Tootfinder

Aquifer system faces decline in multiple regions, study shows #Washington

Aquifer system faces decline in multiple regions, study shows
Groundwater is declining across Eastern Washington's complex, interconnected aquifer system, as people draw on it for irrigation, drinking and other uses at a pace that threatens its sustainability, according to a new study by a Washington State University researcher.

AWorld: Dynamic Multi-Agent System with Stable Maneuvering for Robust GAIA Problem Solving
Zhitian Xie, Qintong Wu, Chengyue Yu, Chenyi Zhuang, Jinjie Gu
https://arxiv.org/abs/2508.09889

AWorld: Dynamic Multi-Agent System with Stable Maneuvering for Robust GAIA Problem Solving
The rapid advancement of large language models (LLMs) has empowered intelligent agents to leverage diverse external tools for solving complex real-world problems. However, as agents increasingly depend on multiple tools, they encounter new challenges: extended contexts from disparate sources and noisy or irrelevant tool outputs can undermine system reliability and accuracy. These challenges underscore the necessity for enhanced stability in agent-based systems. To address this, we introduce dyn…

Normative Moral Pluralism for AI: A Framework for Deliberation in Complex Moral Contexts
David-Doron Yaacov
https://arxiv.org/abs/2508.08333 https://arxiv.…

Normative Moral Pluralism for AI: A Framework for Deliberation in Complex Moral Contexts
The conceptual framework proposed in this paper centers on the development of a deliberative moral reasoning system - one designed to process complex moral situations by generating, filtering, and weighing normative arguments drawn from diverse ethical perspectives. While the framework is rooted in Machine Ethics, it also makes a substantive contribution to Value Alignment by outlining a system architecture that links structured moral reasoning to action under time constraints. Grounded in norm…

Agentic Document Extraction – #Python Library for Complex Document Processing 📄
powered by https://landing.ai
🔍 Extracts structured data from complex documents with tables, pictures & charts - retu…

The Cardinals are 2-0, so why does it feel so uneasy after their win over Carolina? https://www.nytimes.com/athletic/6629796/2025/09/14/arizona-cardinals-beat-carolina-panthers-2-0/

Ukraine behind new pipeline explosion in Siberia that supplies Russian military-industrial complex, source claims: https://benborges.xyz/2025/07/11/ukraine-behind-new-pipeline-explosion.html

Charged Proca Stars
Yahir Mio, Miguel Alcubierre
https://arxiv.org/abs/2508.09081 https://arxiv.org/pdf/2508.09081

Charged Proca Stars
We consider self-gravitating stationary configurations of a charged massive complex Proca field, also known as charged Proca stars, in the particular case of spherical symmetry. We first present a general 3+1 decomposition of the Einstein--Maxwell--Proca system, starting from the action and field equations. We then restrict our system to the case of spherical symmetry and, after imposing a harmonic time dependence ansatz for the Proca field, we construct families of charged Proca stars for diff…

Vector-Centric Machine Learning Systems: A Cross-Stack Approach
Wenqi Jiang
https://arxiv.org/abs/2508.08469 https://arxiv.org/pdf/2508.08469

Vector-Centric Machine Learning Systems: A Cross-Stack Approach
Today, two major trends are shaping the evolution of ML systems. First, modern AI systems are becoming increasingly complex, often integrating components beyond the model itself. A notable example is Retrieval-Augmented Generation (RAG), which incorporates not only multiple models but also vector databases, leading to heterogeneity in both system components and underlying hardware. Second, with the end of Moore's Law, achieving high system efficiency is no longer feasible without accounting for…

Transforming Questions and Documents for Semantically Aligned Retrieval-Augmented Generation
Seokgi Lee
https://arxiv.org/abs/2508.09755 https://arxiv.org/…

Transforming Questions and Documents for Semantically Aligned Retrieval-Augmented Generation
We introduce a novel retrieval-augmented generation (RAG) framework tailored for multihop question answering. First, our system uses large language model (LLM) to decompose complex multihop questions into a sequence of single-hop subquestions that guide document retrieval. This decomposition mitigates the ambiguity inherent in multi-hop queries by clearly targeting distinct knowledge facets. Second, instead of embedding raw or chunked documents directly, we generate answerable questions from ea…

