Tootfinder

from my link log —
Portable dynamically linked packages on Linux.
https://brioche.dev/blog/portable-dynamically-linked-packages-on-linux/
saved 2025-03-18

DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router
Minghao Guo, Qingcheng Zeng, Xujiang Zhao, Yanchi Liu, Wenchao Yu, Mengnan Du, Haifeng Chen, Wei Cheng
https://arxiv.org/abs/2507.22050

DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router
Large Language Models (LLMs) excel at many reasoning tasks but struggle with knowledge-intensive queries due to their inability to dynamically access up-to-date or domain-specific information. Retrieval-Augmented Generation (RAG) has emerged as a promising solution, enabling LLMs to ground their responses in external sources. However, existing RAG methods lack fine-grained control over both the query and source sides, often resulting in noisy retrieval and shallow reasoning. In this work, we in…

Decision Transformer-Based Drone Trajectory Planning with Dynamic Safety-Efficiency Trade-Offs
Chang-Hun Ji, SiWoon Song, Youn-Hee Han, SungTae Moon
https://arxiv.org/abs/2507.21506

Decision Transformer-Based Drone Trajectory Planning with Dynamic Safety-Efficiency Trade-Offs
A drone trajectory planner should be able to dynamically adjust the safety-efficiency trade-off according to varying mission requirements in unknown environments. Although traditional polynomial-based planners offer computational efficiency and smooth trajectory generation, they require expert knowledge to tune multiple parameters to adjust this trade-off. Moreover, even with careful tuning, the resulting adjustment may fail to achieve the desired trade-off. Similarly, although reinforcement le…

VizGenie: Toward Self-Refining, Domain-Aware Workflows for Next-Generation Scientific Visualization
Ayan Biswas, Terece L. Turton, Nishath Rajiv Ranasinghe, Shawn Jones, Bradley Love, William Jones, Aric Hagberg, Han-Wei Shen, Nathan DeBardeleben, Earl Lawrence
https://arxiv.org/abs/2507.21124

VizGenie: Toward Self-Refining, Domain-Aware Workflows for Next-Generation Scientific Visualization
We present VizGenie, a self-improving, agentic framework that advances scientific visualization through large language model (LLM) by orchestrating of a collection of domain-specific and dynamically generated modules. Users initially access core functionalities--such as threshold-based filtering, slice extraction, and statistical analysis--through pre-existing tools. For tasks beyond this baseline, VizGenie autonomously employs LLMs to generate new visualization scripts (e.g., VTK Python code),…

Search-Based Fuzzing For RESTful APIs That Use MongoDB
Hernan Ghianni, Man Zhang, Juan P. Galeotti, Andrea Arcuri
https://arxiv.org/abs/2507.20848 https://…

Search-Based Fuzzing For RESTful APIs That Use MongoDB
In RESTful APIs, interactions with a database are a common and crucial aspect. When generating whitebox tests, it is essential to consider the database's state (i.e., the data contained in the database) to achieve higher code coverage and uncover more hidden faults. This article presents novel techniques to enhance search-based software test generation for RESTful APIs interacting with NoSQL databases. Specifically, we target the popular MongoDB database, by dynamically analyzing (via automated…

Rotatable RIS Assisted Physical Layer Multicasting
Ji Wang, Jiayu Tian, Lijuan Qin, Kunrui Cao, Hongbo Xu, Xingwang Li, Tony. Q. S. Quek
https://arxiv.org/abs/2507.20113 https:/…

Rotatable RIS Assisted Physical Layer Multicasting
Reconfigurable Intelligent Surfaces (RIS) dynamically control signal propagation to enhance wireless communications. This paper presents a novel framework for rotatable RIS assisted physical-layer multicast systems, aiming to maximize the sum of minimum multicast rates via joint optimization of base station beamforming, RIS phase shifts, and orientation. Unlike unicast or non-rotatable setups, the rotatable RIS adapts orientation to align signals with user groups, improving fairness and rates f…

This https://arxiv.org/abs/2505.08944 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Toward Cost-Efficient Serving of Mixture-of-Experts with Asynchrony
Mixture-of-Experts (MoE) architectures offer the promise of larger model capacity without the prohibitive costs of fully dense designs. However, in real-world inference serving, load skew across experts often leads to suboptimal device utilization and excessive synchronization overheads. This paper introduces Asynchronous Expert Parallelism (AEP), a new paradigm that decouples layer execution from barrier-style synchronization. By dynamically queuing tokens at each layer (referred to as $μ$-qu…

Realization of a Quantum Error Detection Code with a Dynamically Reassigned Ancillary Qubit
Alena S. Kazmina, Artyom M. Polyanskiy, Elena Yu. Egorova, Nikolay N. Abramov, Daria A. Kalacheva, Viktor B. Lubsanov, Aleksey N. Bolgar, Ilya A. Simakov
https://arxiv.org/abs/2506.20529

Realization of a Quantum Error Detection Code with a Dynamically Reassigned Ancillary Qubit
Quantum error correction (QEC) is essential for achieving fault-tolerant quantum computing. While superconducting qubits are among the most promising candidates for scalable QEC, their limited nearest-neighbor connectivity presents significant challenges for implementing a wide range of error correction codes. In this work, we experimentally demonstrate a quantum error detection scheme that employs a dynamically reassigned ancillary qubit on a chain of three linearly connected transmon qubits. …

Bayesian-Guided Diversity in Sequential Sampling for Recommender Systems
Hiba Bederina, Jill-J\^enn Vie
https://arxiv.org/abs/2506.21617 https://

Bayesian-Guided Diversity in Sequential Sampling for Recommender Systems
The challenge of balancing user relevance and content diversity in recommender systems is increasingly critical amid growing concerns about content homogeneity and reduced user engagement. In this work, we propose a novel framework that leverages a multi-objective, contextual sequential sampling strategy. Item selection is guided by Bayesian updates that dynamically adjust scores to optimize diversity. The reward formulation integrates multiple diversity metrics-including the log-determinant vo…

Movable Antennas-aided Wireless Energy Transfer for the Internet of Things
Osmel Mart\'inez Rosabal, Onel Alcaraz L\'opez, Marco Di Renzo, Richard Demo Souza, Hirley Alves
https://arxiv.org/abs/2506.21966

Movable Antennas-aided Wireless Energy Transfer for the Internet of Things
Recent advancements in movable antennas (MAs) technology create new opportunities for 6G and beyond wireless systems. MAs are promising for radio frequency wireless energy transfer because they can dynamically adjust antenna positions, improving energy efficiency and scalability. This work aims to minimize the power consumed by an analog beamforming power beacon equipped with independently-controlled MAs (IMAs) for charging multiple single-antenna devices. To this end, we enforce a minimum sepa…

Dark Matter Constraints in Myrzakulov $F(R,T)$ Gravity: A Vielbein Approach in Weitzenb\"{o}ck Spacetime with Observational Data
Davood Momeni, Ratbay Myrzakulov
https://arxiv.org/abs/2507.21359

Dark Matter Constraints in Myrzakulov $F(R,T)$ Gravity: A Vielbein Approach in Weitzenböck Spacetime with Observational Data
We explore dark matter phenomenology in Myrzakulov $F(R,T)$ gravity, formulated via the vielbein approach in Weitzenböck spacetime. In this torsion-based extension of gravity, dark matter emerges as a geometric effect rather than a particle species, with curvature and torsion contributing dynamically to the field equations. Using recent data -- including SPARC galaxy rotation curves, Planck CMB observations, and weak lensing from DES and KiDS -- we constrain the model through MCMC analysis. Ou…

Towards a Robust Transport Network With Self-adaptive Network Digital Twin
Cl\'audio Modesto, Jo\~ao Borges, Cleverson Nahum, Lucas Matni, Cristiano Bonato Both, Kleber Cardoso, Glauco Gon\c{c}alves, Ilan Correa, Silvia Lins, Andrey Silva, Aldebaro Klautau
https://arxiv.org/abs/2507.20971

Towards a Robust Transport Network With Self-adaptive Network Digital Twin
The ability of the network digital twin (NDT) to remain aware of changes in its physical counterpart, known as the physical twin (PTwin), is a fundamental condition to enable timely synchronization, also referred to as twinning. In this way, considering a transport network, a key requirement is to handle unexpected traffic variability and dynamically adapt to maintain optimal performance in the associated virtual model, known as the virtual twin (VTwin). In this context, we propose a self-adapt…

Cluster dynamics modeling of hydrogen saturation retention in tungsten with a universal trapping-site sink strength
Yuanyuan Zhang, Xiaoru Chen Chuanguo Zhang, Yonggang Li
https://arxiv.org/abs/2507.20121

