Tootfinder

Dual-Numbers Reverse AD for Functional Array Languages
Tom Smeding, Miko{\l}aj Konarski, Simon Peyton Jones, Andrew Fitzgibbon
https://arxiv.org/abs/2507.12640

Dual-Numbers Reverse AD for Functional Array Languages
The standard dual-numbers construction works well for forward-mode automatic differentiation (AD) and is attractive due to its simplicity; recently, it also has been adapted to reverse-mode AD, but practical performance, especially on array programs, leaves a lot to be desired. In this paper we introduce first-class support for multidimensional arrays in dual-numbers reverse-mode AD with little to no performance overhead. The algorithm consists of three loosely-coupled components: a semantics-p…

Largest dyadic dual VC-dimension of non-piercing families
Xinqi Huang, Yuzhen Qi, Mingyuan Rong, Zixiang Xu
https://arxiv.org/abs/2506.13606 https://

Largest dyadic dual VC-dimension of non-piercing families
The dyadic dual VC-dimension of a set system \( \mathcal{F} \) is the largest integer \( \ell \) such that there exist \( \ell \) sets \( F_1, F_{2}, \dots, F_\ell \in \mathcal{F} \), where every pair \( \{i, j\} \in \binom{[\ell]}{2} \) is witnessed by an element \( a_{i,j} \in F_i \cap F_j \) that does not belong to any other set \( F_k \) with \( k \in [\ell] \setminus \{i, j\} \). In this paper, we determine the largest dyadic dual VC-dimension of a non-piercing family is exactly $4$, provi…

HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD
Hanwen Liu, Yuhe Huang, Yifeng Gong, Yanjie Zhai, Jiaxuan Lu
https://arxiv.org/abs/2507.12133

HyDRA: A Hybrid Dual-Mode Network for Closed- and Open-Set RFFI with Optimized VMD
Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Fingerprint Identification (RFFI) offers a non-cryptographic solution by exploiting hardware-induced signal distortions. This paper proposes HyDRA, a Hybrid Dual-mode RF Architecture that integrates an optimized Variational Mode Decomposition (VMD) with a novel architecture based on the fusion of Convolutional Neural Networks (CNNs), Transformers, and Ma…

DiFuse-Net: RGB and Dual-Pixel Depth Estimation using Window Bi-directional Parallax Attention and Cross-modal Transfer Learning
Kunal Swami, Debtanu Gupta, Amrit Kumar Muduli, Chirag Jaiswal, Pankaj Kumar Bajpai
https://arxiv.org/abs/2506.14709

DiFuse-Net: RGB and Dual-Pixel Depth Estimation using Window Bi-directional Parallax Attention and Cross-modal Transfer Learning
Depth estimation is crucial for intelligent systems, enabling applications from autonomous navigation to augmented reality. While traditional stereo and active depth sensors have limitations in cost, power, and robustness, dual-pixel (DP) technology, ubiquitous in modern cameras, offers a compelling alternative. This paper introduces DiFuse-Net, a novel modality decoupled network design for disentangled RGB and DP based depth estimation. DiFuse-Net features a window bi-directional parallax atte…

Trump Media and Technology Group files an S-1 with the US SEC to launch a spot Bitcoin and Ethereum ETF, allocating 75% to bitcoin and 25% to ether (Oliver Knight/CoinDesk)
https://www.coindesk.com/business/2025/06/16/d…

Donald Trump's Truth Social Files for Dual BTC and ETH ETF
The move follows registration for a standalone Truth Social bitcoin ETF earlier this month.

Long-time storage of a decoherence-free subspace logical qubit in a dual-type quantum memory
Y. L. Xu, L. Zhang, C. Zhang, Y. K. Wu, Y. Y. Chen, C. X. Huang, Z. B. Cui, R. Yao, W. Q. Lian, J. Y. Ma, W. X. Guo, B. X. Qi, P. Y. Hou, Y. F. Pu, Z. C. Zhou, L. He, L. M. Duan
https://arxiv.org/abs/2507.13320

Long-time storage of a decoherence-free subspace logical qubit in a dual-type quantum memory
A quantum memory is an essential element for quantum computation, quantum network and quantum metrology. Previously, a single-qubit quantum memory with a coherence time of about an hour has been realized in a dual-species setup where a coolant ion provides sympathetic cooling for a memory ion of different species. However, the frequent random position hopping between the ions in the room-temperature trap limits the technique there only applicable to single-qubit storage. Here we report a multi-…

Dual Protection Ring: User Profiling Via Differential Privacy and Service Dissemination Through Private Information Retrieval
Imdad Ullah, Najm Hassan, Tariq Ahamed Ahangar, Zawar Hussain Shah, Mehregan Mahdavi Andrew Levula
https://arxiv.org/abs/2506.13170

Dual Protection Ring: User Profiling Via Differential Privacy and Service Dissemination Through Private Information Retrieval
User profiling is crucial in providing personalised services, as it relies on analysing user behaviour and preferences to deliver targeted services. This approach enhances user experience and promotes heightened engagement. Nevertheless, user profiling also gives rise to noteworthy privacy considerations due to the extensive tracking and monitoring of personal data, potentially leading to surveillance or identity theft. We propose a dual-ring protection mechanism to protect user privacy by exam…

Novel Approach to Dual-Channel Estimation in Integrated Sensing and Communications for 6G
Alejandro Castilla, Sa\'ul Fenollosa, Monika Drozdowska, Alejandro Lopez-Escudero, Sergio Mic\`o-Rosa, Narcis Cardona
https://arxiv.org/abs/2507.12221

Novel Approach to Dual-Channel Estimation in Integrated Sensing and Communications for 6G
Integrated Sensing and Communication (ISAC) design is crucial for 6G and harmonizes environmental data sensing with communication, emphasizing the need to understand and model these elements. This paper delves into dual-channel models for ISAC, employing channel extraction techniques to validate and enhance accuracy. Focusing on millimeter wave (mmWave) radars, it explores the extraction of the bistatic sensing channel from monostatic measurements and subsequent communication channel estimation…

The $L_{p}$ Dual Minkowski Problem for Group-Invariant Convex Bodies
Junjie Shan
https://arxiv.org/abs/2507.13233 https://arxiv.org/p…

The $L_{p}$ Dual Minkowski Problem for Group-Invariant Convex Bodies
This paper studies the $L_p$ dual Minkowski problem for all $q > 0$ and $p \in \mathbb{R}$. We establish the existence of solutions for group-invariant convex bodies (which may not be origin-symmetric), covering two major open problems as special cases: the $L_p$ Minkowski problem ($q = n, p \in \mathbb{R}$) and the dual Minkowski problem ($p = 0, q > 0$).

Convergence Analysis of a Dual-Wind Discontinuous Galerkin Method for an Elliptic Optimal Control Problem with Control Constraints
Satyajith Bommana Boyana, Thomas Lewis, Sijing Liu, Yi Zhang
https://arxiv.org/abs/2506.12330

Convergence Analysis of a Dual-Wind Discontinuous Galerkin Method for an Elliptic Optimal Control Problem with Control Constraints
This paper investigates a symmetric dual-wind discontinuous Galerkin (DWDG) method for solving an elliptic optimal control problem with control constraints. The governing constraint is an elliptic partial differential equation (PDE), which is discretized using the symmetric DWDG approach. We derive error estimates in the energy norm for both the state and the adjoint state, as well as in the $L^2$ norm of the control variable. Numerical experiments are provided to demonstrate the robustness and…

3D FlowMatch Actor: Unified 3D Policy for Single- and Dual-Arm Manipulation
Nikolaos Gkanatsios, Jiahe Xu, Matthew Bronars, Arsalan Mousavian, Tsung-Wei Ke, Katerina Fragkiadaki
https://arxiv.org/abs/2508.11002

3D FlowMatch Actor: Unified 3D Policy for Single- and Dual-Arm Manipulation
We present 3D FlowMatch Actor (3DFA), a 3D policy architecture for robot manipulation that combines flow matching for trajectory prediction with 3D pretrained visual scene representations for learning from demonstration. 3DFA leverages 3D relative attention between action and visual tokens during action denoising, building on prior work in 3D diffusion-based single-arm policy learning. Through a combination of flow matching and targeted system-level and architectural optimizations, 3DFA achieve…

