophily Enhanced Graph Domain Adaptation
Graph Domain Adaptation (GDA) transfers knowledge from labeled source graphs to unlabeled target graphs, addressing the challenge of label scarcity. In this paper, we highlight the significance of graph homophily, a pivotal factor for graph domain alignment, which, however, has long been overlooked in existing approaches. Specifically, our analysis first reveals that homophily discrepancies exist in benchmarks. Moreover, we also show that homophily discrepancies degrade GDA performance from bot…

This https://arxiv.org/abs/2308.03734 has been replaced.
link: https://scholar.google.com/scholar?q=a

Labeling without Seeing? Blind Annotation for Privacy-Preserving Entity Resolution
The entity resolution problem requires finding pairs across datasets that belong to different owners but refer to the same entity in the real world. To train and evaluate solutions (either rule-based or machine-learning-based) to the entity resolution problem, generating a ground truth dataset with entity pairs or clusters is needed. However, such a data annotation process involves humans as domain oracles to review the plaintext data for all candidate record pairs from different parties, which…

once again love whenever i come across an overly specific meme, like what real friend of the creator is getting ribbed here

Heute vor 62 Jahren: Am 6. Juni 1963 zündeten die #USA im Rahmen von Operation Storax die Atombombe "Apshapa". Storax war eine Serie von #Kernwaffentests bei der 62/63 insgesamt 47 Bomben im Testgebiet in #Nevada

This https://arxiv.org/abs/2408.02541 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Modelling power-law ultrasound absorption using a time-fractional, static memory, Fourier pseudo-spectral method
We describe and implement a numerical method for modelling the frequency-dependent power-law absorption of ultrasound in tissue, as governed by the first order linear wave equations with a loss taking the form of a fractional time derivative. The (Caputo) fractional time derivative requires the full problem history which is contained within an iterative procedure. The resulting numerical method requires a fixed (static) memory cost irrespective of the number of time steps. The spatial domain is…

This https://arxiv.org/abs/2412.19480 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Inequalities between Dirichlet and Neumann Eigenvalues on Surfaces
For a bounded Lipschitz domain $Σ$ in a Riemannian surface $M$ satisfying certain curvature condition, we prove that $$μ_{3-β_1} \leq λ_{1},$$ where $μ_k$ ($λ_k$ resp.) is the $k$-th Neumann (Dirichlet resp.) Laplacian eigenvalue on $Σ$ and $β_1$ is the first Betti number of $Σ.$ If $Σ$ is smooth and simply connected, we can further derive the strict inequality $ μ_{3}< λ_{1}. $ This extends previous results on the Euclidean space to various curved surfaces, including the flat cylin…

This https://arxiv.org/abs/2505.14470 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

PAST: Phonetic-Acoustic Speech Tokenizer
We present PAST, a novel end-to-end framework that jointly models phonetic information alongside signal reconstruction, eliminating the need for external pretrained models. Unlike previous approaches that rely on pretrained self-supervised models, PAST employs supervised phonetic data, directly integrating domain knowledge into the tokenization process via auxiliary tasks. Additionally, we introduce a streamable, causal variant of PAST, enabling real-time speech applications. Results demonstrat…

Core-collapse supernova parameter estimation with the upcoming Vera C. Rubin Observatory
Andrea Simongini, F. Ragosta, I. Di Palma, S. Piranomonte
https://arxiv.org/abs/2506.04184

Core-collapse supernova parameter estimation with the upcoming Vera C. Rubin Observatory
The Vera Rubin Observatory's Legacy Survey of Space and Time (LSST) is expected to revolutionize time-domain optical astronomy as we know it. With its unprecedented depth, the LSST will survey the southern hemisphere sky, generating nearly 32 trillion observations over its nominal 10-year operation. Among these, approximately 10 million will be supernovae (SNe). These observations will uniquely characterize the SN population, enabling studies of known and rare SN types, detailed parameterizatio…