Cluster dynamics modeling of hydrogen saturation retention in tungsten with a universal trapping-site sink strength
Hydrogen isotope (HI) retention poses a key issue for tungsten (W)-based plasma-facing materials (PFMs) in fusion devices, where microstructures such as dislocations (DLs) and grain boundaries (GBs) play a dominant role. Existing theoretical sink strength models for microstructures like DLs and GBs fail to account for the observed saturation of HI retention. In this study, we propose a novel universal trapping-site model that dynamically represents sink strengths as time-dependent site concentr…

Dynamically emergent correlations in a Brownian gas with diffusing diffusivity
Nikhil Mesquita, Satya N. Majumdar, Sanjib Sabhapandit
https://arxiv.org/abs/2506.20859

Dynamically emergent correlations in a Brownian gas with diffusing diffusivity
We study a gas of $N$ Brownian particles in the presence of a common stochastic diffusivity $D(t)=B^2(t)$, where $B(t)$ represents a one-dimensional Brownian motion at time $t$. Starting with all the particles from the origin, the gas expands ballistically. We show that because of the common stochastic diffusivity, the expanding gas gets dynamically correlated, and the joint probability density function of the position of the particles has a conditionally independent and identically distributed…

Effect of applied pressure on the non-relativistic spin-splitting (NRSS) of FeSb2 altermagnet: A first-principles study
Shalika R. Bhandari, R. Tamang, Keshav Shrestha, Samy Brahimi, Samir Lounis, D. P. Rai
https://arxiv.org/abs/2507.22018

Effect of applied pressure on the non-relativistic spin-splitting (NRSS) of FeSb2 altermagnet: A first-principles study
We have investigated the pressure-dependent electronic structure, phonon stability, and anomalous Hall response of the recently discovered altermagnet FeSb2 from density functional theory (DFT) and Wannier function analysis. From density functional perturbation theory (DFPT) calculations, we have found that FeSb2 remains dynamically stable up to 10 GPa, evidenced by positive phonon frequencies. Our spin-polarised band structure shows that the node of band crossing between spin-up and spin-down …

Refining Czech GEC: Insights from a Multi-Experiment Approach
Petr Pechman, Milan Straka, Jana Strakov\'a, Jakub N\'aplava
https://arxiv.org/abs/2506.22402

Refining Czech GEC: Insights from a Multi-Experiment Approach
We present a grammar error correction (GEC) system that achieves state of the art for the Czech language. Our system is based on a neural network translation approach with the Transformer architecture, and its key feature is its real-time synthetic generation pipeline, which dynamically augments sentences with artificial errors by introducing both language-agnostic and Czech-specific errors. We conduct a comprehensive series of experiments, investigating the Czech GEC corpora as bases for synth…

Chiral Quantum Droplet in a Spin-Orbit Coupled Bose Gas
Tianqi Luo, Xiaoling Cui
https://arxiv.org/abs/2506.22198 https://arxiv.org/p…

Chiral Quantum Droplet in a Spin-Orbit Coupled Bose Gas
We report the formation of chiral quantum droplet in a spin-orbit coupled Bose gas, where the system turns to a self-bound droplet when moving towards a particular direction and remains gaseous otherwise. The chirality arises from the breaking of Galilean invariance by spin-orbit coupling, which enables the system to dynamically adjust its condensation momentum and spin polarization in response to its velocity. As a result, only towards a specific moving direction and beyond a critical velocity…

On Reconfigurable Bisimulation, with an Application to the Distributed Synthesis Problem
Yehia Abd Alrahman, Nir Piterman
https://arxiv.org/abs/2505.21672 …

On Reconfigurable Bisimulation, with an Application to the Distributed Synthesis Problem
We consider the problem of distributing a centralised transition system to a set of asynchronous agents recognising the same language. Existing solutions are either manual or involve a huge explosion in the number of states from the centralised system. The difficulty arises from the need to keep a rigid communication scheme, specifying a fixed mapping from events to those who can participate in them. Thus, individual agents need to memorise seen events and their order to dynamically compare the…

Optimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Yeon-Koo Che, Andrew B. Choi
https://arxiv.org/abs/2505.22862 https://

Optimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Allocation of goods and services often involves both stochastic supply and stochastic demand. Motivated by applications such as cloud computing, gig platforms, and blockchain auctions, we study the design of optimal selling mechanisms in an environment where buyers with private valuations arrive stochastically and are assigned goods that also arrive stochastically, and either buyers or goods can be held in a queue at costs until allocation. The optimal mechanism dynamically leverages competitiv…

Dynamically phase-separated states in driven binary dusty plasma
Farida Batool, Sandeep Kumar, Sanat Kumar Tiwari
https://arxiv.org/abs/2507.19248 https://…

Dynamically phase-separated states in driven binary dusty plasma
We comprehensively study external forcing-driven dynamical structure formation in a binary dusty plasma mixture. Using two-dimensional driven-dissipative molecular dynamics simulations, we demonstrate phase segregation into bands and lanes beyond a critical forcing threshold. The particles interact via the Debye-Hückel potential, with interaction strength serving as a control parameter for determining the critical forcing. During early evolution, the results exhibit features of two-stream inst…

The Impact of Simple, Brief, and Adaptive Instructions within Virtual Reality Training: Components of Cognitive Load Theory in an Assembly Task
Rebecca L. Pharmer, Christopher D. Wickens, Lucas Plabst, Benjamin A. Clegg, Leanne M. Hirshfield, Joanna E. Lewis, Jalynn B. Nicoly, Cara A. Spencer, Francisco R. Ortega
https://arxiv.org/abs/2507…

The Impact of Simple, Brief, and Adaptive Instructions within Virtual Reality Training: Components of Cognitive Load Theory in an Assembly Task
Objective: The study examined the effects of varying all three core elements of cognitive load on learning efficiency during a shape assembly task in virtual reality (VR). Background: Adaptive training systems aim to improve learning efficiency and retention by dynamically adjusting difficulty. However, design choices can impact the cognitive workload imposed on the learner. The present experiments examined how aspects of cognitive load impact training outcomes. Method: Participants learned…

Adaptive BSTs for Single-Source and All-to-All Requests: Algorithms and Lower Bounds
Maryam Shiran
https://arxiv.org/abs/2507.20228 https://arxiv.org/pdf/2…

Adaptive BSTs for Single-Source and All-to-All Requests: Algorithms and Lower Bounds
Adaptive binary search trees are a fundamental data structure for organizing hierarchical information. Their ability to dynamically adjust to access patterns makes them particularly valuable for building responsive and efficient networked and distributed systems. We present a unified framework for adaptive binary search trees with fixed restructuring cost, analyzed under two models: the single-source model, where the cost of querying a node is proportional to its distance from a fixed source,…

Performance Analysis of Wireless Communication Systems Assisted by Fluid Reconfigurable Intelligent Surfaces
Farshad Rostami Ghadi, Kai-Kit Wong, F. Javier Lopez-Martinez, George C. Alexandropoulos, Chan-Byoung Chae
https://arxiv.org/abs/2505.23680

Performance Analysis of Wireless Communication Systems Assisted by Fluid Reconfigurable Intelligent Surfaces
This letter investigates the performance of emerging wireless communication systems assisted by a fluid reconfigurable intelligent surface (FRIS). Unlike conventional reconfigurable intelligent surfaces (RISs), an FRIS consists of fluid-inspired metamaterials arranged in a densely packed matrix of sub-elements over a surface. It dynamically activates specific elements for signal reflection and modulation based on real-time channel conditions. Considering a downlink scenario where a base station…

From HOSTS.TXT to Modern Internet Infrastructure
🌐 #hoststxt

From HOSTS.TXT to Modern Internet Infrastructure | AXON Shield
The development of DNS demonstrates an impressive journey from its initial basic form into a modern distributed system which provides high resilience. The internet initially used a basic centralized text file named HOSTS.TXT for its operations. The rapid internet expansion made the initial text file system unworkable so developers created a new solution which could scale dynamically. The system evolves because organizations need better scalability and absolute reliability along with robust secu…

Synchronization and Applications of Piecewise Recursive Sequences with Dynamic Thresholds
Slimane Alaoui Soulimani Valenti
https://arxiv.org/abs/2507.19605 https://

Synchronization and Applications of Piecewise Recursive Sequences with Dynamic Thresholds
We investigate piecewise recursive sequences where both the sequence and its switching threshold evolve dynamically. We consider coupled evolution: $a_{n+1} = f(a_n)$ if $a_n \leq c_n$, otherwise $a_{n+1} = g(a_n)$, with threshold $c_{n+1} = h(a_n, c_n)$. Our analysis reveals that when an orbit switches between regimes infinitely often and both sequences converge, they appear to converge to the same limit (Common Limit Theorem). For linear systems, we identify five possible dynamical behaviors:…