Caught in the Game: On the History and Evolution of Web Browser Gaming
#history

VA-Blueprint: Uncovering Building Blocks for Visual Analytics System Design
Leonardo Ferreira, Gustavo Moreira, Fabio Miranda
https://arxiv.org/abs/2508.07497 https://

VA-Blueprint: Uncovering Building Blocks for Visual Analytics System Design
Designing and building visual analytics (VA) systems is a complex, iterative process that requires the seamless integration of data processing, analytics capabilities, and visualization techniques. While prior research has extensively examined the social and collaborative aspects of VA system authoring, the practical challenges of developing these systems remain underexplored. As a result, despite the growing number of VA systems, there are only a few structured knowledge bases to guide their d…

Spin-Orbit Structure and Helicity Anomaly in Relativistic Electron Vortex Beams
Zhongze Guo, Bei Xu, Qiang Gu
https://arxiv.org/abs/2507.08493 https://

Spin-Orbit Structure and Helicity Anomaly in Relativistic Electron Vortex Beams
The relativistic electron vortex beam (REVB) has attracted increasing attention due to its nontrivial spin-orbit structure recently. As relativistic electrons are governed by the Dirac equation, exact solutions to this equation provide the most reliable starting point for understanding angular momentum characteristics of REVBs. In this work, a set of exact eigensolutions of the Dirac equation are derived in a complex cylindrical coordinate system using a generalized series expansion method. We …

Algebraic hyperbolicity of adjoint linear systems on spherical varieties
Minseong Kwon, Haesong Seo
https://arxiv.org/abs/2508.09414 https://arxiv.org/pdf/…

Algebraic hyperbolicity of adjoint linear systems on spherical varieties
Moraga and Yeong conjectured that for a smooth complex projective variety $X$ of dimension $n$, an ample line bundle $A$ on $X$ and an integer $m \ge 3 n + 1$, very general elements of the adjoint linear system $|ω_{X} \otimes A^{\otimes m}|$ are algebraically hyperbolic. We prove the conjecture for spherical varieties with smooth orbit closures. As a corollary, we conclude that the conjecture holds for horospherical varieties, and for toroidal spherical varieties. Furthermore, for a…

Modular Vacuum-Based Fixturing System for Adaptive Disassembly Workspace Integration
Haohui Pan, Takuya Kiyokawa, Tomoki Ishikura, Shingo Hamada, Genichiro Matsuda, Kensuke Harada
https://arxiv.org/abs/2508.05936

Modular Vacuum-Based Fixturing System for Adaptive Disassembly Workspace Integration
The disassembly of small household appliances poses significant challenges due to their complex and curved geometries, which render traditional rigid fixtures inadequate. In this paper, we propose a modular vacuum-based fixturing system that leverages commercially available balloon-type soft grippers to conform to arbitrarily shaped surfaces and provide stable support during screw-removal tasks. To enable a reliable deployment of the system, we develop a stability-aware planning framework that …

ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System
Dong Han, Zhehong Ai, Pengxiang Cai, Shuzhou Sun, Shanya Lu, Jianpeng Chen, Ben Gao, Lingli Ge, Weida Wang, Xiangxin Zhou, Xihui Liu, Mao Su, Wanli Ouyang, Lei Bai, Dongzhan Zhou, Tao XU, Yuqiang Li, Shufei Zhang
https://arxiv.org/abs/2509.08736

ChemBOMAS: Accelerated BO in Chemistry with LLM-Enhanced Multi-Agent System
The efficiency of Bayesian optimization (BO) in chemistry is often hindered by sparse experimental data and complex reaction mechanisms. To overcome these limitations, we introduce ChemBOMAS, a new framework named LLM-Enhanced Multi-Agent System for accelerating BO in chemistry. ChemBOMAS's optimization process is enhanced by LLMs and synergistically employs two strategies: knowledge-driven coarse-grained optimization and data-driven fine-grained optimization. First, in the knowledge-driven coa…

OpenAI releases GPT-5 pro, a version with extended reasoning exclusive to ChatGPT Pro subscribers, saying it scored 88.4% without tools on the GPQA benchmark (Maximilian Schreiner/The Decoder)
https://the-decoder.com/openai-claims-

OpenAI launches GPT-5 as a unified system with adaptive reasoning for complex tasks
OpenAI has unveiled GPT-5, a new AI system that builds on the reasoning advances of the o1 and o3 models and unifies every previous model line into a single adaptive architecture.