BEAR: BGP Event Analysis and Reporting
Hanqing Li, Melania Fedeli, Vinay Kolar, Diego Klabjan
https://arxiv.org/abs/2506.04514 https://

BEAR: BGP Event Analysis and Reporting
The Internet comprises of interconnected, independently managed Autonomous Systems (AS) that rely on the Border Gateway Protocol (BGP) for inter-domain routing. BGP anomalies--such as route leaks and hijacks--can divert traffic through unauthorized or inefficient paths, jeopardizing network reliability and security. Although existing rule-based and machine learning methods can detect these anomalies using structured metrics, they still require experts with in-depth BGP knowledge of, for example…

Frequency Automata: A novel formal model of hybrid systems in combined time and frequency domains
Moon Kim, Avinash Malik, Partha Roop
https://arxiv.org/abs/2506.00251

Frequency Automata: A novel formal model of hybrid systems in combined time and frequency domains
Hybrid systems are mostly modelled, simulated, and verified in the time domain by computer scientists. Engineers, however, use both frequency and time domain modelling due to their distinct advantages. For example, frequency domain modelling is better suited for control systems, using features such as spectra of the signal. Considering this, we introduce, for the first time, a formal model called frequency automata for hybrid systems modelling and simulation, which are represented in combined t…

Human-In-The-Loop Workflow for Neuro- Symbolic Scholarly Knowledge Organization
Lena John, Tim Wittenborg, S\"oren Auer, Oliver Karras
https://arxiv.org/abs/2506.03221

Human-In-The-Loop Workflow for Neuro- Symbolic Scholarly Knowledge Organization
As the volume of scientific literature continues to grow, efficient knowledge organization is an increasingly challenging task. Traditional structuring of scientific content is time-consuming and requires significant domain expertise, increasing the need for tool support. Our goal is to create a Human-in-the-Loop (HITL) workflow that supports researchers in creating and structuring scientific knowledge, leveraging neural models and knowledge graphs, exemplified using the Open Research Knowledge…

This https://arxiv.org/abs/2403.10282 has been replaced.
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Non-Conforming Structure Preserving Finite Element Method for Doubly Diffusive Flows on Bounded Lipschitz Domains
We study a stationary model of doubly diffusive flows with temperature-dependent viscosity on bounded Lipschitz domains in two and three dimensions. A new well-posedness and regularity analysis of weak solutions under minimal assumptions on domain geometry and data regularity are established. A fully non-conforming finite element method based on Crouzeix-Raviart elements, which ensures locally exactly divergence-free velocity fields is explored. Unlike previously proposed schemes, this discreti…

Localized Functional Principal Component Analysis Based on Covariance Structure
Maria Laura Battagliola, Jan O. Bauer
https://arxiv.org/abs/2506.02836 http…

Localized Functional Principal Component Analysis Based on Covariance Structure
Functional principal component analysis (FPCA) is a widely used technique in functional data analysis for identifying the primary sources of variation in a sample of random curves. The eigenfunctions obtained from standard FPCA typically have non-zero support across the entire domain. In applications, however, it is often desirable to analyze eigenfunctions that are non-zero only on specific portions of the original domain-and exhibit zero regions when little is contributed to a specific direct…

Ich hab vor ca. 2 stunden, 4 domains tranferiert, 3 de und eine info domain, aus welchen gründen auch imner, war bei der info domain eine andere mailadresse interlegt als bei den de domains. Nun wurde, weil ich die info domain schon mal transferieren wollte und da wurde, warum auch die hinterlegte mailadresse geändert und da der tranfsfer misslamg, wollte ich wissen wann die sperrung endet ?
Ja und da heute freitag ist, wird antwort wohl erst am montag komnen.