AdapSCA-PSO: An Adaptive Localization Algorithm with AI-Based Hybrid SCA-PSO for IoT WSNs
Ze Zhang, Qian Dong, Wenhan Wang
https://arxiv.org/abs/2507.22317 https://

AdapSCA-PSO: An Adaptive Localization Algorithm with AI-Based Hybrid SCA-PSO for IoT WSNs
The accurate localization of sensor nodes is a fundamental requirement for the practical application of the Internet of Things (IoT). To enable robust localization across diverse environments, this paper proposes a hybrid meta-heuristic localization algorithm. Specifically, the algorithm integrates the Sine Cosine Algorithm (SCA), which is effective in global search, with Particle Swarm Optimization (PSO), which excels at local search. An adaptive switching module is introduced to dynamically s…

Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning
Le Xu, Chenxing Li, Yong Ren, Yujie Chen, Yu Gu, Ruibo Fu, Shan Yang, Dong Yu
https://arxiv.org/abs/2505.22045

Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning
Current vision-guided audio captioning systems frequently fail to address audiovisual misalignment in real-world scenarios, such as dubbed content or off-screen sounds. To bridge this critical gap, we present an entropy-aware gated fusion framework that dynamically modulates visual information flow through cross-modal uncertainty quantification. Our novel approach employs attention entropy analysis in cross-attention layers to automatically identify and suppress misleading visual cues during mo…

Probabilistic Link Budget Analysis for Low Earth Orbit Satellites in the Optical Regime
Dhruv Shivkant, Shreyaans Jain, Rohit K Ramakrishnan
https://arxiv.org/abs/2507.20908 htt…

Probabilistic Link Budget Analysis for Low Earth Orbit Satellites in the Optical Regime
Low Earth Orbit (LEO) optical satellite communication systems face performance challenges due to atmospheric effects such as scintillation, turbulence, wavefront distortion, beam spread, and jitter. This paper presents a comprehensive mathematical model to characterize these effects and their impact on signal propagation. We develop a methodology for dynamically calculating link budgets at any location and time by integrating these models into a probabilistic framework. The approach accounts fo…

Revisiting the $\Lambda_c^ \rightarrow\bar{K}^0\eta p$ reaction: the role of $N^*(1535),~ N^*(1650)$ and $\Sigma(1620)$
Jing Song, Melahat Bayar, Yi-Yao Li, Eulogio Oset
https://arxiv.org/abs/2507.19240

Revisiting the $Λ_c^+\rightarrow\bar{K}^0ηp$ reaction: the role of $N^*(1535),~ N^*(1650)$ and $Σ(1620)$
We perform a theoretical study of the weak decay $Λ_c^+ \rightarrow \bar{K}^0 ηp$ using a coupled-channel chiral unitary approach that incorporates both pseudoscalar-baryon and vector-baryon interactions. Our framework includes contributions from both internal and external weak emission mechanisms, as well as strong final state interactions. We assume that the $N^*(1535)$ and $N^*(1650)$ resonances are dynamically generated through meson-baryon scattering and they appear as distinct structure…

Quantifying the Performance Gap for Simple Versus Optimal Dynamic Server Allocation Policies
Niklas Carlsson, Derek Eager
https://arxiv.org/abs/2507.19667 https://

Quantifying the Performance Gap for Simple Versus Optimal Dynamic Server Allocation Policies
Cloud computing enables the dynamic provisioning of server resources. To exploit this opportunity, a policy is needed for dynamically allocating (and deallocating) servers in response to the current load conditions. In this paper we describe several simple policies for dynamic server allocation and develop analytic models for their analysis. We also design semi-Markov decision models that enable determination of the performance achieved with optimal policies, allowing us to quantify the perform…

ALMA survey of a massive node of the Cosmic Web at $z\sim 3$. II. A dynamically cold and massive disk galaxy in the proximity of a hyperluminous quasar
A. Pensabene, S. Cantalupo, W. Wang, C. Bacchini, F. Fraternali, M. Bischetti, C. Cicone, R. Decarli, G. Pezzulli, M. Galbiati, T. Lazeyras, N. Ledos, G. Quadri, A. Travascio
https://

ALMA survey of a massive node of the Cosmic Web at $z\sim 3$. II. A dynamically cold and massive disk galaxy in the proximity of a hyperluminous quasar
Advancing our understanding of the formation and evolution of early massive galaxies and black holes requires detailed studies of dense structures in the high-redshift Universe. In this work, we present high-angular resolution ($\simeq0.3''$) ALMA observations targeting the CO(4--3) line and the underlying 3-mm dust continuum toward the Cosmic Web node MQN01, a region identified through deep multiwavelength surveys as one of the densest concentrations of galaxies and AGN at cosmic noon. At the …

Fell in love with #IntelliJIDEA’s way of dynamically adding parts of the file’s path to the caption of the buffer’s tab if I have opened two files with identical names.
#programming #coding…

SO emission in the dynamically perturbed protoplanetary disks around CQ Tau and MWC 758
Francesco Zagaria, Haochang Jiang, Gianni Cataldi, Stefano Facchini, Myriam Benisty, Yuri Aikawa, Sean Andrews, Jaehan Bae, Marcelo Barraza-Alfaro, Pietro Curone, Ian Czekala, Daniele Fasano, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Andr\'es F. Izquierdo, Jensen Lawrence, Giuseppe Lodato, Fran\c{c}ois M\'enard, Christophe Pinte, Giovanni P. Rosotti, Jochen Stadler, Richard Tea…

SO emission in the dynamically perturbed protoplanetary disks around CQ Tau and MWC 758
We report the serendipitous detection of the SO $J_N=6_5-5_4$ (219.949 GHz) rotational transition in archival Atacama Large Millimeter/submillimeter Array (ALMA) observations of the spiral hosting protoplanetary disks around CQ Tau (with $\approx4.9σ$ significance) and MWC 758 (with $\approx3.4σ$ significance). In the former, the SO emission comes in the shape of a ring, arises from the edge of the continuum cavity, and is qualitatively consistent, at the currently available spectral resoluti…

Stellar Dynamics in Open Clusters Increases the Binary Fraction and Mass Ratios: Evidence from Photometric Binaries in 35 Open Clusters
Anna C. Childs, Aaron M. Geller
https://arxiv.org/abs/2506.20889

Stellar Dynamics in Open Clusters Increases the Binary Fraction and Mass Ratios: Evidence from Photometric Binaries in 35 Open Clusters
Using the Bayesian Analysis of Stellar Evolution-9 (BASE-9) code and Gaia DR3, Pan-STARRS, and 2MASS data, we identify photometric binaries in 35 open clusters (OCs) and constrain their masses. We find a strong correlation between the binary fraction and cluster dynamical age and an even stronger correlation between core binary fraction and cluster dynamical age. We find the binary mass-ratio (q) distribution of dynamically young OCs is statistically distinct from that of the old OCs. On averag…

> _cobs_ext.cpython-313-wasm32-emscripten.so
> look inside
> ELF 64-bit LSB shared object, x86-64, version 1 (SYSV), dynamically linked
having a normal evening

Efficient Strategy Synthesis for MDPs via Hierarchical Block Decomposition
Alexandros Evangelidis, Gricel V\'azquez, Simos Gerasimou
https://arxiv.org/abs/2506.17792

Efficient Strategy Synthesis for MDPs via Hierarchical Block Decomposition
Software-intensive systems, such as software product lines and robotics, utilise Markov decision processes (MDPs) to capture uncertainty and analyse sequential decision-making problems. Despite the usefulness of conventional policy synthesis methods, they fail to scale to large state spaces. Our approach addresses this issue and accelerates policy synthesis in large MDPs by dynamically refining the MDP and iteratively selecting the most fragile MDP regions for refinement. This iterative procedu…

Prompt-Guided Turn-Taking Prediction
Koji Inoue, Mikey Elmers, Yahui Fu, Zi Haur Pang, Divesh Lala, Keiko Ochi, Tatsuya Kawahara
https://arxiv.org/abs/2506.21191

Prompt-Guided Turn-Taking Prediction
Turn-taking prediction models are essential components in spoken dialogue systems and conversational robots. Recent approaches leverage transformer-based architectures to predict speech activity continuously and in real-time. In this study, we propose a novel model that enables turn-taking prediction to be dynamically controlled via textual prompts. This approach allows intuitive and explicit control through instructions such as "faster" or "calmer" adapting dynamically to conversational partne…

Tunable bound states in the continuum through hybridization of 1D and 2D metasurfaces
Fedor Kovalev, Mariusz Martyniuk, Andrey Miroshnichenko, Ilya Shadrivov
https://arxiv.org/abs/2506.21147