More than 60% of double-peaked narrow emission lines not related to dual galaxy systems?
Zhang XueGuang (GXU)
https://arxiv.org/abs/2507.12893 https://

More than 60% of double-peaked narrow emission lines not related to dual galaxy systems?
Dual galaxy system (DGS) is one of the widely accepted scenarios to explain the double-peaked narrow emission lines (DPNELs) due to orbital motions of the two galaxies in a merging system. After considering no physical connections between two independent narrow emission line regions in two galaxies in one DGS, there should be no correlations between flux ratios $R_{R}$ of red-shifted narrow emission components from one galaxy and flux ratios $R_{B}$ of blue-shifted narrow emission components fr…

Interactive Hybrid Rice Breeding with Parametric Dual Projection
Changjian Chen, Pengcheng Wang, Fei Lyu, Zhuo Tang, Li Yang, Long Wang, Yong Cai, Feng Yu, Kenli Li
https://arxiv.org/abs/2507.11848

Interactive Hybrid Rice Breeding with Parametric Dual Projection
Hybrid rice breeding crossbreeds different rice lines and cultivates the resulting hybrids in fields to select those with desirable agronomic traits, such as higher yields. Recently, genomic selection has emerged as an efficient way for hybrid rice breeding. It predicts the traits of hybrids based on their genes, which helps exclude many undesired hybrids, largely reducing the workload of field cultivation. However, due to the limited accuracy of genomic prediction models, breeders still need t…

I officially hate press fit connectors. No idea how you're supposed to do these in low volume / prototyping. Oshpark's hole tolerances probably didn't help.
But I think they're in and hopefully i didn't crack any MLCCs in the process.

R\'enyi-Induced Information Geometry and Hartigan's Prior Family
Rebecca Maria Kuntz, Heinrich von Campe, Bj\"orn Malte Sch\"afer
https://arxiv.org/abs/2506.12028

Rényi-Induced Information Geometry and Hartigan's Prior Family
We derive the information geometry induced by the statistical Rényi divergence, namely its metric tensor, its dual parametrized connections, as well as its dual Laplacians. Based on these results, we demonstrate that the Rényi-geometry, though closely related, differs in structure from Amari's well-known $α$-geometry. Subsequently, we derive the canonical uniform prior distributions for a statistical manifold endowed with a Rényi-geometry, namely the dual Rényi-covolumes. We find that the …

Dual LiDAR-Based Traffic Movement Count Estimation at a Signalized Intersection: Deployment, Data Collection, and Preliminary Analysis
Saswat Priyadarshi Nayak, Guoyuan Wu, Kanok Boriboonsomsin, Matthew Barth
https://arxiv.org/abs/2507.13073

Dual LiDAR-Based Traffic Movement Count Estimation at a Signalized Intersection: Deployment, Data Collection, and Preliminary Analysis
Traffic Movement Count (TMC) at intersections is crucial for optimizing signal timings, assessing the performance of existing traffic control measures, and proposing efficient lane configurations to minimize delays, reduce congestion, and promote safety. Traditionally, methods such as manual counting, loop detectors, pneumatic road tubes, and camera-based recognition have been used for TMC estimation. Although generally reliable, camera-based TMC estimation is prone to inaccuracies under poor l…

An augmented Lagrangian method for strongly regular minimizers in a class of convex composite optimization problems
Chengjing Wang, Peipei Tang
https://arxiv.org/abs/2507.12040

An augmented Lagrangian method for strongly regular minimizers in a class of convex composite optimization problems
In this paper, we study a class of convex composite optimization problems. We begin by characterizing the equivalence between the primal/dual strong second-order sufficient condition and the dual/primal nondegeneracy condition. Building on this foundation, we derive a specific set of equivalent conditions for the perturbation analysis of the problem. Furthermore, we employ the augmented Lagrangian method (ALM) to solve the problem and provide theoretical guarantees for its performance. Specific…

Testing the effective action approach to bubble nucleation in holography
Oscar Henriksson, Niko Jokela, Xin Li
https://arxiv.org/abs/2507.11622 https://

Testing the effective action approach to bubble nucleation in holography
The nucleation of bubbles during a first-order phase transition has recently been explored using holographic duality, which can provide an important complement to standard perturbative methods. These computations typically require finding static and spatially inhomogeneous saddle points, known as critical bubbles, which correspond in the gravitational dual to solutions of nonlinear partial differential equations. A computationally simpler alternative is to use the gravitational dual to derive t…

Dual Protection Ring: User Profiling Via Differential Privacy and Service Dissemination Through Private Information Retrieval
Imdad Ullah, Najm Hassan, Tariq Ahamed Ahangar, Zawar Hussain Shah, Mehregan Mahdavi Andrew Levula
https://arxiv.org/abs/2506.13170

Dual Protection Ring: User Profiling Via Differential Privacy and Service Dissemination Through Private Information Retrieval
User profiling is crucial in providing personalised services, as it relies on analysing user behaviour and preferences to deliver targeted services. This approach enhances user experience and promotes heightened engagement. Nevertheless, user profiling also gives rise to noteworthy privacy considerations due to the extensive tracking and monitoring of personal data, potentially leading to surveillance or identity theft. We propose a dual-ring protection mechanism to protect user privacy by exam…

Dual Effect of L-Cysteine on the Reorientation and Relaxation of Fe3O4-Decorated Graphene Oxide Liquid Crystals
M. Zhezhu, Y. Melikyan, V. Hayrapetyan, A. Vasilev, H. Gharagulyan
https://arxiv.org/abs/2507.12018

Dual Effect of L-Cysteine on the Reorientation and Relaxation of Fe3O4-Decorated Graphene Oxide Liquid Crystals
Here, we study the dynamics of Fe3O4-decorated L-Cysteine-functionalized GOLC director under an external magnetic field and analyze L-Cysteine's influence on the reorientation and relaxation time of the director. In particular, Fe3O4 nanoparticles were synthesized by solution-combustion method and added for altering orientational properties of GO which we synthesized electrochemically and functionalized by L-Cysteine. In addition, a comprehensive comparison of the director behaviour of GOLC and…

"All I can tell you is what people from Altrincham who were at the protest had to say. They are keen to stress, often unprompted, that they are not racist - they are angry and concerned.
"They cite alarming statistics about asylum seekers accused of sexual assault and rape - statistics that I could not find any evidence to support. They claim that asylum seekers in this hotel are 'robbing shops' - something that the police told me they have 'no knowledge' of.&q…

We spoke to the people protesting outside an asylum seeker hotel in Greater Manchester
Protesters at Cresta Court in Altrincham have been divided only by a dual carriageway

On the paper Optimal dual frames of probabilistic erasures
Shankhadeep Mondal, Ram Narayan Mohapatra
https://arxiv.org/abs/2507.11452 https://

On the paper Optimal dual frames of probabilistic erasures
In the paper Optimal Dual Frames for Probabilistic Erasures, the authors have given conditions under which the canonical dual is claimed to be the unique probability optimal dual for 1-erasure reconstruction. In this paper, we demonstrate via counterexamples that the conditions provided are not sufficient to guarantee uniqueness. We also noticed a mistake in the proof of the theorem and proved the correct version of the theorem with a stronger but valid condition. Furthermore, we show that the …

Is this from the guys that claim they are into "PC, not Linux"? I'd watch that (streaming 12 hours from now, 18 June 2025, 20:00 GMT) ->
Watch Us Build A Linux-Based Dual GPU PC - LIVE - PCWorld
https://www.youtube.com/watch?v=ZG5iYjyIqLM

Training-Free Anomaly Generation via Dual-Attention Enhancement in Diffusion Model
Zuo Zuo, Jiahao Dong, Yanyun Qu, Zongze Wu
https://arxiv.org/abs/2508.11550 https://

Training-Free Anomaly Generation via Dual-Attention Enhancement in Diffusion Model
Industrial anomaly detection (AD) plays a significant role in manufacturing where a long-standing challenge is data scarcity. A growing body of works have emerged to address insufficient anomaly data via anomaly generation. However, these anomaly generation methods suffer from lack of fidelity or need to be trained with extra data. To this end, we propose a training-free anomaly generation framework dubbed AAG, which is based on Stable Diffusion (SD)'s strong generation ability for effective an…