This https://arxiv.org/abs/2407.15742 has been replaced.
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New solutions for the Lane-Emden problem on planar domains
We consider the Lane-Emden problem on planar domains. When the exponent is large, the existence and multiplicity of solutions strongly depend on the geometric properties of the domain, which also deeply affect their qualitative behavior. Remarkably, a wide variety of solutions, both positive and sign-changing, have been found when the exponent is sufficiently large. In this paper, we focus on this topic and fine new sign-changing solutions that exhibit an unexpected concentration phenomenon as …

Today the #SemDH2025 workshop takes place alongside #ESWC2025. I’m happy that Philipp Tögel will present our paper on Data-rich Web Annotations. We discuss how web annotations, a W3C standard, can be leveraged to include complex analysis with domain-specific data models as

This https://arxiv.org/abs/2503.18617 has been replaced.
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Scaling Laws for Emulation of Stellar Spectra
Neural network-based emulators for the inference of stellar parameters and elemental abundances represent an increasingly popular methodology in modern spectroscopic surveys. However, these approaches are often constrained by their emulation precision and domain transfer capabilities. Greater generalizability has previously been achieved only with significantly larger model architectures, as demonstrated by Transformer-based models in natural language processing. This observation aligns with ne…

This https://arxiv.org/abs/2503.16456 has been replaced.
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Position: Beyond Assistance -- Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care
This position paper argues for a fundamental shift in how Large Language Models (LLMs) are integrated into the mental health care domain. We advocate for their role as co-creators rather than mere assistive tools. While LLMs have the potential to enhance accessibility, personalization, and crisis intervention, their adoption remains limited due to concerns about bias, evaluation, over-reliance, dehumanization, and regulatory uncertainties. To address these challenges, we propose two structured …

“Music has the capacity to ‘render nonsonorous forces sonorous’ - that is, it makes audible the general flux of forces and movements that constitute natural becoming: duration, pressure, tension and relaxation, attraction and repulsion, consistency and dissolution, and so on - pure tendencies, intensities, and events presented independently of the world of bodies and objects that constitutes the domain of representation and figuration.”

Heute vor 62 Jahren: Am 6. Juni 1963 zündeten die #USA im Rahmen von Operation Storax die Atombombe "Hutia". Storax war eine Serie von #Kernwaffentests bei der 62/63 insgesamt 47 Bomben im Testgebiet in #Nevada

A Generalized Graph Signal Processing Framework for Multiple Hypothesis Testing over Networks
Xingchao Jian, Martin G\"olz, Feng Ji, Wee Peng Tay, Abdelhak M. Zoubir
https://arxiv.org/abs/2506.03496

A Generalized Graph Signal Processing Framework for Multiple Hypothesis Testing over Networks
We consider the multiple hypothesis testing (MHT) problem over the joint domain formed by a graph and a measure space. On each sample point of this joint domain, we assign a hypothesis test and a corresponding $p$-value. The goal is to make decisions for all hypotheses simultaneously, using all available $p$-values. In practice, this problem resembles the detection problem over a sensor network during a period of time. To solve this problem, we extend the traditional two-groups model such that …

Empirical Evaluation of Generalizable Automated Program Repair with Large Language Models
Viola Campos, Ridwan Shariffdeen, Adrian Ulges, Yannic Noller
https://arxiv.org/abs/2506.03283

Empirical Evaluation of Generalizable Automated Program Repair with Large Language Models
Automated Program Repair (APR) proposes bug fixes to aid developers in maintaining software. The state of the art in this domain focuses on using LLMs, leveraging their strong capabilities to comprehend specifications in natural language and to generate program code. Recent works have shown that LLMs can be used to generate repairs. However, despite the APR community's research achievements and several industry deployments in the last decade, APR still lacks the capabilities to generalize broad…

Heute vor 57 Jahren: Am 6. Juni 1968 zündeten die USA im Rahmen von Operation #Crosstie fünf #Atombomben "Tub 1-5" simultan. Crosstie war eine Serie von Tests zwischen 67/68 bei der insgesamt 48 #Kernwaffentests