Tunable bound states in the continuum through hybridization of 1D and 2D metasurfaces
This work presents a novel approach to create and dynamically control quasi-Bound States in the Continuum (BIC) resonances through the hybridization of 1D and 2D metasurfaces using micro-electromechanical systems (MEMS). By introducing out-of-plane symmetry breaking through a silicon MEMS membrane positioned above a 1D silicon metasurface, the quasi-BIC resonance's central wavelength and quality factor are precisely tuned. The proposed design achieves ultranarrow resonance linewidths with the s…

Hiord: An Approach to the Specification and Verification of Higher-Order (C)LP Programs
Marco Ciccal\`e, Daniel Jurjo-Rivas, Jose F. Morales, Pedro L\'opez-Garc\'ia, Manuel V. Hermenegildo
https://arxiv.org/abs/2507.17233

Hiord: An Approach to the Specification and Verification of Higher-Order (C)LP Programs
Higher-order constructs enable more expressive and concise code by allowing procedures to be parameterized by other procedures. Assertions allow expressing partial program specifications, which can be verified either at compile time (statically) or run time (dynamically). In higher-order programs, assertions can also describe higher-order arguments. While in the context of (C)LP, run-time verification of higher-order assertions has received some attention, compile-time verification remains rela…

Salience Adjustment for Context-Based Emotion Recognition
Bin Han, Jonathan Gratch
https://arxiv.org/abs/2507.15878 https://arxiv.org…

Salience Adjustment for Context-Based Emotion Recognition
Emotion recognition in dynamic social contexts requires an understanding of the complex interaction between facial expressions and situational cues. This paper presents a salience-adjusted framework for context-aware emotion recognition with Bayesian Cue Integration (BCI) and Visual-Language Models (VLMs) to dynamically weight facial and contextual information based on the expressivity of facial cues. We evaluate this approach using human annotations and automatic emotion recognition systems in…

Electronegativity effects on plasma dynamics in He/O$_2$ RF microplasma jets at atmospheric pressure
Lukas Vogelhuber, Ihor Korolov, Mate Vass, Katharina Noesges, Tim Bolles, Kevin K\"ohn, Maximilian Klich, Ralf Peter Brinkmann, Thomas Mussenbrock
https://arxiv.org/abs/2505.22460

Electronegativity effects on plasma dynamics in He/O$_2$ RF microplasma jets at atmospheric pressure
This work investigates the transitions between ohmic mode and Penning-Gamma mode in a capacitively coupled radio frequency micro atmospheric pressure plasma jets (CCRF $μ$APPJ) operated in He/O$_2$ mixtures by comparing phase-resolved optical emission spectroscopy (PROES) measurements of helium excitation with numerical simulations. The simulations employ a hybrid model that treats electrons kinetically via PIC/MCC, while ions and neutrals are modeled fluid dynamically. These results reveal th…

Optimal Empirical Risk Minimization under Temporal Distribution Shifts
Yujin Jeong, Ramesh Johari, Dominik Rothenh\"ausler, Emily Fox
https://arxiv.org/abs/2507.13287

Optimal Empirical Risk Minimization under Temporal Distribution Shifts
Temporal distribution shifts pose a key challenge for machine learning models trained and deployed in dynamically evolving environments. This paper introduces RIDER (RIsk minimization under Dynamically Evolving Regimes) which derives optimally-weighted empirical risk minimization procedures under temporal distribution shifts. Our approach is theoretically grounded in the random distribution shift model, where random shifts arise as a superposition of numerous unpredictable changes in the data-g…

Online Planning for Cooperative Air-Ground Robot Systems with Unknown Fuel Requirements
Ritvik Agarwal, Behnoushsadat Hatami, Alvika Gautam, Parikshit Maini
https://arxiv.org/abs/2506.20804

Online Planning for Cooperative Air-Ground Robot Systems with Unknown Fuel Requirements
We consider an online variant of the fuel-constrained UAV routing problem with a ground-based mobile refueling station (FCURP-MRS), where targets incur unknown fuel costs. We develop a two-phase solution: an offline heuristic-based planner computes initial UAV and UGV paths, and a novel online planning algorithm that dynamically adjusts rendezvous points based on real-time fuel consumption during target processing. Preliminary Gazebo simulations demonstrate the feasibility of our approach in ma…

Dislocations and crystallization dynamics of chiral soliton lattices
Minoru Eto, Kentaro Nishimura, Muneto Nitta
https://arxiv.org/abs/2506.16354 https://

Dislocations and crystallization dynamics of chiral soliton lattices
Dislocations, as topological defects in crystal lattices, are fundamental to understanding plasticity in materials. Similar periodic structures also arise in continuum field theories, such as chiral soliton lattices (CSLs), which appear in condensed matter systems like chiral magnets and in high-energy contexts such as quantum chromodynamics in strong magnetic field or under rapid rotation. This work investigates whether dislocations can dynamically form within such emergent CSLs. The chiral si…

A Scalable Resource Management Layer for FPGA SoCs in 6G Radio Units
Nikolaos Bartzoudis, Jos\'e Rubio Fern\'andez, David L\'opez-Bueno, Antonio Rom\'an Villarroel
https://arxiv.org/abs/2507.19963

A Scalable Resource Management Layer for FPGA SoCs in 6G Radio Units
This work presents a perspective on addressing the underutilization of computing resources in FPGA SoC devices deployed in 5G radio and edge computing infrastructure. The initial step in this approach involves developing a resource management layer capable of dynamically migrating and scaling functions within these devices in response to contextual events. This layer serves as the foundation for designing a hierarchical, data-driven micro-orchestrator responsible for managing the lifecycle of f…

A New cw-NMR Q-meter for Dynamically Polarized Targets for Particle Physics
J. D. Maxwell, J. Brock, C. Cuevas, H. Dong, C. D. Keith, J. J. Pierce
https://arxiv.org/abs/2506.14637

A New cw-NMR Q-meter for Dynamically Polarized Targets for Particle Physics
Polarized solid targets produced via Dynamic Nuclear Polarization rely on Continuous-Wave Nuclear Magnetism Resonance measurements to accurately determine the degree of polarization of bulk samples polarized to nearly 100%. Since the late 1970's phase sensitive detection methods have been utilized to observe the magnetization of a sample as a small change in inductance under RF excitation near the Larmor frequency of the nuclear species of interest, using a device known as a Q-meter. Liverpool …

Multidimensional Nebular-Phase Calculations of Dynamically-Driven Double-Degenerate Double-Detonation Models for Type Ia Supernovae
J. M. Pollin, S. A. Sim, L. J. Shingles, R. Pakmor, F. P. Callan, C. E. Collins, F. K. Roepke, L. A. Kwok, A. Holas, S. Srivastav
https://arxiv.org/abs/2507.05000

Multidimensional Nebular-Phase Calculations of Dynamically-Driven Double-Degenerate Double-Detonation Models for Type Ia Supernovae
The dynamically-driven double-degenerate double-detonation model has emerged as a promising progenitor candidate for Type Ia supernovae. In this scenario, the primary white dwarf ignites due to dynamical interaction with a companion white dwarf, which may also undergo a detonation. Consequently, two scenarios exist: one in which the secondary survives and another in which both white dwarfs detonate. In either case, substantial departures from spherical symmetry are imprinted on the ejecta. Here…

MultiTaskDeltaNet: Change Detection-based Image Segmentation for Operando ETEM with Application to Carbon Gasification Kinetics
Yushuo Niu, Tianyu Li, Yuanyuan Zhu, Qian Yang
https://arxiv.org/abs/2507.16803

MultiTaskDeltaNet: Change Detection-based Image Segmentation for Operando ETEM with Application to Carbon Gasification Kinetics
Transforming in-situ transmission electron microscopy (TEM) imaging into a tool for spatially-resolved operando characterization of solid-state reactions requires automated, high-precision semantic segmentation of dynamically evolving features. However, traditional deep learning methods for semantic segmentation often encounter limitations due to the scarcity of labeled data, visually ambiguous features of interest, and small-object scenarios. To tackle these challenges, we introduce MultiTaskD…

AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
Ruosen Li, Ziming Luo, Quan Zhang, Ruochen Li, Ben Zhou, Ali Payani, Xinya Du
https://arxiv.org/abs/2506.20160

AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
Large reasoning models (LRMs) achieve impressive reasoning capabilities by generating lengthy chain-of-thoughts, but this "overthinking" incurs high latency and cost without commensurate accuracy gains. In this work, we introduce AALC, a lightweight, accuracy-aware length reward integrated into reinforcement learning that dynamically balances correctness and brevity during training. By incorporating validation accuracy into the reward and employing a smooth, dynamically scheduled length penalty…

Towards Bitrate-Efficient and Noise-Robust Speech Coding with Variable Bitrate RVQ
Yunkee Chae, Kyogu Lee
https://arxiv.org/abs/2506.16538 https://