🚀 Demonstrates practical #AI agent development without complex abstractions or extensive engineering overhead
https://ampcode.com/how-to-build-an-agent

Besondere Anforderungen des automatisierten Fahrens an den Entwurf
Robert Graubohm, Markus Maurer
https://arxiv.org/abs/2508.09731 https://arxiv.org/pdf/25…

Besondere Anforderungen des automatisierten Fahrens an den Entwurf
The development of automated vehicles and automated driving functions is an exceptionally complex task that requires the integration of numerous, sometimes conflicting interests and various constraints already in the early stages of system design. This chapter explains important challenges in concept specifications for automated driving and presents a systematic process model that contributes to overcoming the special requirements in this field. In addition, it describes the successful implemen…

Hybrid-Precision Block-Jacobi Preconditioned GMRES Solver for Linear System in Circuit Simulation
Zijian Zhang, Rui Hong, Xuesong Chen, Shuting Cai
https://arxiv.org/abs/2509.09139

Hybrid-Precision Block-Jacobi Preconditioned GMRES Solver for Linear System in Circuit Simulation
As integrated circuits become increasingly complex, the demand for efficient and accurate simulation solvers continues to rise. Traditional solvers often struggle with large-scale sparse systems, leading to prolonged simulation times and reduced accuracy. In this paper, a hybrid-precision block-Jacobi preconditioned GMRES solver is proposed to solve the large sparse system in circuit simulation. The proposed method capitalizes on the structural sparsity and block properties of circuit matrices,…

by Joachim Luetke
#art

Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis
Aina Ferr\`a Marc\'us, Robert Jankowski, Meritxell Vila Mi\~nana, Carles Casacuberta, M. \'Angeles Serrano
https://arxiv.org/abs/2509.08350

Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis
Many complex networks, ranging from social to biological systems, exhibit structural patterns consistent with an underlying hyperbolic geometry. Revealing the dimensionality of this latent space can disentangle the structural complexity of communities, impact efficient network navigation, and fundamentally shape connectivity and system behavior. We introduce a novel topological data analysis weighting scheme for graphs, based on chordless cycles, aimed at estimating the dimensionality of networ…

Create sufficiently complex situations that they surpass the attenuation capacity of the governing system, and do so at a rate that is faster than the relaxation time of that governing system.
#Cybernetics #Anarchism

Finite-Time Splash in Free Boundary Problem of 3D Neo-Hookean Elastodynamics
Wei Zhang, Jie Fu, Chengchun Hao
https://arxiv.org/abs/2508.08751 https://arxi…

Finite-Time Splash in Free Boundary Problem of 3D Neo-Hookean Elastodynamics
This paper establishes finite-time splash singularity formation for 3D viscous incompressible neo-Hookean elastodynamics with free boundaries. The system features mixed stress-kinematic conditions where viscous-elastic stresses balance pressure forces at the evolving interface -- a configuration generating complex boundary integrals that distinguish it from Navier-Stokes or MHD systems. To address this challenge, we employ a Lagrangian framework inspired by Coutand and Shkoller (2019), developi…

Defending Against Prompt Injection With a Few DefensiveTokens
Sizhe Chen, Yizhu Wang, Nicholas Carlini, Chawin Sitawarin, David Wagner
https://arxiv.org/abs/2507.07974

Defending Against Prompt Injection With a Few DefensiveTokens
When large language model (LLM) systems interact with external data to perform complex tasks, a new attack, namely prompt injection, becomes a significant threat. By injecting instructions into the data accessed by the system, the attacker is able to override the initial user task with an arbitrary task directed by the attacker. To secure the system, test-time defenses, e.g., defensive prompting, have been proposed for system developers to attain security only when needed in a flexible manner. …

Anomalous diffusion in coupled viscoelastic media: A fractional Langevin equation approach
Chan Lim, Jae-Hyung Jeon
https://arxiv.org/abs/2507.08291 https:…