Initial Characterization of Stellar Photometry of Roman images from the OpenUniverse Simulations
Lauren Aldoroty, Daniel Scolnic, Arun Kannawadi, Rob Knop, Benjamin Rose, Rebekah Hounsell, Michael Troxel
https://arxiv.org/abs/2506.04332

Initial Characterization of Stellar Photometry of Roman images from the OpenUniverse Simulations
NASA's Nancy Grace Roman Space Telescope (Roman) will provide an opportunity to study dark energy with unprecedented precision and accuracy using several techniques, including measurements of high-$z$ Type Ia Supernovae (SNe Ia, $z \lesssim 3.0$) via the High-Latitude Time Domain Survey (HLTDS). In this work, we do an initial "benchmark" characterization of the photometric repeatability of stellar fluxes, which must be below $1\%$ when sky noise is subdominant in order xto enable a number of ca…

Learning Parametric Convex Functions
Maximilian Schaller, Alberto Bemporad, Stephen Boyd
https://arxiv.org/abs/2506.04183 https://arx…

Learning Parametric Convex Functions
A parametrized convex function depends on a variable and a parameter, and is convex in the variable for any valid value of the parameter. Such functions can be used to specify parametrized convex optimization problems, i.e., a convex optimization family, in domain specific languages for convex optimization. In this paper we address the problem of fitting a parametrized convex function that is compatible with disciplined programming, to some given data. This allows us to fit a function arising i…

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa RYu
https://arxiv.org/abs/2506.00056

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Artificial intelligence (AI) is reshaping inverse design across manufacturing domain, enabling high-performance discovery in materials, products, and processes. However, purely data-driven approaches often struggle in realistic settings characterized by sparse data, high-dimensional design spaces, and nontrivial physical constraints. This perspective argues for a new generation of design systems that transcend black-box modeling by integrating domain knowledge, physics-informed learning, and in…

An iterative tangential interpolation framework for model reduction of MIMO systems
Jared Jonas, Bassam Bamieh
https://arxiv.org/abs/2506.03410 https://

An iterative tangential interpolation framework for model reduction of MIMO systems
We consider model reduction of large-scale MIMO systems using tangential interpolation in the frequency domain. Our scheme is related to the recently-developed Adaptive Antoulas--Anderson (AAA) algorithm, which is an iterative algorithm that uses concepts from the Loewner framework. Our algorithm uses low-rank interpolation and iteratively adds interpolation points based on several criteria including minimizing maximum errors. We show there is freedom in the interpolation point selection method…

This https://arxiv.org/abs/2412.20697 has been replaced.
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An inverse obstacle scattering problem with passive data in the time domain
This work considers a time domain inverse acoustic obstacle scattering problem due to passive data. Motivated by the Helmholtz-Kirchhoff identity in the frequency domain, we propose to relate the time domain measurement data in passive imaging to an approximate data set given by the subtraction of two scattered wave fields. We propose a time domain linear sampling method for the approximate data set and show how to tackle the measurement data in passive imaging. An imaging functional is built b…

AURA: Agentic Upskilling via Reinforced Abstractions
Alvin Zhu, Yusuke Tanaka, Dennis Hong
https://arxiv.org/abs/2506.02507 https://a…

AURA: Agentic Upskilling via Reinforced Abstractions
We study the combinatorial explosion involved in translating high-level task prompts into deployable control policies for agile robots through multi-stage reinforcement learning. We introduce AURA (Agentic Upskilling via Reinforced Abstractions), a schema-centric curriculum RL framework that leverages Large Language Models (LLMs) as autonomous designers of multi-stage curricula. AURA transforms user prompts into YAML workflows that encode full reward functions, domain randomization strategies, …

This https://arxiv.org/abs/2504.14822 has been replaced.
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Completing A Systematic Review in Hours instead of Months with Interactive AI Agents
Systematic reviews (SRs) are vital for evidence-based practice in high stakes disciplines, such as healthcare, but are often impeded by intensive labors and lengthy processes that can take months to complete. Due to the high demand for domain expertise, existing automatic summarization methods fail to accurately identify relevant studies and generate high-quality summaries. To that end, we introduce InsightAgent, a human-centered interactive AI agent powered by large language models that revolu…