CogDDN: A Cognitive Demand-Driven Navigation with Decision Optimization and Dual-Process Thinking
Yuehao Huang, Liang Liu, Shuangming Lei, Yukai Ma, Hao Su, Jianbiao Mei, Pengxiang Zhao, Yaqing Gu, Yong Liu, Jiajun Lv
https://arxiv.org/abs/2507.11334

CogDDN: A Cognitive Demand-Driven Navigation with Decision Optimization and Dual-Process Thinking
Mobile robots are increasingly required to navigate and interact within unknown and unstructured environments to meet human demands. Demand-driven navigation (DDN) enables robots to identify and locate objects based on implicit human intent, even when object locations are unknown. However, traditional data-driven DDN methods rely on pre-collected data for model training and decision-making, limiting their generalization capability in unseen scenarios. In this paper, we propose CogDDN, a VLM-bas…

Reflective Homework as a Learning Tool: Evidence from Comparing Thirteen Years of Dual vs. Single Submission
Madhur Dixit, Kavya Lalbahadur Joshi, Kaveri Bhalchandra Konde, Edward F. Gehringer
https://arxiv.org/abs/2508.09314

Reflective Homework as a Learning Tool: Evidence from Comparing Thirteen Years of Dual vs. Single Submission
Dual-submission homework, where students submit work, receive feedback and then revise has gained attention as a way to foster reflection and discourage reliance on online answer repositories. This study analyzes 13 years of exam data from a computer architecture course to compare student performance under single versus dual-submission homework conditions. Using pooled t-tests on matched exam questions, we found that dual-submission significantly improved outcomes in a majority of cases. The re…

Hermitian Self-dual Twisted Generalized Reed-Solomon Codes
Chun'e Zhao, Yuxin Han, Wenping Ma, Tongjiang Yan, Yuhua Sun
https://arxiv.org/abs/2508.09687 https://

Hermitian Self-dual Twisted Generalized Reed-Solomon Codes
Self-dual maximum distance separable (MDS) codes over finite fields are linear codes with significant combinatorial and cryptographic applications. Twisted generalized Reed-Solomon (TGRS) codes can be both MDS and self-dual. In this paper, we study a general class of TGRS codes (A-TGRS), which encompasses all previously known special cases. First, we establish a sufficient and necessary condition for an A-TGRS code to be Hermitian self-dual. Furthermore, we present four constructions of self-du…

Note on the linearisation of finite abelian groups
Aur\'elien Djament (CNRS, LAGA)
https://arxiv.org/abs/2507.13047 https://arxiv…

Note on the linearisation of finite abelian groups
If $K$ is a field \textit{with enough roots of unity} and $V$ an abelian group, the $K$-algebra $K[V]$ of the group $V$ is split semisimple, so that the canonical morphism $K[V]\to K^{V^\sharp}$, where $V^\sharp$ denotes the dual group of $V$ (which may be seen as Hom$(V,K^\times)$), is an isomorphism of $K$-algebras. If one removes the assumption that $K$ has enough roots of unity, one can easily deduce from it (by using a base change and Krull-Schmidt) that it remains a $K$-linear isomorphism…

Inversion of Arctic dual-channel sound speed profile based on random airgun signal
Jinbao Weng (Laboratory of Ocean acoustics and Remote Sensing, Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, Fujian 361005, China, Fujian Provincial Key Laboratory of Marine Physical and Geological Processes, Xiamen, Fujian 361005, China), Yubo Qi (State key laboratory of acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China), Yanming Yang (Labora…

Inversion of Arctic dual-channel sound speed profile based on random airgun signal
For the unique dual-channel sound speed profiles of the Canadian Basin and the Chukchi Plateau in the Arctic, based on the propagation characteristics of refracted normal modes under dual-channel sound speed profiles, an inversion method using refracted normal modes for dual-channel sound speed profiles is proposed. This method proposes a dual-parameter representation method for dual-channel sound speed profiles, tailored to the characteristics of dual-channel sound speed profiles. A dispersion…

Dual-View Disentangled Multi-Intent Learning for Enhanced Collaborative Filtering
Shanfan Zhang, Yongyi Lin, Yuan Rao, Chenlong Zhang
https://arxiv.org/abs/2506.11538

Dual-View Disentangled Multi-Intent Learning for Enhanced Collaborative Filtering
Disentangling user intentions from implicit feedback has become a promising strategy to enhance recommendation accuracy and interpretability. Prior methods often model intentions independently and lack explicit supervision, thus failing to capture the joint semantics that drive user-item interactions. To address these limitations, we propose DMICF, a unified framework that explicitly models interaction-level intent alignment while leveraging structural signals from both user and item perspectiv…

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…

Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
Andrzej Cichocki
https://arxiv.org/abs/2506.13984 https://a…

Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
In this paper, we develop a wide class Mirror Descent (MD) algorithms, which play a key role in machine learning. For this purpose we formulated the constrained optimization problem, in which we exploits the Bregman divergence with the Tempesta multi-parametric deformation logarithm as a link function. This link function called also mirror function defines the mapping between the primal and dual spaces and is associated with a very-wide (in fact, theoretically infinite) class of generalized tra…

HELENA: High-Efficiency Learning-based channel Estimation using dual Neural Attention
Miguel Camelo Botero, Esra Aycan Beyazit, Nina Slamnik-Krije\v{s}torac, Johann M. Marquez-Barja
https://arxiv.org/abs/2506.13408

HELENA: High-Efficiency Learning-based channel Estimation using dual Neural Attention
Accurate channel estimation is critical for high-performance Orthogonal Frequency-Division Multiplexing systems such as 5G New Radio, particularly under low signal-to-noise ratio and stringent latency constraints. This letter presents HELENA, a compact deep learning model that combines a lightweight convolutional backbone with two efficient attention mechanisms: patch-wise multi-head self-attention for capturing global dependencies and a squeeze-and-excitation block for local feature refinement…

Vertex functions for bow varieties and their Mirror Symmetry
Tommaso Maria Botta, Hunter Dinkins
https://arxiv.org/abs/2507.13219 https://

Vertex functions for bow varieties and their Mirror Symmetry
In this paper, we study the vertex functions of finite type $A$ bow varieties. Vertex functions are $K$-theoretic analogs of $I$-functions, and 3d mirror symmetry predicts that the $q$-difference equations satisfied by the vertex functions of a variety and its 3d mirror dual are the same after a change of variable swapping the roles of the various parameters. Thus the vertex functions are related by a matrix of elliptic functions, which is expected to be the elliptic stable envelope of M. Agana…

DPNO: A Dual Path Architecture For Neural Operator
Yichen Wang, Wenlian Lu
https://arxiv.org/abs/2507.12719 https://arxiv.org/pdf/250…

DPNO: A Dual Path Architecture For Neural Operator
Neural operators have emerged as a powerful tool for solving partial differential equations (PDEs) and other complex scientific computing tasks. However, the performance of single operator block is often limited, thus often requiring composition of basic operator blocks to achieve better per-formance. The traditional way of composition is staking those blocks like feedforward neural networks, which may not be very economic considering parameter-efficiency tradeoff. In this pa-per, we propose a …

Riemannian curvature of gaussian distribution in dual coordinate system
Prosper Rosaire Mama Assandje, Dongho Joseph, Thomas Bouetou Bouetou
https://arxiv.org/abs/2507.08141

Riemannian curvature of gaussian distribution in dual coordinate system
In this paper, we study the geometric nonlinearity properties, such as curvature and torsion, in a dual coordinate system of the Riemannian manifold defined by the Gaussian distribution. We also give the Amari formulas explicitly in this new coordinate system, which allows us to characterize existing geometric invariants, such as the dual potential function and the Fisher metric.