Towards Bitrate-Efficient and Noise-Robust Speech Coding with Variable Bitrate RVQ
Residual Vector Quantization (RVQ) has become a dominant approach in neural speech and audio coding, providing high-fidelity compression. However, speech coding presents additional challenges due to real-world noise, which degrades compression efficiency. Standard codecs allocate bits uniformly, wasting bitrate on noise components that do not contribute to intelligibility. This paper introduces a Variable Bitrate RVQ (VRVQ) framework for noise-robust speech coding, dynamically adjusting bitrate…

Formal Verification of Neural Certificates Done Dynamically
Thomas A. Henzinger, Konstantin Kueffner, Emily Yu
https://arxiv.org/abs/2507.11987 https://

Formal Verification of Neural Certificates Done Dynamically
Neural certificates have emerged as a powerful tool in cyber-physical systems control, providing witnesses of correctness. These certificates, such as barrier functions, often learned alongside control policies, once verified, serve as mathematical proofs of system safety. However, traditional formal verification of their defining conditions typically faces scalability challenges due to exhaustive state-space exploration. To address this challenge, we propose a lightweight runtime monitoring fr…

Dynamically Dressed States of a Quantum Four-Level System
Carolin Calcagno, Friedrich Sbresny, Thomas K. Bracht, Sang Kyu Kim, Eduardo Zubizarreta Casalengua, Katarina Boos, William Rauhaus, Hubert Riedl, Jonathan J. Finley, Doris E. Reiter, Kai M\"uller
https://arxiv.org/abs/2506.14643…

Dynamically Dressed States of a Quantum Four-Level System
In this work, we experimentally and theoretically study the dressed-state emission of the biexciton-exciton cascade in a semiconductor quantum dot under pulsed, resonant, two-photon excitation. Building on the well-characterized steady-state dressed emission of the four-level system, we examine its dynamic counterpart under pulsed, resonant excitation, addressing both experimental observations and theoretical modeling. Here we report several sidebands emerging from the biexciton-to-exciton tran…

Mixture of Raytraced Experts
Andrea Perin, Giacomo Lagomarsini, Claudio Gallicchio, Giuseppe Nuti
https://arxiv.org/abs/2507.12419 https://

Mixture of Raytraced Experts
We introduce a Mixture of Raytraced Experts, a stacked Mixture of Experts (MoE) architecture which can dynamically select sequences of experts, producing computational graphs of variable width and depth. Existing MoE architectures generally require a fixed amount of computation for a given sample. Our approach, in contrast, yields predictions with increasing accuracy as the computation cycles through the experts' sequence. We train our model by iteratively sampling from a set of candidate exper…

@… a javascript framework to toggle tailwind classes dynamically

Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Chengpeng Hu, Ziming Wang, Bo Yuan, Jialin Liu, Chengqi Zhang, Xin Yao
https://arxiv.org/abs/2506.16795

Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Dynamic material handling (DMH) involves the assignment of dynamically arriving material transporting tasks to suitable vehicles in real time for minimising makespan and tardiness. In real-world scenarios, historical task records are usually available, which enables the training of a decision policy on multiple instances consisting of historical records. Recently, reinforcement learning has been applied to solve DMH. Due to the occurrence of dynamic events such as new tasks, adaptability is hig…

Mapping the Evolution of Research Contributions using KnoVo
Sajratul Y. Rubaiat, Syed N. Sakib, Hasan M. Jamil
https://arxiv.org/abs/2506.17508 https://

Mapping the Evolution of Research Contributions using KnoVo
This paper presents KnoVo (Knowledge Evolution), an intelligent framework designed for quantifying and analyzing the evolution of research novelty in the scientific literature. Moving beyond traditional citation analysis, which primarily measures impact, KnoVo determines a paper's novelty relative to both prior and subsequent work within its multilayered citation network. Given a target paper's abstract, KnoVo utilizes Large Language Models (LLMs) to dynamically extract dimensions of comparison…

My beloved waifu, Debichan, wholeheartedly approves of my gender-fluid, bisexual identity, only because I use Debian! 😉
#Waifu #Debichan #Debian

Apache Flink is uniquely positioned to serve as the backbone for AI agents, equipping them with the powerful new tool of stream processing. Join Steffen Hoellinger at this year's Berlin Buzzwords to explore how Flink jobs can be transformed into “Agents”—autonomous, goal-driven entities that dynamically interact with data streams, trigger actions, and adapt their behaviour based on real-time insights.
Learn more:

A Ground-Based Transit Observation of the Long-Period Extremely Low-Density Planet HIP 41378 f
Juliana Garc\'ia-Mej\'ia, Zo\"e L. de Beurs, Patrick Tamburo, Andrew Vanderburg, David Charbonneau, Karen A. Collins, Khalid Barkaoui, Cristilyn N. Watkins, Chris Stockdale, Richard P. Schwarz, Raquel For\'es-Toribio, Jose A. Mu\~noz, Giovanni Isopi, Franco Mallia, Aldo Zapparata, Adam Popowicz, Andrzej Brudny, Eric Agol, Munazza K. Alam, Zouhair Benkhaldoun, Jehin Emmanuel, …

A Ground-Based Transit Observation of the Long-Period Extremely Low-Density Planet HIP 41378 f
We present a ground-based transit detection of HIP 41378 f, a long-period ($P = 542$ days), extremely low-density ($0.09 \pm 0.02$ g cm$^{-3}$) giant exoplanet in a dynamically complex system. Using photometry from Tierras, TRAPPIST-North, and multiple LCOGT sites, we constrain the transit center time to $T_{C,6} = 2460438.889 \pm 0.049$ BJD TDB. This marks only the second ground-based detection of HIP 41378 f, currently the longest-period and longest-duration transiting exoplanet observed from…

I've spent most of today trying (and failing) to do something which seems as though it should be inherently simple: I've been trying to open an new popup window from #Clojurescript running in a browser, and give that window dynamically generated content.
My mental health really is rubbish today, but I'm not sure to what extent that's the problem and to what extent this …

Leveraging 5G Physical Layer Monitoring for Adaptive Remote Rendering in XR Applications
Inhar Yeregui, Daniel Mej\'ias, Mikel Zorrilla, Roberto Viola, Jasone Astorga, Eduardo Jacob
https://arxiv.org/abs/2505.22123

Leveraging 5G Physical Layer Monitoring for Adaptive Remote Rendering in XR Applications
As immersive eXtended Reality (XR) applications demand substantial network resources, understanding their interaction with 5G networks becomes crucial to improve them. This paper investigates the role of 5G physical-layer monitoring to manage and enhance the remote rendering of XR content dynamically. By observing network metrics directly from the physical layer, we propose a system to adapt streaming parameters such as bitrate, framerate, and resolution in real time based on available network …

Efficient calculation of thermodynamic properties of baryon-rich QCD matter from heavy-ion transport models
Lipei Du
https://arxiv.org/abs/2506.19766 https…

Efficient calculation of thermodynamic properties of baryon-rich QCD matter from heavy-ion transport models
This study presents the MATRICS framework (Modeling Aggregated Tensors for Relativistic Ion Collision Simulations) that implements modular workflows to enable parallel execution of particle generation, grid construction, and tensor calculations for heavy-ion collisions. It introduces an efficient approach to calculating the space-time distribution of the energy-momentum tensor and charge currents from discrete particles generated by transport models. By dynamically adjusting grid resolution bas…

Physics-Guided Radiotherapy Treatment Planning with Deep Learning
Stefanos Achlatis, Efstratios Gavves, Jan-Jakob Sonke
https://arxiv.org/abs/2506.19880 ht…

Physics-Guided Radiotherapy Treatment Planning with Deep Learning
Radiotherapy (RT) is a critical cancer treatment, with volumetric modulated arc therapy (VMAT) being a commonly used technique that enhances dose conformity by dynamically adjusting multileaf collimator (MLC) positions and monitor units (MU) throughout gantry rotation. Adaptive radiotherapy requires frequent modifications to treatment plans to account for anatomical variations, necessitating time-efficient solutions. Deep learning offers a promising solution to automate this process. To this en…

Dynamically Tunable Membrane Metasurfaces for Infrared Spectroscopy
Furkan Kuruoglu, Samir Rosas, Jin-Woo Cho, David A. Czaplewski, Yuri Kivshar, Mikhail Kats, Filiz Yesilkoy
https://arxiv.org/abs/2506.10115

Dynamically Tunable Membrane Metasurfaces for Infrared Spectroscopy
Mid-infrared spectroscopy enables biochemical sensing by identifying vibrational molecular fingerprints, but it faces limitations in instrumentation portability and analytical sensitivity. Optical metasurfaces with strong mid-IR photonic resonances provide an attractive solution towards on-chip spectrometry and sensitive molecular detection, yet their static nature hinders their anticipated impact. Here, we introduce and demonstrate dynamically tunable silicon membrane metasurfaces exhibiting h…