This https://arxiv.org/abs/2409.14644 has been replaced.
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An Effective Approach to Embedding Source Code by Combining Large Language and Sentence Embedding Models
The advent of large language models (LLMs) has significantly advanced artificial intelligence (AI) in software engineering (SE), with source code embeddings playing a crucial role in tasks such as source code clone detection and source code clustering. However, existing methods for source code embedding, including those based on LLMs, often rely on costly supervised training or fine-tuning for domain adaptation. This paper proposes a novel approach to embedding source code by combining large la…

This https://arxiv.org/abs/2406.07206 has been replaced.
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Mean-Field Magnetohydrodynamics Models as Scaling Limits of Stochastic Induction Equations
We study the asymptotic properties of a stochastic model for the induction equations of the magnetic field in a three dimensional periodic domain. The turbulent velocity field driving the electromotive force on the magnetic field is modeled by a noise white in time. For this model we rigorously take a scaling limit leading to a deterministic model. While in case of isotropic turbulence this produces an additional dissipation in the limit model which influences also the decay rate of the Magneti…

This https://arxiv.org/abs/2411.09063 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

The typical elasticity of a quadratic order
For an atomic domain $D$, the $elasticity$ $ρ(D)$ of $D$ is defined as $\sup\{r/s: π_1\cdots π_r = ρ_1 \cdots ρ_s,~ \text{where each $π_i, ρ_j$ is irreducible}\}$; the elasticity provides a concrete measure of the failure of unique factorization in $D$. Fix a quadratic number field $K$ with discriminant $Δ_K$, and for each positive integer $f$, let $\mathcal{O}_f = \mathbb{Z} + f\mathcal{O}_K$ denote the order of conductor $f$ in $K$. Results of Halter-Koch imply that $\mathcal{O}_f$ ha…

A "Wenlu" Brain System for Multimodal Cognition and Embodied Decision-Making: A Secure New Architecture for Deep Integration of Foundation Models and Domain Knowledge
Liang Geng
https://arxiv.org/abs/2506.00570

A "Wenlu" Brain System for Multimodal Cognition and Embodied Decision-Making: A Secure New Architecture for Deep Integration of Foundation Models and Domain Knowledge
With the rapid penetration of artificial intelligence across industries and scenarios, a key challenge in building the next-generation intelligent core lies in effectively integrating the language understanding capabilities of foundation models with domain-specific knowledge bases in complex real-world applications. This paper proposes a multimodal cognition and embodied decision-making brain system, ``Wenlu", designed to enable secure fusion of private knowledge and public models, unified proc…

XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Ioan-Paul Ciobanu, Andrei-Iulian Hiji, Nicolae-Catalin Ristea, Paul Irofti, Cristian Rusu, Radu Tudor Ionescu
https://arxiv.org/abs/2506.00462

XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Recent advances in audio generation led to an increasing number of deepfakes, making the general public more vulnerable to financial scams, identity theft, and misinformation. Audio deepfake detectors promise to alleviate this issue, with many recent studies reporting accuracy rates close to 99%. However, these methods are typically tested in an in-domain setup, where the deepfake samples from the training and test sets are produced by the same generative models. To this end, we introduce XMAD-…

This https://arxiv.org/abs/2506.00261 has been replaced.
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GPR: Empowering Generation with Graph-Pretrained Retriever
Graph retrieval-augmented generation (GRAG) places high demands on graph-specific retrievers. However, existing retrievers often rely on language models pretrained on plain text, limiting their effectiveness due to domain misalignment and structure ignorance. To address these challenges, we propose GPR, a graph-based retriever pretrained directly on knowledge graphs. GPR aligns natural language questions with relevant subgraphs through LLM-guided graph augmentation and employs a structure-aware…