Anomalous diffusion in coupled viscoelastic media: A fractional Langevin equation approach
Anomalous diffusion often arises in complex environments where viscoelastic or crowded conditions influence particle motion. In many biological and soft-matter systems, distinct components of the medium exhibit unique viscoelastic responses, resulting in time-dependent changes in the observed diffusion exponents. Here, we develop a theoretical model of two particles, each embedded in a distinct viscoelastic medium, and coupled via a harmonic potential. By formulating and solving a system of cou…

Retrieval-Augmented Multi-Agent System for Rapid Statement of Work Generation
Amulya Suravarjhula, Rashi Chandrashekhar Agrawal, Sakshi Jayesh Patel, Rahul Gupta
https://arxiv.org/abs/2508.07569

Retrieval-Augmented Multi-Agent System for Rapid Statement of Work Generation
Drafting a Statement of Work (SOW) is a vital part of business and legal projects. It outlines key details like deliverables, timelines, responsibilities, and legal terms. However, creating these documents is often a slow and complex process. It usually involves multiple people, takes several days, and leaves room for errors or outdated content. This paper introduces a new AI-driven automation system that makes the entire SOW drafting process faster, easier, and more accurate. Instead of relyin…

Dissecting NGC 3132: Tracing the mass-loss history of the southern ring planetary nebula
K. Bouvis, S. Akras, H. Monteiro, L. Konstantinou, P. Boumis, J. Garc\'ia-Rojas, D. R. Gon\c{c}alves, A. Monreal-Ibero, I. Aleman, K. N. Gourgouliatos
https://arxiv.org/abs/2507.08079

Dissecting NGC 3132: Tracing the mass-loss history of the southern ring planetary nebula
Central to our understanding of stellar evolution and its impact on processes in our Galaxy and across the Universe is the study of mass loss. While the general framework is well established, recent JWST observations of objects like NGC 3132 have revealed intricate nebular structures, suggesting complex mass-loss processes likely driven by multiple star system at its core. These findings pose new challenges for the currently available investigation tools. The primary goal of this study is the f…

“Artificially complex structures […] pose a number of practical and intellectual problems; man is responsible for their synthesis, regulation, and continued maintenance. In almost no instance can artificial-rational systems be built and left alone. They require continued attention, rebuilding, and repair. Eternal vigilance is the price of artificial complexity.”
—Langdon Winner (1977), Autonomous Technology, p. 183

“Artificially complex structures […] pose a number of practical and intellectual problems; man is responsible for their synthesis, regulation, and continued maintenance. In almost no instance can artificial-rational systems be built and left alone. They require continued attention, rebuilding, and repair. Eternal vigilance is the price of artificial complexity.”
—Langdon Winner (1977), Autonomous Technology, p. 183

“Artificially complex structures […] pose a number of practical and intellectual problems; man is responsible for their synthesis, regulation, and continued maintenance. In almost no instance can artificial-rational systems be built and left alone. They require continued attention, rebuilding, and repair. Eternal vigilance is the price of artificial complexity.”
—Langdon Winner (1977), Autonomous Technology, p. 183

To Trade or Not to Trade: An Agentic Approach to Estimating Market Risk Improves Trading Decisions
Dimitrios Emmanoulopoulos, Ollie Olby, Justin Lyon, Namid R. Stillman
https://arxiv.org/abs/2507.08584

To Trade or Not to Trade: An Agentic Approach to Estimating Market Risk Improves Trading Decisions
Large language models (LLMs) are increasingly deployed in agentic frameworks, in which prompts trigger complex tool-based analysis in pursuit of a goal. While these frameworks have shown promise across multiple domains including in finance, they typically lack a principled model-building step, relying instead on sentiment- or trend-based analysis. We address this gap by developing an agentic system that uses LLMs to iteratively discover stochastic differential equations for financial time serie…

The Role of Community Detection Methods in Performance Variations of Graph Mining Tasks
Shrabani Ghosh, Erik Saule
https://arxiv.org/abs/2509.09045 https://