Weekend Reads
* Societal cost of DDoS
https://thegfce.org/news/estimating-the-societal-cost-of-ddos-attacks-a-dual-lens-model-for-national-impact-assessment/
* HTTP/1.1 desync attacks

Estimating The Societal Cost Of DDoS Attacks: A Dual-Lens Model For National Impact Assessment - The GFCE
A new discussion paper, "Estimating the Societal Cost of DDoS Attacks: A Dual-Lens Model for National Impact Assessment," authored by Carlos Alvarez, Director

Robotic System for Chemical Experiment Automation with Dual Demonstration of End-effector and Jig Operations
Hikaru Sasaki, Naoto Komeno, Takumi Hachimine, Kei Takahashi, Yu-ya Ohnishi, Tetsunori Sugawara, Araki Wakiuchi, Miho Hatanaka, Tomoyuki Miyao, Hiroharu Ajiro, Mikiya Fujii, Takamitsu Matsubara
https://arxiv.org/abs/2506.…

Robotic System for Chemical Experiment Automation with Dual Demonstration of End-effector and Jig Operations
While robotic automation has demonstrated remarkable performance, such as executing hundreds of experiments continuously over several days, it is challenging to design a program that synchronizes the robot's movements with the experimental jigs to conduct an experiment. We propose a concept that enables the automation of experiments by utilizing dual demonstrations of robot motions and jig operations by chemists in an experimental environment constructed to be controlled by a robot. To verify t…

Addressing Local Realism through Bell Tests at Colliders
Matthew Low
https://arxiv.org/abs/2508.10979 https://arxiv.org/pdf/2508.10979

Addressing Local Realism through Bell Tests at Colliders
One of the most notable aspects of quantum systems is that their components can exhibit correlations much stronger than those allowed by classical physics. Two examples of quantum correlations are quantum entanglement and Bell nonlocality, but generally there is a hierarchy of many types of quantum correlations. Among these correlations, Bell nonlocality holds a special place because it plays a dual role in distinguishing theories where local realism is a valid description. A Bell test, which i…

A covariant scalar-field framework for singularity resolution and dark energy
Martin Drobczyk
https://arxiv.org/abs/2506.12464 https://

A covariant scalar-field framework for singularity resolution and dark energy
We present a covariant scalar-field framework that unifies the space-time singularity resolution with dynamic dark energy. The theory extends general relativity by introducing a scalar field $Φ$ whose potential couples to the Lorentz-invariant quantity $X \equiv u_α u_β T^{αβ}_{\mathrm{matter}}$, ensuring manifest covariance. The resulting density-responsive scalar energy $ρ_Φ$ exhibits dual behavior: (i) in high-density regimes, it saturates at $ρ_Φ\leq AM_P^4/2$, providing a Planck-s…

Cost-Efficient Design for 5G-Enabled MEC Servers under Uncertain User Demands
Yunyi Wu (University of Tsukuba), Yongbing Zhang (University of Tsukuba)
https://arxiv.org/abs/2506.13003

Cost-Efficient Design for 5G-Enabled MEC Servers under Uncertain User Demands
Mobile edge computing (MEC) enhances the performance of 5G networks by enabling low-latency, high-speed services through deploying data units of the base station on edge servers located near mobile users. However, determining the optimal capacity of these servers while dynamically offloading tasks and allocating computing resources to meet uncertain user demands presents significant challenges. This paper focuses on the design and planning of edge servers with the dual objectives of minimizing …

Total/dual correlation/coherence, redundancy/synergy, complexity, and O-information for real and complex valued multivariate data
Roberto D. Pascual-Marqui, Kieko Kochi, Toshihiko Kinoshita
https://arxiv.org/abs/2507.08773

Total/dual correlation/coherence, redundancy/synergy, complexity, and O-information for real and complex valued multivariate data
Firstly, assuming Gaussianity, equations for the following information theory measures are presented: total correlation/coherence (TC), dual total correlation/coherence (DTC), O-information, TSE complexity, and the redundancy-synergy index (RSI). Since these measures are functions of the covariance matrix "S" and its inverse "S^-1", the associated Wishart and inverse-Wishart distributions are of note. The DTC is shown here to be the Kullback-Leibler (KL) divergence for the inverse-Wishart pair …

Mapping Emotions in the Brain: A Bi-Hemispheric Neural Model with Explainable Deep Learning
David Freire-Obreg\'on, Agnieszka Dubiel, Prasoon Kumar Vinodkumar, Gholamreza Anbarjafari, Dorota Kami\'nska, Modesto Castrill\'on-Santana
https://arxiv.org/abs/2507.12625

Mapping Emotions in the Brain: A Bi-Hemispheric Neural Model with Explainable Deep Learning
Recent advances have shown promise in emotion recognition from electroencephalogram (EEG) signals by employing bi-hemispheric neural architectures that incorporate neuroscientific priors into deep learning models. However, interpretability remains a significant limitation for their application in sensitive fields such as affective computing and cognitive modeling. In this work, we introduce a post-hoc interpretability framework tailored to dual-stream EEG classifiers, extending the Local Interp…

A universal cutoff phenomenon for mean-field exchange models
Pietro Caputo, Matteo Quattropani, Federico Sau
https://arxiv.org/abs/2506.12816 https://

A universal cutoff phenomenon for mean-field exchange models
We study a broad class of high-dimensional mean-field exchange models, encompassing both noisy and singular dynamics, along with their dual processes. This includes a generalized version of the averaging process as well as some non-reversible extensions of classical exchange dynamics, such as the flat Kac model. Within a unified framework, we analyze convergence to stationarity from worst-case initial data in Wasserstein distance. Our main result establishes a universal cutoff phenomenon at an …

APFL: Analytic Personalized Federated Learning via Dual-Stream Least Squares
Kejia Fan, Jianheng Tang, Zhirui Yang, Feijiang Han, Jiaxu Li, Run He, Yajiang Huang, Anfeng Liu, Houbing Herbert Song, Yunhuai Liu, Huiping Zhuang
https://arxiv.org/abs/2508.10732

APFL: Analytic Personalized Federated Learning via Dual-Stream Least Squares
Personalized Federated Learning (PFL) has presented a significant challenge to deliver personalized models to individual clients through collaborative training. Existing PFL methods are often vulnerable to non-IID data, which severely hinders collective generalization and then compromises the subsequent personalization efforts. In this paper, to address this non-IID issue in PFL, we propose an Analytic Personalized Federated Learning (APFL) approach via dual-stream least squares. In our APFL, w…

The $\ell$-modular local theta correspondence
Justin Trias
https://arxiv.org/abs/2507.11421 https://arxiv.org/pdf/2507.11421

The $\ell$-modular local theta correspondence
We study the validity of the local theta correspondence over a non-archimedean local field in the context of modular representation theory \textit{i.e.} for representations with coefficient fields of positive characteristic. For a symplectic-orthogonal or a unitary-unitary dual pair over a $p$-adic field, we obtain a bijective correspondence, as long as the characteristic of the coefficient field is large enough compared to the size of the dual pair, and call it the modular local theta correspo…

A ringed-space-like structure on coalgebras for noncommutative algebraic geometry
So Nakamura
https://arxiv.org/abs/2506.14689 https://

A ringed-space-like structure on coalgebras for noncommutative algebraic geometry
Inspired by the perspective of Reyes' noncomutative spectral theory, we attempt to develop noncommutative algebraic geometry by introducing ringed coalgebras, which can be thought of as a noncommutative generalization of schemes over a field $k$. These objects arise from fully residually finite-dimensional(RFD) algebras introduced by Reyes and from schemes locally of finite type over $k$. The construction uses the Heyneman-Sweedler finite dual coalgebra and the Takeuchi underlying coalgebra. Wh…

GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
Kecen Li, Zhicong Huang, Xinwen Hou, Cheng Hong
https://arxiv.org/abs/2506.11444 https://

GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
As Diffusion Models (DM) generate increasingly realistic images, related issues such as copyright and misuse have become a growing concern. Watermarking is one of the promising solutions. Existing methods inject the watermark into the single-domain of initial Gaussian noise for generation, which suffers from unsatisfactory robustness. This paper presents the first dual-domain DM watermarking approach using a pipelined injector to consistently embed watermarks in both the spatial and frequency d…

Brazil’s ANPD Preliminary Study on Generative AI highlights the dual nature of data protection law: balancing rights with technological innovation
https://fpf.org/blog/brazils-anpd-prel

Torsion Theories in a Non-pointed Context
Andrea Cappelletti, Andrea Montoli
https://arxiv.org/abs/2506.13349 https://arxiv.org/pdf/2…

Torsion Theories in a Non-pointed Context
We study a non-pointed version of the notion of torsion theory in the framework of categories equipped with a posetal monocoreflective subcategory such that the coreflector inverts monomorphisms. We explore the connections of such torsion theories with factorization systems and categorical Galois structures. We describe several examples of these torsion theories, in the dual of elementary toposes, in varieties of universal algebras used as models for non-classical logic, and in coslices of the …