Dynamic Transmission Line Switching Amidst Wildfire-Prone Weather Under Decision-Dependent Uncertainty
Juan-Alberto Estrada-Garcia, Ruiwei Jiang, Alexandre Moreira
https://arxiv.org/abs/2507.13611

Dynamic Transmission Line Switching Amidst Wildfire-Prone Weather Under Decision-Dependent Uncertainty
During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multi-stage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for…

Investigation of $T_{cs0}^{*}(2870)^{0}$ in $pp$ collisions at $\sqrt{s}$ = 7 TeV with the PACIAE model
Qiang Wang, Zhi-Lei She, An-Ke Lei, Dai-Mei Zhou, Wen-Chao Zhang, Hua Zheng, Yu-Liang Yan, Ben-Hao Sa
https://arxiv.org/abs/2506.20145

Investigation of $T_{cs0}^{*}(2870)^{0}$ in $pp$ collisions at $\sqrt{s}$ = 7 TeV with the PACIAE model
We have used the parton and hadron cascade model PACIAE together with the Dynamically Constrained Phase-space Coalescence model (DCPC) to study the $T_{cs0}^{*}(2870)^{0}$ production in $pp$ collision at $\sqrt{s}$ = 7 TeV, in line with the LHCb observation of $T_{cs0}^{*}(2870)^{0}$ in the $B^{-}\to D^{-}D^{0}K^{0}_{S}$ decays in $pp$ collisions at $\sqrt{s}$ = 7, 8, and 13 TeV [PRL 134(2025)101901]. The final hadronic states of the $pp$ collisions at $\sqrt{s}$ = 7 TeV are first simulated by …

EANS: Reducing Energy Consumption for UAV with an Environmental Adaptive Navigation Strategy
Tian Liu, Han Liu, Boyang Li, Long Chen, Kai Huang
https://arxiv.org/abs/2506.20485

EANS: Reducing Energy Consumption for UAV with an Environmental Adaptive Navigation Strategy
Unmanned Aerial Vehicles (UAVS) are limited by the onboard energy. Refinement of the navigation strategy directly affects both the flight velocity and the trajectory based on the adjustment of key parameters in the UAVS pipeline, thus reducing energy consumption. However, existing techniques tend to adopt static and conservative strategies in dynamic scenarios, leading to inefficient energy reduction. Dynamically adjusting the navigation strategy requires overcoming the challenges including the…

E-FreeM2: Efficient Training-Free Multi-Scale and Cross-Modal News Verification via MLLMs
Van-Hoang Phan, Long-Khanh Pham, Dang Vu, Anh-Duy Tran, Minh-Son Dao
https://arxiv.org/abs/2506.20944

E-FreeM2: Efficient Training-Free Multi-Scale and Cross-Modal News Verification via MLLMs
The rapid spread of misinformation in mobile and wireless networks presents critical security challenges. This study introduces a training-free, retrieval-based multimodal fact verification system that leverages pretrained vision-language models and large language models for credibility assessment. By dynamically retrieving and cross-referencing trusted data sources, our approach mitigates vulnerabilities of traditional training-based models, such as adversarial attacks and data poisoning. Addi…

Dynamically Tunable Helical Antenna
Ethan Chien, Jan Steckel
https://arxiv.org/abs/2506.14065 https://arxiv.org/pdf/2506.14065…

Dynamically Tunable Helical Antenna
Unmanned aerial FPV systems demand ultra-low latency, high-reliability communication links. At high speeds and in cluttered environments, Doppler shifts and rapid multipath changes can dramatically raise packet error rates. This paper investigates these phenomena in the context of ExpressLRS (ELRS) long-range FPV control links and demonstrates a novel solution: real-time geometry tuning of a circularly polarized helical antenna array. This study integrates Maxwell-equation-based full-wave simul…

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Christoph Jung, C. F. Bolz-Tereick
https://arxiv.org/abs/2506.16883 https://…

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Compared to the more commonly used time-based profiling, allocation profiling provides an alternate view of the execution of allocation heavy dynamically typed languages. However, profiling every single allocation in a program is very inefficient. We present a sampling allocation profiler that is deeply integrated into the garbage collector of PyPy, a Python virtual machine. This integration ensures tunable low overhead for the allocation profiler, which we measure and quantify. Enabling alloca…

Accelerating Containerized Service Delivery at the Network Edge
Yinuo Deng, Hailiang Zhao, Dongjing Wang, Peng Chen, Wenzhuo Qian, Jianwei Yin, Schahram Dustdar, Shuiguang Deng
https://arxiv.org/abs/2507.20116

Accelerating Containerized Service Delivery at the Network Edge
Efficient container image distribution is crucial for enabling machine learning inference at the network edge, where resource limitations and dynamic network conditions create significant challenges. In this paper, we present PeerSync, a decentralized P2P-based system designed to optimize image distribution in edge environments. PeerSync employs a popularity- and network-aware download engine that dynamically adapts to content popularity and real-time network conditions using a sliding window m…

Towards AI Search Paradigm
Yuchen Li, Hengyi Cai, Rui Kong, Xinran Chen, Jiamin Chen, Jun Yang, Haojie Zhang, Jiayi Li, Jiayi Wu, Yiqun Chen, Changle Qu, Keyi Kong, Wenwen Ye, Lixin Su, Xinyu Ma, Long Xia, Daiting Shi, Jiashu Zhao, Haoyi Xiong, Shuaiqiang Wang, Dawei Yin
https://arxiv.org/abs/2506.17188

Towards AI Search Paradigm
In this paper, we introduce the AI Search Paradigm, a comprehensive blueprint for next-generation search systems capable of emulating human information processing and decision-making. The paradigm employs a modular architecture of four LLM-powered agents (Master, Planner, Executor and Writer) that dynamically adapt to the full spectrum of information needs, from simple factual queries to complex multi-stage reasoning tasks. These agents collaborate dynamically through coordinated workflows to e…

Frequency Resource Management in 6G User-Centric CFmMIMO: A Hybrid Reinforcement Learning and Metaheuristic Approach
Selina Cheggour, Valeria Loscri
https://arxiv.org/abs/2505.22443

Frequency Resource Management in 6G User-Centric CFmMIMO: A Hybrid Reinforcement Learning and Metaheuristic Approach
As sixth-generation (6G) networks continue to evolve, AI-driven solutions are playing a crucial role in enabling more efficient and adaptive resource management in wireless communication. One of the key innovations in 6G is user-centric cell-free massive Multiple-Input Multiple-Output (UC-CFmMIMO), a paradigm that eliminates traditional cell boundaries and enhances network performance by dynamically assigning access points (APs) to users. This approach is particularly well-suited for vehicular …

10,000 Resolved Triples from Gaia: Empirical Constraints on Triple Star Populations
Cheyanne Shariat, Kareem El-Badry, Smadar Naoz
https://arxiv.org/abs/2506.16513

10,000 Resolved Triples from Gaia: Empirical Constraints on Triple Star Populations
We present a catalog of $\sim 10,000$ resolved triple star systems within 500 pc of the Sun, constructed using Gaia data. The triples include main-sequence, red giant, and white dwarf components spanning separations of 10 to 50,000 au. A well-characterized selection function allows us to constrain intrinsic demographics of the triple star population. We find that (a) all systems are compatible with being hierarchical and dynamically stable; (b) mutual orbital inclinations are isotropic for wide…

RARE-UNet: Resolution-Aligned Routing Entry for Adaptive Medical Image Segmentation
Simon Winther Albertsen, Hjalte Svaneborg Bj{\o}rnstrup, Mostafa Mehdipour Ghazi
https://arxiv.org/abs/2507.15524

RARE-UNet: Resolution-Aligned Routing Entry for Adaptive Medical Image Segmentation
Accurate segmentation is crucial for clinical applications, but existing models often assume fixed, high-resolution inputs and degrade significantly when faced with lower-resolution data in real-world scenarios. To address this limitation, we propose RARE-UNet, a resolution-aware multi-scale segmentation architecture that dynamically adapts its inference path to the spatial resolution of the input. Central to our design are multi-scale blocks integrated at multiple encoder depths, a resolution-…

JWST Coronagraphic Images of 14 Her c: a Cold Giant Planet in a Dynamically Hot, Multi-planet System
Daniella C. Bardalez Gagliuffi, William O. Balmer, Laurent Pueyo, Timothy D. Brandt, Mark R. Giovinazzi, Sarah Millholland, Brennen Black, Tiger Lu, Malena Rice, James Mang, Caroline Morley, Brianna Lacy, Julien Girard, Elisabeth Matthews, Aarynn Carter, Brendan P. Bowler, Jacqueline K. Faherty, Clemence Fontanive, Emily Rickman