The Role of Community Detection Methods in Performance Variations of Graph Mining Tasks
In real-world scenarios, large graphs represent relationships among entities in complex systems. Mining these large graphs often containing millions of nodes and edges helps uncover structural patterns and meaningful insights. Dividing a large graph into smaller subgraphs facilitates complex system analysis by revealing local information. Community detection extracts clusters or communities of graphs based on statistical methods and machine learning models using various optimization techniques.…

🤖 Models available: WebSailor-3B on #HuggingFace & WebDancer-QwQ-32B for complex reasoning
🛠️ Complete post-training methodology with DUPO algorithm for efficient agentic RL
https://github.com/Alibaba-NLP/W…

Narrative Memory in Machines: Multi-Agent Arc Extraction in Serialized TV
Roberto Balestri, Guglielmo Pescatore
https://arxiv.org/abs/2508.07010 https://ar…

Narrative Memory in Machines: Multi-Agent Arc Extraction in Serialized TV
Serialized television narratives present significant analytical challenges due to their complex, temporally distributed storylines that necessitate sophisticated information management. This paper introduces a multi-agent system (MAS) designed to extract and analyze narrative arcs by implementing principles of computational memory architectures. The system conceptualizes narrative understanding through analogues of human memory: Large Language Models (LLMs) provide a form of semantic memory for…

Introduction to Sachdev-Ye-Kitaev Model: A Strongly Correlated System Perspective
Rishabh Jha
https://arxiv.org/abs/2507.07195 https://

Introduction to Sachdev-Ye-Kitaev Model: A Strongly Correlated System Perspective
The Sachdev-Ye-Kitaev (SYK) model delivers an analytically tractable framework for exotic strongly correlated phases where conventional paradigms like Landau's Fermi liquid theory collapse. This review offers a pedagogical introduction to the SYK physics, highlighting its unique capacity to model \textit{strange metals} -- systems exhibiting linear-in-temperature resistivity, Planckian dissipation, and quasiparticle breakdown. We systematically construct both Majorana and complex fermion varian…

Compositional Inductive Invariant Inference via Assume-Guarantee Reasoning
Ian Dardik, Eunsuk Kang
https://arxiv.org/abs/2509.06250 https://arxiv.org/pdf/2…

Compositional Inductive Invariant Inference via Assume-Guarantee Reasoning
A common technique for verifying the safety of complex systems is the inductive invariant method. Inductive invariants are inductive formulas that overapproximate the reachable states of a system and imply a desired safety property. However, inductive invariants are notoriously complex, which makes inductive invariant inference a challenging problem. In this work, we observe that inductive invariant formulas are complex primarily because they must be closed over the transition relation of an en…

Improving sampling of binding free energy differences between covalently bound ligands in alternate binding pockets using MT-REXEE
Anika Friedman, Michael Shirts
https://arxiv.org/abs/2508.06720

Improving sampling of binding free energy differences between covalently bound ligands in alternate binding pockets using MT-REXEE
The primary limitation for the application of alchemical free energy methods to a wider variety of complex molecular systems in achieving reasonable sampling. Flexible binding complexes often have high free energy barriers, which require prohibitively long simulations to sample sufficiently to obtain reliable free energy estimates. An example of such a system is the FabB--acyl chain complex, which features acyl chain substrates from 4 to 16 carbons in length. Previous experimental evidence supp…

Ukraine war latest: Kyiv behind new pipeline explosion in Siberia, drone strikes reported at Russian aircraft plant: https://benborges.xyz/2025/07/11/ukraine-war-latest-kyiv-behind.html

Fast Collection Operations from Indexed Stream Fusion
Scott Kovach, Praneeth Kolichala, Kyle A. Miller, David Broman, Fredrik Kjolstad
https://arxiv.org/abs/2507.06456

Fast Collection Operations from Indexed Stream Fusion
We present a system of efficient methods for traversing and combining associative collection data structures. A distinguishing feature of the system is that, like traditional sequential iterator libraries, it does not require specialized compiler infrastructure or staged compilation for efficiency and composability. By using a representation based on indexed streams, the library can express complex joins over input collections while using no intermediate allocations. We implement the library fo…

Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Chun-Hsiao Yeh, Yilin Wang, Nanxuan Zhao, Richard Zhang, Yuheng Li, Yi Ma, Krishna Kumar Singh
https://arxiv.org/abs/2507.05259