Research on Quality Measurement and Dynamic Transmission of Higher Education in China from the Perspective of Dual Circulation: An Empirical Analysis Based on Entropy Weight-TOPSIS and PVAR Models
Zhangming Yang, Xiaoting Yin, Dahai Zhang
https://arxiv.org/abs/2508.09216

Research on Quality Measurement and Dynamic Transmission of Higher Education in China from the Perspective of Dual Circulation: An Empirical Analysis Based on Entropy Weight-TOPSIS and PVAR Models
Drawing on the new pattern of 'dual circulation', an evaluation system for the development level of China's higher education has been constructed, utilizing data from Chinese provinces over the period 2020 to 2022. Initially, the evaluation model is established, followed by the screening of initial indicators through correlation analysis. Subsequently, an entropy weight-TOPSIS model are employed for static quantification, and the PVAR model is introduced for the first time to describe the dynam…

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance
Peizhang Shao, Linrui Xu, Jinxi Wang, Wei Zhou, Xingyu Wu
https://arxiv.org/abs/2507.07748

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance
This paper establishes the first comprehensive review of Large Language Models (LLMs) applied within the legal domain. It pioneers an innovative dual lens taxonomy that integrates legal reasoning frameworks and professional ontologies to systematically unify historical research and contemporary breakthroughs. Transformer-based LLMs, which exhibit emergent capabilities such as contextual reasoning and generative argumentation, surmount traditional limitations by dynamically capturing legal seman…

Live Improvisation For Dual Vintage Moog Modular Synthesizers & Drums
https://www.synthtopia.com/content/2025/07/20/live-improvisation-for-dual-vin…

Live Improvisation For Dual Vintage Moog Modular Synthesizers & Drums
The jam features an amazing set of instruments, including dual Moog modular systems, an Oberheim Eight Voice SEM and a Roland Jupiter-8. 

DualPhys-GS: Dual Physically-Guided 3D Gaussian Splatting for Underwater Scene Reconstruction
Jiachen Li, Guangzhi Han, Jin Wan, Yuan Gao, Delong Han
https://arxiv.org/abs/2508.09610

DualPhys-GS: Dual Physically-Guided 3D Gaussian Splatting for Underwater Scene Reconstruction
In 3D reconstruction of underwater scenes, traditional methods based on atmospheric optical models cannot effectively deal with the selective attenuation of light wavelengths and the effect of suspended particle scattering, which are unique to the water medium, and lead to color distortion, geometric artifacts, and collapsing phenomena at long distances. We propose the DualPhys-GS framework to achieve high-quality underwater reconstruction through a dual-path optimization mechanism. Our approac…

LLM-Driven Dual-Level Multi-Interest Modeling for Recommendation
Ziyan Wang, Yingpeng Du, Zhu Sun, Jieyi Bi, Haoyan Chua, Tianjun Wei, Jie Zhang
https://arxiv.org/abs/2507.10917

LLM-Driven Dual-Level Multi-Interest Modeling for Recommendation
Recently, much effort has been devoted to modeling users' multi-interests based on their behaviors or auxiliary signals. However, existing methods often rely on heuristic assumptions, e.g., co-occurring items indicate the same interest of users, failing to capture user multi-interests aligning with real-world scenarios. While large language models (LLMs) show significant potential for multi-interest analysis due to their extensive knowledge and powerful reasoning capabilities, two key challenge…

Onboard Dual Quaternion Guidance for Rocket Landing
Abhinav G. Kamath, Javier A. Doll, Purnanand Elango, Taewan Kim, Skye Mceowen, Yue Yu, Taylor P. Reynolds, Gavin F. Mendeck, John M. Carson III, Mehran Mesbahi, Beh\c{c}et A\c{c}{\i}kme\c{s}e
https://arxiv.org/abs/2508.10439

Onboard Dual Quaternion Guidance for Rocket Landing
The dual quaternion guidance (DQG) algorithm was selected as the candidate 6-DoF powered-descent guidance algorithm for NASA's Safe and Precise Landing -- Integrated Capabilities Evolution (SPLICE) project. DQG is capable of handling state-triggered constraints that are of utmost importance in terms of enabling technologies such as terrain relative navigation. In this work, we develop a custom solver for DQG to enable onboard implementation for future rocket landing missions. We describe the de…

Cutting Slack: Quantum Optimization with Slack-Free Methods for Combinatorial Benchmarks
Monit Sharma, Hoong Chuin Lau
https://arxiv.org/abs/2507.12159 htt…

Cutting Slack: Quantum Optimization with Slack-Free Methods for Combinatorial Benchmarks
Constraint handling remains a key bottleneck in quantum combinatorial optimization. While slack-variable-based encodings are straightforward, they significantly increase qubit counts and circuit depth, challenging the scalability of quantum solvers. In this work, we investigate a suite of Lagrangian-based optimization techniques including dual ascent, bundle methods, cutting plane approaches, and augmented Lagrangian formulations for solving constrained combinatorial problems on quantum simulat…

Conformal Turaev-Viro Theory
Thomas Hartman
https://arxiv.org/abs/2507.11652 https://arxiv.org/pdf/2507.11652

Conformal Turaev-Viro Theory
We define and study Conformal Turaev-Viro (CTV) theory, a dual formulation of Virasoro TQFT based on triangulating 3-manifolds with tetrahedra. Edges of the triangulation are labeled by continuous conformal weights, and tetrahedra are glued together weighted by the Cardy density of states. We demonstrate that the CTV partition function is equal to the modular S-transform of the Virasoro TQFT amplitude-squared, $|Z_{Vir}|^2$. This is analogous to a known result for discrete spin networ…

""economic dynamics" in Russia are "rapidly declining, with a risk of a technical recession in the second and third quarters" of 2025."
Putin Warned of Dual Threat to Russian Economy: 'Countdown to a Crisis'
https://www.newsweek.com/putin-warned-dual-threat-russian-economy-countdown-crisis-2082449

Framing Triangulations and Framing Posets of Planar DAGs with Nontrivial Netflow Vectors
Jonah Berggren
https://arxiv.org/abs/2507.12684 https://

Framing Triangulations and Framing Posets of Planar DAGs with Nontrivial Netflow Vectors
The space of unit flows on a directed acyclic graph (DAG) with one source and one sink is known to admit regular unimodular triangulations induced by framings of the DAG. The dual graph of any of these triangulations may be given the structure of the Hasse diagram of a lattice, generalizing many variations of the Tamari lattice and the weak order. We extend this theory to flow polytopes of DAGs which may have multiple sources, multiple sinks, and nontrivial netflow vectors under certain planari…

Dual RIS-Assisted Monostatic L-Band Radar Target Detection in NLoS Scenarios
Salman Liaquat, Ijaz Haider Naqvi, Nor Muzlifah Mahyuddin
https://arxiv.org/abs/2507.11036

Dual RIS-Assisted Monostatic L-Band Radar Target Detection in NLoS Scenarios
The use of a single Reconfigurable Intelligent Surface (RIS) to boost the signal-to-noise ratio (SNR) at the radar offers significant improvement in detecting targets, especially in non-line-of-sight (NLoS) scenarios. However, there are scenarios where no path exists between the radar and the target, even with a single RIS-assisted radar, due to other present obstacles. This paper derives an expression for SNR in target detection scenarios where dual RISs assist a monostatic radar in NLoS situa…

Secure Pinching Antenna-aided ISAC
Elmehdi Illi, Marwa Qaraqe, Ali Ghrayeb
https://arxiv.org/abs/2507.13131 https://arxiv.org/pdf/250…

Secure Pinching Antenna-aided ISAC
In this letter, a pinching antenna (PA)-aided scheme for establishing a secure integrated sensing and communication system (ISAC) is investigated. The underlying system comprises a dual-functional radar communication (DFRC) base station (BS) linked to multiple waveguides to serve several downlink users while sensing a set of malicious targets in a given area. The PA-aided BS aims at preserving communication confidentiality with the legitimate users while being able to detect malicious targets. …

SUSEP-Net: Simulation-Supervised and Contrastive Learning-based Deep Neural Networks for Susceptibility Source Separation
Min Li, Chen Chen, Zhenghao Li, Yin Liu, Shanshan Shan, Peng Wu, Pengfei Rong, Feng Liu, G. Bruce Pike, Alan H. Wilman, Hongfu Sun, Yang Gao
https://arxiv.org/abs/2506.13293