SVD-Based Graph Fractional Fourier Transform on Directed Graphs and Its Application
Lu Li, Haiye Huo
https://arxiv.org/abs/2506.03925 https://

SVD-Based Graph Fractional Fourier Transform on Directed Graphs and Its Application
Graph fractional Fourier transform (GFRFT) is an extension of graph Fourier transform (GFT) that provides an additional fractional analysis tool for graph signal processing (GSP) by generalizing temporal-vertex domain Fourier analysis to fractional orders. In recent years, a large number of studies on GFRFT based on undirected graphs have emerged, but there are very few studies on directed graphs. Therefore, in this paper, one of our main contributions is to introduce two novel GFRFTs defined o…

This https://arxiv.org/abs/2505.23337 has been replaced.
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Matryoshka Model Learning for Improved Elastic Student Models
Industry-grade ML models are carefully designed to meet rapidly evolving serving constraints, which requires significant resources for model development. In this paper, we propose MatTA, a framework for training multiple accurate Student models using a novel Teacher-TA-Student recipe. TA models are larger versions of the Student models with higher capacity, and thus allow Student models to better relate to the Teacher model and also bring in more domain-specific expertise. Furthermore, multiple…

This https://arxiv.org/abs/2504.09642 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

HBS -- Hardware Build System: A Tcl-based, minimal common abstraction approach for build system for hardware designs
Build systems become an indispensable part of the software implementation and deployment process. New programming languages are released with the build system integrated into the language tools, for example, Go, Rust, or Zig. However, in the hardware description domain, no official build systems have been released with the predominant Hardware Description Languages (HDL) such as VHDL or SystemVerilog. Moreover, hardware design projects are often multilanguage. The paper proposes a new build s…

NetPress: Dynamically Generated LLM Benchmarks for Network Applications
Yajie Zhou, Jiajun Ruan, Eric S. Wang, Sadjad Fouladi, Francis Y. Yan, Kevin Hsieh, Zaoxing Liu
https://arxiv.org/abs/2506.03231

NetPress: Dynamically Generated LLM Benchmarks for Network Applications
Despite growing interest in domain-specific benchmarking of large language models (LLMs) and agents, current evaluations remain limited to static, small-scale datasets, especially in high-stakes tasks like network operations that demand reliability for deployments. We present NetPress, an automated benchmark generation framework for evaluating LLM agents in network applications. NetPress introduces a unified abstraction with state and action, enabling dynamic generation of diverse query sets al…

This https://arxiv.org/abs/2505.10640 has been replaced.
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The Hitchhikers Guide to Production-ready Trustworthy Foundation Model powered Software (FMware)
Foundation Models (FMs) such as Large Language Models (LLMs) are reshaping the software industry by enabling FMware, systems that integrate these FMs as core components. In this KDD 2025 tutorial, we present a comprehensive exploration of FMware that combines a curated catalogue of challenges with real-world production concerns. We first discuss the state of research and practice in building FMware. We further examine the difficulties in selecting suitable models, aligning high-quality domain-s…

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
Ronny Ko, Jiseong Jeong, Shuyuan Zheng, Chuan Xiao, Taewan Kim, Makoto Onizuka, Wonyong Shin
https://arxiv.org/abs/2505.23847

Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership. Yet, cross-domain collaboration shatters the unified trust assumptions behind current alignment and containment techniques. An agent benign in isolation may, when receiving messages from an untrusted peer, leak secrets or viola…

Universal Reusability in Recommender Systems: The Case for Dataset- and Task-Independent Frameworks
Tri Kurniawan Wijaya, Xinyang Shao, Gonzalo Fiz Pontiveros, Edoardo D'Amico
https://arxiv.org/abs/2506.03391

Universal Reusability in Recommender Systems: The Case for Dataset- and Task-Independent Frameworks
Recommender systems are pivotal in delivering personalized experiences across industries, yet their adoption and scalability remain hindered by the need for extensive dataset- and task-specific configurations. Existing systems often require significant manual intervention, domain expertise, and engineering effort to adapt to new datasets or tasks, creating barriers to entry and limiting reusability. In contrast, recent advancements in large language models (LLMs) have demonstrated the transform…