Beyond Simple Edits: X-Planner for Complex Instruction-Based Image Editing
Recent diffusion-based image editing methods have significantly advanced text-guided tasks but often struggle to interpret complex, indirect instructions. Moreover, current models frequently suffer from poor identity preservation, unintended edits, or rely heavily on manual masks. To address these challenges, we introduce X-Planner, a Multimodal Large Language Model (MLLM)-based planning system that effectively bridges user intent with editing model capabilities. X-Planner employs chain-of-thou…

ViDove: A Translation Agent System with Multimodal Context and Memory-Augmented Reasoning
Yichen Lu, Wei Dai, Jiaen Liu, Ching Wing Kwok, Zongheng Wu, Xudong Xiao, Ao Sun, Sheng Fu, Jianyuan Zhan, Yian Wang, Takatomo Saito, Sicheng Lai
https://arxiv.org/abs/2507.07306

ViDove: A Translation Agent System with Multimodal Context and Memory-Augmented Reasoning
LLM-based translation agents have achieved highly human-like translation results and are capable of handling longer and more complex contexts with greater efficiency. However, they are typically limited to text-only inputs. In this paper, we introduce ViDove, a translation agent system designed for multimodal input. Inspired by the workflow of human translators, ViDove leverages visual and contextual background information to enhance the translation process. Additionally, we integrate a multimo…

Benelux Prime Ministers' Summit Joint Declaration Luxembourg
10 SEP 2025
"Security, Safety & Resilience
We reaffirm our commitment to advancing societal preparedness and resilience across the Benelux region. In an era marked by increasingly complex threats - from hybrid challenges to natural disasters - it is vital to foster unity, readiness, and shared solutions.

collins_yeast: Collins yeast interactome (2007)
Network of protein-protein interactions in Saccharomyces cerevisiae (budding yeast), measured by co-complex associations identified by high-throughput affinity purification and mass spectrometry (AP/MS).
This network has 1622 nodes and 9070 edges.
Tags: Biological, Protein interactions, Unweighted

KMT-2024-BLG-0404L: A triple microlensing system consisting of a star, a brown dwarf, and a planet
Cheongho Han, Andrzej Udalski, Chung-Uk Lee, Yoon-Hyun Ryu, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Kyu-Ha Hwang, Youn Kil Jung, In-Gu Shin, Yossi Shvartzvald, Jennifer C. Yee, Hongjing Yang, Weicheng Zang, Doeon Kim, Dong-Jin Kim, Byeong-Gon Park, Richard W. Pogge, Przemek Mr\'oz, Micha{\l} K. Szyma\'nski, Jan Skowron, Rados{\l}aw Poleski, Igor Soszy\'nski, Pawe{\l} Pi…

KMT-2024-BLG-0404L: A triple microlensing system consisting of a star, a brown dwarf, and a planet
We have investigated the lensing event KMT-2024-BLG-0404. The light curve of the event exhibited a complex structure with multiple distinct features, including two prominent caustic spikes, two cusp bumps, and a brief discontinuous feature between the caustic spikes. While a binary-lens model captured the general anomaly pattern, it could not account for a discontinuous anomaly feature between the two caustic spikes. To explore the origin of the unexplained feature, we conducted more advanced m…

Gall's Law: "a complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over with a working simple system."
— John Gall (1975) Systemantics: How Systems Really Work and How They Fail
#KISS

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions
Dhruv S. Kushwaha, Zoleikha A. Biron
https://arxiv.org/abs/2508.09128 https://…

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions
Reinforcement learning (RL) has proven to be particularly effective in solving complex decision-making problems for a wide range of applications. From a control theory perspective, RL can be considered as an adaptive optimal control scheme. Lyapunov and barrier functions are the most commonly used certificates to guarantee system stability for a proposed/derived controller and constraint satisfaction guarantees, respectively, in control theoretic approaches. However, compared to theoretical gua…

Componentwise Automata Learning for System Integration (Extended Version)
Hiroya Fujinami, Masaki Waga, Jie An, Kohei Suenaga, Nayuta Yanagisawa, Hiroki Iseri, Ichiro Hasuo
https://arxiv.org/abs/2508.04458