SUSEP-Net: Simulation-Supervised and Contrastive Learning-based Deep Neural Networks for Susceptibility Source Separation
Quantitative susceptibility mapping (QSM) provides a valuable tool for quantifying susceptibility distributions in human brains; however, two types of opposing susceptibility sources (i.e., paramagnetic and diamagnetic), may coexist in a single voxel, and cancel each other out in net QSM images. Susceptibility source separation techniques enable the extraction of sub-voxel information from QSM maps. This study proposes a novel SUSEP-Net for susceptibility source separation by training a dual-br…

PoseGRAF: Geometric-Reinforced Adaptive Fusion for Monocular 3D Human Pose Estimation
Ming Xu, Xu Zhang
https://arxiv.org/abs/2506.14596 https://

PoseGRAF: Geometric-Reinforced Adaptive Fusion for Monocular 3D Human Pose Estimation
Existing monocular 3D pose estimation methods primarily rely on joint positional features, while overlooking intrinsic directional and angular correlations within the skeleton. As a result, they often produce implausible poses under joint occlusions or rapid motion changes. To address these challenges, we propose the PoseGRAF framework. We first construct a dual graph convolutional structure that separately processes joint and bone graphs, effectively capturing their local dependencies. A Cross…

Characterizations of dual of K-frames in quaternionic Hilbert spaces
Chander Shekhar
https://arxiv.org/abs/2508.08263 https://arxiv.org/pdf/2508.08263

Characterizations of dual of K-frames in quaternionic Hilbert spaces
Dual of K-frames in a right quaternionic Hilbert space has been recently introduced and studied by Ellouz[1]. In this paper, we study duals of K-frames and prove a characterization of a K-dual in terms of the canonical K-dual of a K-frame in the case when the range of K is not necessarily closed. Moreover, we defined and studied the Approximate K- Dual of a K-frame in a right quaternionic Hilbert space and proved various results for their existence.

A dual AGN at z = 5.4 associated with a Lyman-alpha Nebula in the Center of a Cosmic Filament
Qiong Li, Christopher J. Conselice, Qiao Duan, Duncan Austin, Tom Harvey, Nathan Adams, George Bendo, Lewi Westcott, Vadim Rusakov, Zheng Cai, Yuanhang Ning, Shiwu Zhang
https://arxiv.org/abs/2508.09749

A dual AGN at z = 5.4 associated with a Lyman-alpha Nebula in the Center of a Cosmic Filament
Predictions from current theories and simulations suggest that dual AGN systems are exceedingly rare at high redshifts. The intense radiation and powerful outflows from AGNs regulate star formation, heat the interstellar medium, and drive massive gas outflows that shape the host galaxy and its surroundings. One manifestation of AGN feedback is the creation of extended Ly$α$ nebulae. However, identifying these systems at high-$z$ is challenging. Here, we report a remarkable dual AGN candidate a…

Enhancing gate control and mitigating short channel effects in 20-50 nm channel length single-gate amorphous oxide Thin Film Transistors
Chankeun Yoon, Yuchen Zhou, Ananth Dodabalapur
https://arxiv.org/abs/2506.14156

Enhancing gate control and mitigating short channel effects in 20-50 nm channel length single-gate amorphous oxide Thin Film Transistors
Field-effect transistors (FETs) with single gates are adversely affected by short channel effects such as drain-induced barrier lowering (DIBL) and increases in the magnitude of sub-threshold swing as the channel length is reduced. Dual-gate and gate-all-around geometries are often employed to improve gate control in very short channel length transistors. This can introduce significant process complexity to the device fabrication compared to single-gate transistors. It is shown in this paper th…

DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning with Dual-Pathway Global-Local Fusion
Jin Li, Zezhong Ding, Xike Xie
https://arxiv.org/abs/2507.11229 h…

Spacetime duality between sequential and measurement-feedback circuits
Tsung-Cheng Lu, Sarang Gopalakrishnan, Yizhi You
https://arxiv.org/abs/2507.12523 ht…

Spacetime duality between sequential and measurement-feedback circuits
Two prevalent approaches for preparing long-range entangled quantum states are (i) linear-depth sequential unitary (SU) circuits, which apply local unitary gates sequentially, and (ii) constant-depth measurement-feedback (MF) circuits, which employ mid-circuit measurements and conditional feedback based on measurement outcomes. Here, we establish that a broad class of SU and MF circuits are dual to each other under a spacetime rotation. We investigate this spacetime duality in the preparation o…

A Dual Quaternion Control Law for Formation Control of Multiple 3-D Rigid Bodies
Chunfeng Cui, Liqun Qi, Hao Chen, Xiangke Wang
https://arxiv.org/abs/2508.10519 https://

A Dual Quaternion Control Law for Formation Control of Multiple 3-D Rigid Bodies
This paper studies the integrated position and attitude control problem for multi-agent systems of 3D rigid bodies. While the state-of-the-art method in [Olfati-Saber and Murray, 2004] established the theoretical foundation for rigid-body formation control, it requires all agents to asymptotically converge to identical positions and attitudes, limiting its applicability in scenarios where distinct desired relative configurations must be maintained. In this paper, we develop a novel dual-quatern…

Pose State Perception of Interventional Robot for Cardio-cerebrovascular Procedures
Shunhan Ji, Yanxi Chen, Zhongyu Yang, Quan Zhang, Xiaohang Nie, Jingqian Sun, Yichao Tang
https://arxiv.org/abs/2506.14201

Pose State Perception of Interventional Robot for Cardio-cerebrovascular Procedures
In response to the increasing demand for cardiocerebrovascular interventional surgeries, precise control of interventional robots has become increasingly important. Within these complex vascular scenarios, the accurate and reliable perception of the pose state for interventional robots is particularly crucial. This paper presents a novel vision-based approach without the need of additional sensors or markers. The core of this paper's method consists of a three-part framework: firstly, a dual-he…

Dual rigidity of the Heisenberg groups
Ingrid Beltita, Daniel Beltita
https://arxiv.org/abs/2508.08904 https://arxiv.org/pdf/2508.08904

Dual rigidity of the Heisenberg groups
We prove the dual rigidity of the Heisenberg groups, that is, they can be distinguished from any other 1-connected Lie groups via the unitary dual spaces.

Triangulating quantum gravity in AdS$_3$
Thomas Hartman
https://arxiv.org/abs/2507.12696 https://arxiv.org/pdf/2507.12696

Triangulating quantum gravity in AdS$_3$
The path integral of pure 3D gravity with negative cosmological constant is formulated on a finite region of spacetime $M$, with boundary conditions that fix geodesic lengths or dihedral angles on $\partial M$. In the dual CFT, this quasi-local amplitude calculates corrections to the Gaussian ensemble of OPE coefficients for black hole states. By triangulating $M$ with generalized tetrahedra, we develop a general method to construct semiclassical geometries and to calculate the exact gravitatio…

Starting to think about GPU acceleration of protocol decodes (rather than just basic math blocks) in ngscopeclient.
Here's the filter graph I'm thinking of using as a benchmark: dual lane QSGMII, 20M points per channel.
The filter graph takes 944 ms end to end to run on my box (2x Xeon 6144 2080 Ti).
Major time consumers:
* Eye pattern (~345 ms)
* QSGMII (~337 ms)
* CDR PLL (~310 ms)
* 8B10B (~160 ms)
* SGMII (~120 ms)
Note that the …

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Alsharif Abuadbba, Chris Hicks, Kristen Moore, Vasilios Mavroudis, Burak Hasircioglu, Diksha Goel, Piers Jennings
https://arxiv.org/abs/2506.13434

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Large Language Models (LLMs) are set to reshape cybersecurity by augmenting red and blue team operations. Red teams can exploit LLMs to plan attacks, craft phishing content, simulate adversaries, and generate exploit code. Conversely, blue teams may deploy them for threat intelligence synthesis, root cause analysis, and streamlined documentation. This dual capability introduces both transformative potential and serious risks. This position paper maps LLM applications across cybersecurity fram…

Reconciling Risk-Aversion Paradoxes in the Distribution-Free Newsvendor Problem: Scarf's Rule Meets Dual Utility
Jonathan Yu-Meng Li, Tiantian Mao, Reza Valimoradi
https://arxiv.org/abs/2507.10735