JWST Coronagraphic Images of 14 Her c: a Cold Giant Planet in a Dynamically Hot, Multi-planet System
Most observed multi-planet systems are coplanar, in a dynamically "cold" configuration of concentric orbits like our own Solar System. With the James Webb Space Telescope (JWST) we have detected 14 Her c, the first mature and cold exoplanet directly imaged in a dynamically "hot", multi-planet system. With large eccentricities and a nonzero mutual inclination, the present-day architecture of this system points to a turbulent past and ongoing angular momentum exchange between the planetary orbits…

OpticalAging: Real-time Presbyopia Simulation for Inclusive Design via Tunable Lenses
Qing Zhang, Zixiong Su, Yoshihito Kondoh, Kazunori Asada, Thad Starner, Kai Kunze, Yuta Itoh, Jun Rekimoto
https://arxiv.org/abs/2506.19307

OpticalAging: Real-time Presbyopia Simulation for Inclusive Design via Tunable Lenses
Presbyopia, a common age-related vision condition affecting most people as they age, often remains inadequately understood by those unaffected. To help bridge the gap between abstract accessibility knowledge and a more grounded appreciation of perceptual challenges, this study presents OpticalAging, an optical see-through simulation approach. Unlike VR-based methods, OpticalAging uses dynamically controlled tunable lenses to simulate the first-person visual perspective of presbyopia's distance-…

MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers
Jushaan Singh Kalra, Xinran Zhao, To Eun Kim, Fengyu Cai, Fernando Diaz, Tongshuang Wu
https://arxiv.org/abs/2506.15862

MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers
Retrieval-augmented Generation (RAG) is powerful, but its effectiveness hinges on which retrievers we use and how. Different retrievers offer distinct, often complementary signals: BM25 captures lexical matches; dense retrievers, semantic similarity. Yet in practice, we typically fix a single retriever based on heuristics, which fails to generalize across diverse information needs. Can we dynamically select and integrate multiple retrievers for each individual query, without the need for manual…

Functional renormalization group study of anomalous magnetic moment in a low energy effective theory
Rui Wen, Chuang Huang, Mei Huang
https://arxiv.org/abs/2506.20246

Functional renormalization group study of anomalous magnetic moment in a low energy effective theory
The quark anomalous magnetic moments (AMMs) are investigated in a 2-flavor low-energy effective theory within the functional renormalization group (FRG) approach under an external magnetic field. The Schwinger formalism is adopted for quark propagators, and Fierz-complete four-quark scatterings are self-consistently included through the renormalization group flows. We find that the quark AMMs are dynamically generated with the chiral symmetry breaking, and the magnitude of the AMM of the down q…

CHAMP: A Configurable, Hot-Swappable Edge Architecture for Adaptive Biometric Tasks
Joel Brogan, Matthew Yohe, David Cornett
https://arxiv.org/abs/2507.17793 https://

CHAMP: A Configurable, Hot-Swappable Edge Architecture for Adaptive Biometric Tasks
What if you could piece together your own custom biometrics and AI analysis system, a bit like LEGO blocks? We aim to bring that technology to field operators in the field who require flexible, high-performance edge AI system that can be adapted on a moment's notice. This paper introduces CHAMP (Configurable Hot-swappable Architecture for Machine Perception), a modular edge computing platform that allows operators to dynamically swap in specialized AI "capability cartridges" for tasks like face…

Unconventional Floquet topological phases in the SSH lattice
Dunkan Mart\'inez, Yuriko Baba, Benjam\'in Santos, Rodrigo P. A. Lima, Pedro Orellana, Francisco Dom\'inguez-Adame, Alexander L\'opez
https://arxiv.org/abs/2507.16441

Unconventional Floquet topological phases in the SSH lattice
Topological materials, known for their edge states robust against local perturbations, hold promise for next-generation quantum technologies, but remain scarce in nature and challenging to realize in static systems. The Su-Schrieffer-Heeger chain is a one-dimensional system for topological phases, although its static control is limited. To overcome these limitations, we propose to use high-frequency monochromatic driving and modulated amplitude pulses to dynamically induce and switch the Floque…

VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning
Senqiao Yang, Junyi Li, Xin Lai, Bei Yu, Hengshuang Zhao, Jiaya Jia
https://arxiv.org/abs/2507.13348

VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning
Recent advancements in vision-language models (VLMs) have improved performance by increasing the number of visual tokens, which are often significantly longer than text tokens. However, we observe that most real-world scenarios do not require such an extensive number of visual tokens. While the performance drops significantly in a small subset of OCR-related tasks, models still perform accurately in most other general VQA tasks with only 1/4 resolution. Therefore, we propose to dynamically proc…

Memento: Note-Taking for Your Future Self
Chao Wan, Albert Gong, Mihir Mishra, Carl-Leander Henneking, Claas Beger, Kilian Q. Weinberger
https://arxiv.org/abs/2506.20642

Memento: Note-Taking for Your Future Self
Large language models (LLMs) excel at reasoning-only tasks, but struggle when reasoning must be tightly coupled with retrieval, as in multi-hop question answering. To overcome these limitations, we introduce a prompting strategy that first decomposes a complex question into smaller steps, then dynamically constructs a database of facts using LLMs, and finally pieces these facts together to solve the question. We show how this three-stage strategy, which we call Memento, can boost the performanc…

EASE: Embodied Active Event Perception via Self-Supervised Energy Minimization
Zhou Chen, Sanjoy Kundu, Harsimran S. Baweja, Sathyanarayanan N. Aakur
https://arxiv.org/abs/2506.17516

EASE: Embodied Active Event Perception via Self-Supervised Energy Minimization
Active event perception, the ability to dynamically detect, track, and summarize events in real time, is essential for embodied intelligence in tasks such as human-AI collaboration, assistive robotics, and autonomous navigation. However, existing approaches often depend on predefined action spaces, annotated datasets, and extrinsic rewards, limiting their adaptability and scalability in dynamic, real-world scenarios. Inspired by cognitive theories of event perception and predictive coding, we p…

Harnessing higher-dimensional fluctuations in an information engine
Antonio Patr\'on Castro, John Bechhoefer, David A. Sivak
https://arxiv.org/abs/2507.15503

Harnessing higher-dimensional fluctuations in an information engine
We study the optimal performance of an information engine consisting of an overdamped Brownian bead confined in a controllable, $d$-dimensional harmonic trap and additionally subjected to gravity. The trap's center is updated dynamically via a feedback protocol designed such that no external work is done by the trap on the bead, while maximizing the extraction of gravitational potential energy and achieving directed motion. We show that performance strikingly improves when thermal fluctuations …

Resolving Black Hole Family Issues Among the Massive Ancestors of Very High-Spin Gravitational-Wave Events Like GW231123
Jakob Stegmann, Aleksandra Olejak, Selma E. de Mink
https://arxiv.org/abs/2507.15967

Resolving Black Hole Family Issues Among the Massive Ancestors of Very High-Spin Gravitational-Wave Events Like GW231123
The latest detection of GW231123, a binary black hole (BH) merger with exceptionally large masses and high spins for the incoming components, has been suggested as a smoking gun for hierarchical formation. In this scenario, a first generation of BHs resulting from collapsing stars form in a dense environment. Here they can assemble dynamically and undergo subsequent mergers. We discuss three challenges for the formation of a GW231123-like event inside a star cluster: 1) The high masses of the i…

Self-Adaptive and Robust Federated Spectrum Sensing without Benign Majority for Cellular Networks
Ngoc Duy Pham, Thusitha Dayaratne, Viet Vo, Shangqi Lai, Sharif Abuadbba, Hajime Suzuki, Xingliang Yuan, Carsten Rudolph
https://arxiv.org/abs/2507.12127

Self-Adaptive and Robust Federated Spectrum Sensing without Benign Majority for Cellular Networks
Advancements in wireless and mobile technologies, including 5G advanced and the envisioned 6G, are driving exponential growth in wireless devices. However, this rapid expansion exacerbates spectrum scarcity, posing a critical challenge. Dynamic spectrum allocation (DSA)--which relies on sensing and dynamically sharing spectrum--has emerged as an essential solution to address this issue. While machine learning (ML) models hold significant potential for improving spectrum sensing, their adoption …

Situational-Constrained Sequential Resources Allocation via Reinforcement Learning
Libo Zhang, Yang Chen, Toru Takisaka, Kaiqi Zhao, Weidong Li, Jiamou Liu
https://arxiv.org/abs/2506.14125

Situational-Constrained Sequential Resources Allocation via Reinforcement Learning
Sequential Resource Allocation with situational constraints presents a significant challenge in real-world applications, where resource demands and priorities are context-dependent. This paper introduces a novel framework, SCRL, to address this problem. We formalize situational constraints as logic implications and develop a new algorithm that dynamically penalizes constraint violations. To handle situational constraints effectively, we propose a probabilistic selection mechanism to overcome li…