Componentwise Automata Learning for System Integration (Extended Version)
Compositional automata learning is attracting attention as an analysis technique for complex black-box systems. It exploits a target system's internal compositional structure to reduce complexity. In this paper, we identify system integration -- the process of building a new system as a composite of potentially third-party and black-box components -- as a new application domain of compositional automata learning. Accordingly, we propose a new problem setting, where the learner has direct access…

"Multilingual Scholarly Publishing and Artificial Intelligence Translation Tools: Weighing Social Justice and Climate Justice"
https://doi.org/10.3998/jep.7100

Way More Than the Sum of Their Parts: From Statistical to Structural Mixtures
James P. Crutchfield
https://arxiv.org/abs/2507.07343 https://

Way More Than the Sum of Their Parts: From Statistical to Structural Mixtures
We show that mixtures comprised of multicomponent systems typically are much more structurally complex than the sum of their parts; sometimes, infinitely more complex. We contrast this with the more familiar notion of statistical mixtures, demonstrating how statistical mixtures miss key aspects of emergent hierarchical organization. This leads us to identify a new kind of structural complexity inherent in multicomponent systems and to draw out broad consequences for system ergodicity.

Network-Specific Models for Multimodal Brain Response Prediction
Andrea Corsico, Giorgia Rigamonti, Simone Zini, Luigi Celona, Paolo Napoletano
https://arxiv.org/abs/2508.06499 …

Network-Specific Models for Multimodal Brain Response Prediction
In this work, we present a network-specific approach for predicting brain responses to complex multimodal movies, leveraging the Yeo 7-network parcellation of the Schaefer atlas. Rather than treating the brain as a homogeneous system, we grouped the seven functional networks into four clusters and trained separate multi-subject, multi-layer perceptron (MLP) models for each. This architecture supports cluster-specific optimization and adaptive memory modeling, allowing each model to adjust tempo…

ElliottAgents: A Natural Language-Driven Multi-Agent System for Stock Market Analysis and Prediction
Jaros{\l}aw A. Chudziak, Micha{\l} Wawer
https://arxiv.org/abs/2507.03435

ElliottAgents: A Natural Language-Driven Multi-Agent System for Stock Market Analysis and Prediction
This paper presents ElliottAgents, a multi-agent system leveraging natural language processing (NLP) and large language models (LLMs) to analyze complex stock market data. The system combines AI-driven analysis with the Elliott Wave Principle to generate human-comprehensible predictions and explanations. A key feature is the natural language dialogue between agents, enabling collaborative analysis refinement. The LLM-enhanced architecture facilitates advanced language understanding, reasoning, …

ROS Help Desk: GenAI Powered, User-Centric Framework for ROS Error Diagnosis and Debugging
Kavindie Katuwandeniya, Samith Rajapaksha Jayasekara Widhanapathirana
https://arxiv.org/abs/2507.07846

ROS Help Desk: GenAI Powered, User-Centric Framework for ROS Error Diagnosis and Debugging
As the robotics systems increasingly integrate into daily life, from smart home assistants to the new-wave of industrial automation systems (Industry 4.0), there's an increasing need to bridge the gap between complex robotic systems and everyday users. The Robot Operating System (ROS) is a flexible framework often utilised in writing robot software, providing tools and libraries for building complex robotic systems. However, ROS's distributed architecture and technical messaging system create b…

Emergent morphogenesis via planar fabrication enabled by a reduced model of composites
Yupeng Zhang, Adam Alon, M. Khalid Jawed
https://arxiv.org/abs/2508.08198 https://

Emergent morphogenesis via planar fabrication enabled by a reduced model of composites
The ability to engineer complex three-dimensional shapes from planar sheets with precise, programmable control underpins emerging technologies in soft robotics, reconfigurable devices, and functional materials. Here, we present a reduced-order numerical and experimental framework for a bilayer system consisting of a stimuli-responsive thermoplastic sheet (Shrinky Dink) bonded to a kirigami-patterned, inert plastic layer. Upon uniform heating, the active layer contracts while the patterned layer…

Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems
Yutong Wu, Jie Zhang, Yiming Li, Chao Zhang, Qing Guo, Nils Lukas, Tianwei Zhang
https://arxiv.org/abs/2508.09230 h…