Reconciling Risk-Aversion Paradoxes in the Distribution-Free Newsvendor Problem: Scarf's Rule Meets Dual Utility
How should a risk-averse newsvendor order optimally under distributional ambiguity? Attempts to extend Scarf's celebrated distribution-free ordering rule using risk measures have led to conflicting prescriptions: CVaR-based models invariably recommend ordering less as risk aversion increases, while mean-standard deviation models -- paradoxically -- suggest ordering more, particularly when ordering costs are high. We resolve this behavioral paradox through a coherent generalization of Scarf's di…

Forgery Guided Learning Strategy with Dual Perception Network for Deepfake Cross-domain Detection
Lixin Jia, Zhiqing Guo, Gaobo Yang, Liejun Wang, Keqin Li
https://arxiv.org/abs/2508.10741

Forgery Guided Learning Strategy with Dual Perception Network for Deepfake Cross-domain Detection
The emergence of deepfake technology has introduced a range of societal problems, garnering considerable attention. Current deepfake detection methods perform well on specific datasets, but exhibit poor performance when applied to datasets with unknown forgery techniques. Moreover, as the gap between emerging and traditional forgery techniques continues to widen, cross-domain detection methods that rely on common forgery traces are becoming increasingly ineffective. This situation highlights th…

DAS: Dual-Aligned Semantic IDs Empowered Industrial Recommender System
Wencai Ye, Mingjie Sun, Shaoyun Shi, Peng Wang, Wenjin Wu, Peng Jiang
https://arxiv.org/abs/2508.10584 htt…

DAS: Dual-Aligned Semantic IDs Empowered Industrial Recommender System
Semantic IDs are discrete identifiers generated by quantizing the Multi-modal Large Language Models (MLLMs) embeddings, enabling efficient multi-modal content integration in recommendation systems. However, their lack of collaborative signals results in a misalignment with downstream discriminative and generative recommendation objectives. Recent studies have introduced various alignment mechanisms to address this problem, but their two-stage framework design still leads to two main limitations…

The AdS/$\mathsf{C}$-$\mathsf{P}$-${\mathsf T}$ Correspondence
Jaume Gomis
https://arxiv.org/abs/2507.12467 https://arxiv.org/pdf/250…

The AdS/$\mathsf{C}$-$\mathsf{P}$-${\mathsf T}$ Correspondence
We study the realization of $\mathsf{C}$, $\mathsf{P}$, $\mathsf{T}$ in ${\cal N}=4$ SYM - corresponding to charge conjugation, parity, and time-reversal - and identify the $\mathsf{C}$, $\mathsf{P}$, $\mathsf{T}$ global symmetries of ${\cal N}=4$ SYM with bulk (gauge) symmetries of string theory on $AdS_5\times S^5$. The dual bulk transformations are symmetries of Type IIB string theory on $AdS_5\times S^5$ that combine string worldsheet symmetries, with geometric transformations acting on $Ad…

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention
Yeonju Ro, Zhenyu Zhang, Souvik Kundu, Zhangyang Wang, Aditya Akella
https://arxiv.org/abs/2506.09316

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention
Large language models (LLMs) excel at capturing global token dependencies via self-attention but face prohibitive compute and memory costs on lengthy inputs. While sub-quadratic methods (e.g., linear attention) can reduce these costs, they often degrade accuracy due to overemphasizing recent tokens. In this work, we first propose \textit{dual-state linear attention} (\textbf{\dsla}), a novel design that maintains two specialized hidden states-one for preserving historical context and one for tr…

Cell Sensing: Traffic detection
Sa\'ul Fenollosa
https://arxiv.org/abs/2507.12211 https://arxiv.org/pdf/2507.12211

Cell Sensing: Traffic detection
This work presents a passive sensing system for traffic monitoring using ambient Long Term Evolution (LTE) signals as a non-intrusive and scalable alternative to traditional surveillance methods. The approach employs a dual-receiver architecture analyzing Channel State Information (CSI) to isolate differential Doppler shifts induced by moving targets, effectively mitigating hardware-induced phase impairments. Implemented with a Software Defined Radio (SDR) platform and srsRAN software, the syst…

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Alsharif Abuadbba, Chris Hicks, Kristen Moore, Vasilios Mavroudis, Burak Hasircioglu, Diksha Goel, Piers Jennings
https://arxiv.org/abs/2506.13434

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Large Language Models (LLMs) are set to reshape cybersecurity by augmenting red and blue team operations. Red teams can exploit LLMs to plan attacks, craft phishing content, simulate adversaries, and generate exploit code. Conversely, blue teams may deploy them for threat intelligence synthesis, root cause analysis, and streamlined documentation. This dual capability introduces both transformative potential and serious risks. This position paper maps LLM applications across cybersecurity fram…

HiFi-Mamba: Dual-Stream W-Laplacian Enhanced Mamba for High-Fidelity MRI Reconstruction
Hongli Chen, Pengcheng Fang, Yuxia Chen, Yingxuan Ren, Jing Hao, Fangfang Tang, Xiaohao Cai, Shanshan Shan, Feng Liu
https://arxiv.org/abs/2508.09179

HiFi-Mamba: Dual-Stream W-Laplacian Enhanced Mamba for High-Fidelity MRI Reconstruction
Reconstructing high-fidelity MR images from undersampled k-space data remains a challenging problem in MRI. While Mamba variants for vision tasks offer promising long-range modeling capabilities with linear-time complexity, their direct application to MRI reconstruction inherits two key limitations: (1) insensitivity to high-frequency anatomical details; and (2) reliance on redundant multi-directional scanning. To address these limitations, we introduce High-Fidelity Mamba (HiFi-Mamba), a novel…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- Stochastic Primal-Dual Q-Learning
Donghwan Lee, Niao He

Extropy Rate: Properties and Application in Feature Selection
Naveen Kumar, Vivek Vijay
https://arxiv.org/abs/2507.11242 https://arxi…

Extropy Rate: Properties and Application in Feature Selection
Extropy, a complementary dual of entropy, (proposed by Lad et al. \cite{lad2015extropy} in 2015) has attracted considerable interest from the research community. In this study, we focus on discrete random variables and define conditional extropy, establishing key properties of joint and conditional extropy such as bounds, uncertainty reduction due to additional information, and Lipschitz continuity. We further introduce the concept of extropy rate for a stochastic process of discrete random var…

Leveraging Bi-Directional Channel Reciprocity for Robust Ultra-Low-Rate Implicit CSI Feedback with Deep Learning
Zhenyu Liu, Yi Ma, Rahim Tafazolli, Zhi Ding
https://arxiv.org/abs/2507.12301

Leveraging Bi-Directional Channel Reciprocity for Robust Ultra-Low-Rate Implicit CSI Feedback with Deep Learning
Deep learning-based implicit channel state information (CSI) feedback has been introduced to enhance spectral efficiency in massive MIMO systems. Existing methods often show performance degradation in ultra-low-rate scenarios and inadaptability across diverse environments. In this paper, we propose Dual-ImRUNet, an efficient uplink-assisted deep implicit CSI feedback framework incorporating two novel plug-in preprocessing modules to achieve ultra-low feedback rates while maintaining high enviro…

Entanglement structure for finite system under dual-unitary dynamics
Gaurav Rudra Malik, Rohit Kumar Shukla, Sudhanva Joshi, S. Aravinda, Sunil Kumar Mishra
https://arxiv.org/abs/2506.09904

Entanglement structure for finite system under dual-unitary dynamics
The dynamics of quantum many-body systems in the chaotic regime are of particular interest due to the associated phenomena of information scrambling and entanglement generation within the system. While these systems are typically intractable using traditional numerical methods, an effective framework can be implemented based on dual-unitary circuits which have emerged as a minimal model for maximally chaotic dynamics. In this work, we investigate how individual two-body operators influence the …

Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective
Vishwak Srinivasan, Qijia Jiang
https://arxiv.org/abs/2507.12246 https…

Designing Algorithms for Entropic Optimal Transport from an Optimisation Perspective
In this work, we develop a collection of novel methods for the entropic-regularised optimal transport problem, which are inspired by existing mirror descent interpretations of the Sinkhorn algorithm used for solving this problem. These are fundamentally proposed from an optimisation perspective: either based on the associated semi-dual problem, or based on solving a non-convex constrained problem over subset of joint distributions. This optimisation viewpoint results in non-asymptotic rates of …

MPC-based Coarse-to-Fine Motion Planning for Robotic Object Transportation in Cluttered Environments
Chen Cai, Ernesto Dickel Saraiva, Ya-jun Pan, Steven Liu
https://arxiv.org/abs/2507.11211