Dynamically stable topological edge states in an extended Su-Schrieffer-Heeger ladder with balanced perturbation
E. S. Ma, K. L. Zhang, Z. Song
https://arxiv.org/abs/2506.05666

Dynamically stable topological edge states in an extended Su-Schrieffer-Heeger ladder with balanced perturbation
The on-site potentials may break the symmetry of a system, resulting in the loss of its original topology protected by the symmetry. In this work, we study the counteracting effect of non-Hermitian terms on real potentials, resulting in dynamically stable topological edge states. We show exactly for a class of systems that the spectrum remains unchanged in the presence of balanced perturbations. As a demonstration, we investigate an extended non-Hermitian Su-Schrieffer-Heeger(SSH) ladder. We fi…

A Foundation Model for Massive MIMO Precoding with an Adaptive per-User Rate-Power Tradeoff
J\'er\^ome Emery, Ali Hasanzadeh Karkan, Jean-Fran\c{c}ois Frigon, Fran\c{c}ois Leduc-Primeau
https://arxiv.org/abs/2507.18587

A Foundation Model for Massive MIMO Precoding with an Adaptive per-User Rate-Power Tradeoff
Deep learning (DL) has emerged as a solution for precoding in massive multiple-input multiple-output (mMIMO) systems due to its capacity to learn the characteristics of the propagation environment. However, training such a model requires high-quality, local datasets at the deployment site, which are often difficult to collect. We propose a transformer-based foundation model for mMIMO precoding that seeks to minimize the energy consumption of the transmitter while dynamically adapting to per-use…

Carbon burning cannot explain puffy hypervelocity white dwarfs
Natsuko Yamaguchi, Kareem El-Badry, Tin Long Sunny Wong, Ken J. Shen
https://arxiv.org/abs/2507.15952

Carbon burning cannot explain puffy hypervelocity white dwarfs
The dominant formation channel of Type Ia supernovae (SNe Ia) has been extensively studied for many years. Several hypervelocity white dwarfs (HVWDs) with space velocities of $\gtrsim 1000\,\mathrm{kms}^{-1}$ have recently been discovered. One possible origin of these stars is the dynamically-driven double-degenerate double-detonation (D6) scenario, in which an accreting sub-Chandrasekhar mass carbon-oxygen (CO) WD detonates as a SN Ia. In this scenario, the less massive WD may survive its comp…

Effective Multi-Task Learning for Biomedical Named Entity Recognition
Jo\~ao Ruano, Gon\c{c}alo M. Correia, Leonor Barreiros, Afonso Mendes
https://arxiv.org/abs/2507.18542 http…

Effective Multi-Task Learning for Biomedical Named Entity Recognition
Biomedical Named Entity Recognition presents significant challenges due to the complexity of biomedical terminology and inconsistencies in annotation across datasets. This paper introduces SRU-NER (Slot-based Recurrent Unit NER), a novel approach designed to handle nested named entities while integrating multiple datasets through an effective multi-task learning strategy. SRU-NER mitigates annotation gaps by dynamically adjusting loss computation to avoid penalizing predictions of entity types …

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes
Jiahao Qiu, Xinzhe Juan, Yimin Wang, Ling Yang, Xuan Qi, Tongcheng Zhang, Jiacheng Guo, Yifu Lu, Zixin Yao, Hongru Wang, Shilong Liu, Xun Jiang, Liu Leqi, Mengdi Wang
https://arxiv.org/abs/2506.14728

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes
While knowledge distillation has become a mature field for compressing large language models (LLMs) into smaller ones by aligning their outputs or internal representations, the distillation of LLM-based agents, which involve planning, memory, and tool use, remains relatively underexplored. Existing agent distillation methods typically replay full teacher trajectories or imitate step-by-step teacher tool usage, but they often struggle to train student agents to dynamically plan and act in novel …

Global magnetohydrodynamic simulations of the inner regions of protoplanetary discs. I. Zero-net flux regime
Matthew J. O. Roberts, Henrik N. Latter, Geoffroy Lesur
https://arxiv.org/abs/2506.16945

Global magnetohydrodynamic simulations of the inner regions of protoplanetary discs. I. Zero-net flux regime
The inner regions of protoplanetary discs, which encompass the putative habitable zone, are dynamically complex, featuring a well ionised, turbulent active inner region and a poorly ionised dead outer region. In this first paper, we investigate a base level model of the magnetohydrodynamic processes around this dead-active zone interface, using five three-dimensional global magnetohydrodynamic simulations in the zero-net flux regime. We employ physically motivated profiles for Ohmic resistivity…

VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Haichao Liu, Haoren Guo, Pei Liu, Benshan Ma, Yuxiang Zhang, Jun Ma, Tong Heng Lee
https://arxiv.org/abs/2507.15266

VLM-UDMC: VLM-Enhanced Unified Decision-Making and Motion Control for Urban Autonomous Driving
Scene understanding and risk-aware attentions are crucial for human drivers to make safe and effective driving decisions. To imitate this cognitive ability in urban autonomous driving while ensuring the transparency and interpretability, we propose a vision-language model (VLM)-enhanced unified decision-making and motion control framework, named VLM-UDMC. This framework incorporates scene reasoning and risk-aware insights into an upper-level slow system, which dynamically reconfigures the optim…

Leveraging Multi-Instance GPUs through moldable task scheduling
Jorge Villarrubia, Luis Costero, Francisco D. Igual, Katzalin Olcoz
https://arxiv.org/abs/2507.13601

Leveraging Multi-Instance GPUs through moldable task scheduling
NVIDIA MIG (Multi-Instance GPU) allows partitioning a physical GPU into multiple logical instances with fully-isolated resources, which can be dynamically reconfigured. This work highlights the untapped potential of MIG through moldable task scheduling with dynamic reconfigurations. Specifically, we propose a makespan minimization problem for multi-task execution under MIG constraints. Our profiling shows that assuming monotonicity in task work with respect to resources is not viable, as is usu…

On the origin and dynamical evolution of Jupiter's moon Amalthea
Ian R. Brunton, Konstantin Batygin
https://arxiv.org/abs/2507.17464 https://arxiv.org/…

On the origin and dynamical evolution of Jupiter's moon Amalthea
Interior to the orbits of Jupiter's iconic Galilean moons are four small satellites with individual mean radii, $R\lesssim 84$ km. Multiple lines of evidence suggest that these bodies formed at a more distant location in Jupiter's circumplanetary disk before coming to reside at their current short-period orbits. Nonetheless, how these moons dynamically evolved to such a location has yet to be explained in the emerging paradigm of Jovian satellite formation. Here, we present a quantitative model…

Closed-Form and Boundary Expressions for Task-Success Probability in Status-Driven Systems
Jianpeng Qi, Chao Liu, Rui Wang, Junyu Dong, Yanwei Yu
https://arxiv.org/abs/2507.17195

Closed-Form and Boundary Expressions for Task-Success Probability in Status-Driven Systems
Timely and efficient dissemination of server status is critical in compute-first networking systems, where user tasks arrive dynamically and computing resources are limited and stochastic. In such systems, the access point plays a key role in forwarding tasks to a server based on its latest received server status. However, modeling the task-success probability suffering the factors of stochastic arrivals, limited server capacity, and bidirectional link delays. Therefore, we introduce a unified …

Assessing the Benefits of Ground Vehicles as Moving Urban Base Stations
Laura Finarelli, Falko Dressler, Marco Ajmone Marsan, Gianluca Rizzo
https://arxiv.org/abs/2507.15423

Assessing the Benefits of Ground Vehicles as Moving Urban Base Stations
In the evolution towards 6G user-centric networking, the moving network (MN) paradigm can play an important role. In a MN, some small cell base stations (BS) are installed on top of vehicles, and enable a more dynamic, flexible and sustainable, network operation. By "following" the users movements and adapting dynamically to their requests, the MN paradigm enables a more efficient utilization of network resources, mitigating the need for dense small cell BS deployments at the cost of an increas…

Group then Scale: Dynamic Mixture-of-Experts Multilingual Language Model
Chong Li, Yingzhuo Deng, Jiajun Zhang, Chengqing Zong
https://arxiv.org/abs/2506.12388

Group then Scale: Dynamic Mixture-of-Experts Multilingual Language Model
The curse of multilinguality phenomenon is a fundamental problem of multilingual Large Language Models (LLMs), where the competition between massive languages results in inferior performance. It mainly comes from limited capacity and negative transfer between dissimilar languages. To address this issue, we propose a method to dynamically group and scale up the parameters of multilingual LLM while boosting positive transfer among similar languages. Specifically, the model is first tuned on monol…