This https://arxiv.org/abs/2412.03318 has been replaced.
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Domain-Agnostic Stroke Lesion Segmentation Using Physics-Constrained Synthetic Data
Segmenting stroke lesions in MRI is challenging due to diverse acquisition protocols that limit model generalisability. In this work, we introduce two physics-constrained approaches to generate synthetic quantitative MRI (qMRI) images that improve segmentation robustness across heterogeneous domains. Our first method, $\texttt{qATLAS}$, trains a neural network to estimate qMRI maps from standard MPRAGE images, enabling the simulation of varied MRI sequences with realistic tissue contrasts. The …

This https://arxiv.org/abs/2504.19583 has been replaced.
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Graph-Based Spectral Decomposition for Parameter Coordination in Language Model Fine-Tuning
This paper proposes a parameter collaborative optimization algorithm for large language models, enhanced with graph spectral analysis. The goal is to improve both fine-tuning efficiency and structural awareness during training. In the proposed method, the parameters of a pre-trained language model are treated as nodes in a graph. A weighted graph is constructed, and Laplacian spectral decomposition is applied to enable frequency-domain modeling and structural representation of the parameter spa…

Textual-Based vs. Thinging Machines Conceptual Modeling
Sabah Al-Fedaghi
https://arxiv.org/abs/2506.02646 https://arxiv.org/pdf/2506.…

Textual-Based vs. Thinging Machines Conceptual Modeling
Software engineers typically interpret the domain description in natural language and translate it into a conceptual model. Three approaches are used in this domain modeling: textual languages, diagrammatic languages, and a mixed based of text and diagrams. According to some researchers, relying on a diagrammatic notation levies certain burdens for designing large models because visual languages are intended to depict everything diagrammatically during a development process but fail to do so fo…

This https://arxiv.org/abs/2402.02160 has been replaced.
link: https://scholar.google.com/scholar?q=a

Data Poisoning for In-context Learning
In the domain of large language models (LLMs), in-context learning (ICL) has been recognized for its innovative ability to adapt to new tasks, relying on examples rather than retraining or fine-tuning. This paper delves into the critical issue of ICL's susceptibility to data poisoning attacks, an area not yet fully explored. We wonder whether ICL is vulnerable, with adversaries capable of manipulating example data to degrade model performance. To address this, we introduce ICLPoison, a speciali…

This https://arxiv.org/abs/2506.00951 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Physics-Informed Neural Networks for the Relativistic Burgers Equation in the Exterior of a Schwarzschild Black Hole
We introduce a Physics-Informed Neural Networks(PINN) to solve a relativistic Burgers equation in the exterior domain of a Schwarzschild black hole. Our main contribution is a PINN architecture that is able to simulate shock wave formations in such curved spacetime, by training a shock- aware network block and introducing a Godunov-inspired residuals in the loss function. We validate our method with numerical experiments with different kinds of initial conditions. We show its ability to reprodu…

This https://arxiv.org/abs/2412.05718 has been replaced.
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RLZero: Direct Policy Inference from Language Without In-Domain Supervision
The reward hypothesis states that all goals and purposes can be understood as the maximization of a received scalar reward signal. However, in practice, defining such a reward signal is notoriously difficult, as humans are often unable to predict the optimal behavior corresponding to a reward function. Natural language offers an intuitive alternative for instructing reinforcement learning (RL) agents, yet previous language-conditioned approaches either require costly supervision or test-time tr…

This https://arxiv.org/abs/2405.20710 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

i$^2$VAE: Interest Information Augmentation with Variational Regularizers for Cross-Domain Sequential Recommendation
Cross-Domain Sequential Recommendation (CDSR) leverages user behaviors across multiple domains to mitigate data sparsity and cold-start challenges in Single-Domain Sequential Recommendation. Existing methods primarily rely on shared users (overlapping users) to learn transferable interest representations. However, these approaches have limited information propagation, benefiting mainly overlapping users and those with rich interaction histories while neglecting non-overlapping (cold-start) and …