MPC-based Coarse-to-Fine Motion Planning for Robotic Object Transportation in Cluttered Environments
This letter presents a novel coarse-to-fine motion planning framework for robotic manipulation in cluttered, unmodeled environments. The system integrates a dual-camera perception setup with a B-spline-based model predictive control (MPC) scheme. Initially, the planner generates feasible global trajectories from partial and uncertain observations. As new visual data are incrementally fused, both the environment model and motion planning are progressively refined. A vision-based cost function pr…

Intelligent Metasurface-Enabled Integrated Sensing and Communication: Unified Framework and Key Technologies
Shunyu Li, Tianqi Mao, Guangyao Liu, Fan Zhang, Ruiqi Liu, Meng Hua, Zhen Gao, Qingqing Wu, George K. Karagiannidis
https://arxiv.org/abs/2506.13713

Intelligent Metasurface-Enabled Integrated Sensing and Communication: Unified Framework and Key Technologies
As the demand for ubiquitous connectivity and high-precision environmental awareness grows, integrated sensing and communication (ISAC) has emerged as a key technology for sixth-generation (6G) wireless networks. Intelligent metasurfaces (IMs) have also been widely adopted in ISAC scenarios due to their efficient, programmable control over electromagnetic waves. This provides a versatile solution that meets the dual-function requirements of next-generation networks. Although reconfigurable inte…

DINA: A Dual Defense Framework Against Internal Noise and External Attacks in Natural Language Processing
Ko-Wei Chuang, Hen-Hsen Huang, Tsai-Yen Li
https://arxiv.org/abs/2508.05671

DINA: A Dual Defense Framework Against Internal Noise and External Attacks in Natural Language Processing
As large language models (LLMs) and generative AI become increasingly integrated into customer service and moderation applications, adversarial threats emerge from both external manipulations and internal label corruption. In this work, we identify and systematically address these dual adversarial threats by introducing DINA (Dual Defense Against Internal Noise and Adversarial Attacks), a novel unified framework tailored specifically for NLP. Our approach adapts advanced noisy-label learning me…

Detectability via observability in a nonuniform framework: dual relationship with controllability and stabilizability
Ignacio Huerta, Pablo Monz\'on
https://arxiv.org/abs/2508.09918

Detectability via observability in a nonuniform framework: dual relationship with controllability and stabilizability
In this paper we propose a new observability property for nonautonomous linear control systems in finite dimension: the nonuniform complete observability, which is more general than the uniform complete observability. A dual relationship is established between this new notion of observability and the recently defined nonuniform complete controllability property, with the aim of obtaining the main result, which proves that nonuniform complete observability guarantees the nonuniform exponential d…

Completeness Stability of Quantum Measurements
Rakesh Saini, Jukka Kiukas, Daniel Burgarth, Alexei Gilchrist
https://arxiv.org/abs/2506.11539 https://

Completeness Stability of Quantum Measurements
We introduce a resource monotone, the completeness stability, to quantify the quality of quantum measurements within a resource-theoretic framework. By viewing a quantum measurement as a frame, the minimum eigenvalue of a frame operator emerges as a significant monotone. It captures bounds on estimation errors and the numerical stability of inverting the frame operator to calculate the optimal dual for state reconstruction. Maximizing this monotone identifies a well-characterized class of quant…

A Black Hole Airy Tail
Stefano Antonini, Luca V. Iliesiu, Pratik Rath, Patrick Tran
https://arxiv.org/abs/2507.10657 https://arxiv.or…

A Black Hole Airy Tail
In Jackiw-Teitelboim (JT) gravity, which is dual to a random matrix ensemble, the annealed entropy differs from the quenched entropy at low temperatures and goes negative. However, computing the quenched entropy in JT gravity requires a replica limit that is poorly understood. To circumvent this, we define an intermediate quantity called the semi-quenched entropy, which has the positivity properties of the quenched entropy, while requiring a much simpler replica trick. We compute this in JT gra…

Affordance-Guided Dual-Armed Disassembly Teleoperation for Mating Parts
Gen Sako, Takuya Kiyokawa, Kensuke Harada, Tomoki Ishikura, Naoya Miyaji, Genichiro Matsuda
https://arxiv.org/abs/2508.05937

Affordance-Guided Dual-Armed Disassembly Teleoperation for Mating Parts
Robotic non-destructive disassembly of mating parts remains challenging due to the need for flexible manipulation and the limited visibility of internal structures. This study presents an affordance-guided teleoperation system that enables intuitive human demonstrations for dual-arm fix-and-disassemble tasks for mating parts. The system visualizes feasible grasp poses and disassembly directions in a virtual environment, both derived from the object's geometry, to address occlusions and structur…

Graph Attention-based Decentralized Actor-Critic for Dual-Objective Control of Multi-UAV Swarms
Haoran Peng, Ying-Jun Angela Zhang
https://arxiv.org/abs/2506.09195

Graph Attention-based Decentralized Actor-Critic for Dual-Objective Control of Multi-UAV Swarms
This research focuses on optimizing multi-UAV systems with dual objectives: maximizing service coverage as the primary goal while extending battery lifetime as the secondary objective. We propose a Graph Attention-based Decentralized Actor-Critic (GADC) to optimize the dual objectives. The proposed approach leverages a graph attention network to process UAVs' limited local observation and reduce the dimension of the environment states. Subsequently, an actor-double-critic network is developed t…

Non-Euclidean dual gradient ascent for entropically regularized linear and semidefinite programming
Yuhang Cai, Michael Lindsey
https://arxiv.org/abs/2506.09711

Non-Euclidean dual gradient ascent for entropically regularized linear and semidefinite programming
We present an optimization framework that exhibits dimension-independent convergence on a broad class of semidefinite programs (SDPs). Our approach first regularizes the primal problem with the von Neumann entropy, then solve the regularized problem using dual gradient ascent with respect to a problem-adapted norm. In particular, we show that the dual gradient norm converges to zero at a rate independent of the ambient dimension and, via rounding arguments, construct primal-feasible solutions i…

DMFI: Dual-Modality Fine-Tuning and Inference Framework for LLM-Based Insider Threat Detection
Kaichuan Kong, Dongjie Liu, Xiaobo Jin, Guanggang Geng, Zhiying Li, Jian Weng
https://arxiv.org/abs/2508.05694

DMFI: Dual-Modality Fine-Tuning and Inference Framework for LLM-Based Insider Threat Detection
Insider threat detection (ITD) poses a persistent and high-impact challenge in cybersecurity due to the subtle, long-term, and context-dependent nature of malicious insider behaviors. Traditional models often struggle to capture semantic intent and complex behavior dynamics, while existing LLM-based solutions face limitations in prompt adaptability and modality coverage. To bridge this gap, we propose DMFI, a dual-modality framework that integrates semantic inference with behavior-aware fine-tu…

Distributed Asynchronous Primal-Dual Optimization for Supply-Chain Networks
Laksh Patel, Neel Shanbhag
https://arxiv.org/abs/2506.08024 https://

Distributed Asynchronous Primal-Dual Optimization for Supply-Chain Networks
Distributed supply-chain optimization demands algorithms that can cope with unreliable communication, unbounded messaging delays, and geographically dispersed agents while still guaranteeing convergence with provable rates. In this work, we introduce DAPD-SCO (Distributed Asynchronous Primal-Dual Optimization for Supply-Chain Networks), a fully asynchronous primal-dual scheme for network flow allocation over directed acyclic supply-chain graphs. Each edge agent independently updates its local f…

Anderson Accelerated Primal-Dual Hybrid Gradient for solving LP
Yingxin Zhou, Stefano Cipolla, Phan Tu Vuong
https://arxiv.org/abs/2508.08062 https://arxiv…

Anderson Accelerated Primal-Dual Hybrid Gradient for solving LP
We present the Anderson Accelerated Primal-Dual Hybrid Gradient (AA-PDHG), a fixed-point-based framework designed to overcome the slow convergence of the standard PDHG method for the solution of linear programming (LP) problems. We establish the global convergence of AA-PDHG under a safeguard condition. In addition, we propose a filtered variant (FAA-PDHG) that applies angle and length filtering to preserve the uniform boundedness of the coefficient matrix, a property crucial for guaranteeing c…