This https://arxiv.org/abs/2503.19449 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

VecTrans: Enhancing Compiler Auto-Vectorization through LLM-Assisted Code Transformations
Auto-vectorization is a fundamental optimization for modern compilers to exploit SIMD parallelism. However, state-of-the-art approaches still struggle to handle intricate code patterns, often requiring manual hints or domain-specific expertise. Large language models (LLMs), with their ability to capture intricate patterns, provide a promising solution, yet their effective application in compiler optimizations remains an open challenge due to issues such as hallucinations and a lack of domain-sp…

This https://arxiv.org/abs/2506.01811 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Quantum Circuit Encodings of Polynomial Chaos Expansions
This work investigates the expressive power of quantum circuits in approximating high-dimensional, real-valued functions. We focus on countably-parametric holomorphic maps $u:U\to \mathbb{R}$, where the parameter domain is $U=[-1,1]^{\mathbb{N}}$. We establish dimension-independent quantum circuit approximation rates via the best $n$-term truncations of generalized polynomial chaos (gPC) expansions of these parametric maps, demonstrating that these rates depend solely on the summability exponen…

This https://arxiv.org/abs/2410.00059 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

IDEA: An Inverse Domain Expert Adaptation Based Active DNN IP Protection Method
Illegitimate reproduction, distribution and derivation of Deep Neural Network (DNN) models can inflict economic loss, reputation damage and even privacy infringement. Passive DNN intellectual property (IP) protection methods such as watermarking and fingerprinting attempt to prove the ownership upon IP violation, but they are often too late to stop catastrophic damage of IP abuse and too feeble against strong adversaries. In this paper, we propose IDEA, an Inverse Domain Expert Adaptation based…

CyberGym: Evaluating AI Agents' Cybersecurity Capabilities with Real-World Vulnerabilities at Scale
Zhun Wang, Tianneng Shi, Jingxuan He, Matthew Cai, Jialin Zhang, Dawn Song
https://arxiv.org/abs/2506.02548

CyberGym: Evaluating AI Agents' Cybersecurity Capabilities with Real-World Vulnerabilities at Scale
Large language model (LLM) agents are becoming increasingly skilled at handling cybersecurity tasks autonomously. Thoroughly assessing their cybersecurity capabilities is critical and urgent, given the high stakes in this domain. However, existing benchmarks fall short, often failing to capture real-world scenarios or being limited in scope. To address this gap, we introduce CyberGym, a large-scale and high-quality cybersecurity evaluation framework featuring 1,507 real-world vulnerabilities fo…

Heute vor 59 Jahren: Am 3. Juni 1966 zündeten die USA im Rahmen von Operation #Flintlock die 44. #Atombombe "Tan". Flintlock war eine Serie von Tests zwischen 65/66 bei der insgesamt 47 #Kernwaffentests

This https://arxiv.org/abs/2008.12591 has been replaced.
link: https://scholar.google.com/scholar?q=a

Convergence of adaptive stochastic collocation with finite elements
We consider an elliptic partial differential equation with a random diffusion parameter discretized by a stochastic collocation method in the parameter domain and a finite element method in the spatial domain. We prove convergence of an adaptive algorithm which adaptively enriches the parameter space as well as refines the finite element meshes.

This https://arxiv.org/abs/2505.23419 has been replaced.
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SWE-bench Goes Live!
The issue-resolving task, where a model generates patches to fix real-world bugs, has emerged as a critical benchmark for evaluating the capabilities of large language models (LLMs). While SWE-bench and its variants have become standard in this domain, they suffer from key limitations: they have not been updated since their initial releases, cover a narrow set of repositories, and depend heavily on manual effort for instance construction and environment setup. These factors hinder scalability a…