Cowpox: Towards the Immunity of VLM-based Multi-Agent Systems
Vision Language Model (VLM)-based agents are stateful, autonomous entities capable of perceiving and interacting with their environments through vision and language. Multi-agent systems comprise specialized agents who collaborate to solve a (complex) task. A core security property is robustness, stating that the system should maintain its integrity under adversarial attacks. However, the design of existing multi-agent systems lacks the robustness consideration, as a successful exploit against o…

Tool for Supporting Debugging and Understanding of Normative Requirements Using LLMs
Alex Kleijwegt, Sinem Getir Yaman, Radu Calinescu
https://arxiv.org/abs/2507.05504

Tool for Supporting Debugging and Understanding of Normative Requirements Using LLMs
Normative requirements specify social, legal, ethical, empathetic, and cultural (SLEEC) norms that must be observed by a system. To support the identification of SLEEC requirements, numerous standards and regulations have been developed. These requirements are typically defined by stakeholders in the non-technical system with diverse expertise (e.g., ethicists, lawyers, social scientists). Hence, ensuring their consistency and managing the requirement elicitation process are complex and error-p…

LLM-based IR-system for Bank Supervisors
Ilias Aarab
https://arxiv.org/abs/2508.02945 https://arxiv.org/pdf/2508.02945

LLM-based IR-system for Bank Supervisors
Bank supervisors face the complex task of ensuring that new measures are consistently aligned with historical precedents. To address this challenge, we introduce a novel Information Retrieval (IR) System tailored to assist supervisors in drafting both consistent and effective measures. This system ingests findings from on-site investigations. It then retrieves the most relevant historical findings and their associated measures from a comprehensive database, providing a solid basis for superviso…

Physics-Informed Neural Networks with Hard Nonlinear Equality and Inequality Constraints
Ashfaq Iftakher, Rahul Golder, M. M. Faruque Hasan
https://arxiv.org/abs/2507.08124 https://arxiv.org/pdf/2507.08124 https://arxiv.org/html/2507.08124
arXiv:2507.08124v1 Announce Type: new
Abstract: Traditional physics-informed neural networks (PINNs) do not guarantee strict constraint satisfaction. This is problematic in engineering systems where minor violations of governing laws can significantly degrade the reliability and consistency of model predictions. In this work, we develop KKT-Hardnet, a PINN architecture that enforces both linear and nonlinear equality and inequality constraints up to machine precision. It leverages a projection onto the feasible region through solving Karush-Kuhn-Tucker (KKT) conditions of a distance minimization problem. Furthermore, we reformulate the nonlinear KKT conditions using log-exponential transformation to construct a general sparse system with only linear and exponential terms, thereby making the projection differentiable. We apply KKT-Hardnet on both test problems and a real-world chemical process simulation. Compared to multilayer perceptrons and PINNs, KKT-Hardnet achieves higher accuracy and strict constraint satisfaction. This approach allows the integration of domain knowledge into machine learning towards reliable hybrid modeling of complex systems.
toXiv_bot_toot

Should we teach vibe coding? Here's why not.
Should AI coding be taught in undergrad CS education?
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I teach undergraduate computer science labs, including for intro and more-advanced core courses. I don't publish (non-negligible) scholarly work in the area, but I've got years of craft expertise in course design, and I do follow the academic literature to some degree. In other words, In not the world's leading expert, but I have spent a lot of time thinking about course design, and consider myself competent at it, with plenty of direct experience in what knowledge & skills I can expect from students as they move through the curriculum.
I'm also strongly against most uses of what's called "AI" these days (specifically, generative deep neutral networks as supplied by our current cadre of techbro). There are a surprising number of completely orthogonal reasons to oppose the use of these systems, and a very limited number of reasonable exceptions (overcoming accessibility barriers is an example). On the grounds of environmental and digital-commons-pollution costs alone, using specifically the largest/newest models is unethical in most cases.
But as any good teacher should, I constantly question these evaluations, because I worry about the impact on my students should I eschew teaching relevant tech for bad reasons (and even for his reasons). I also want to make my reasoning clear to students, who should absolutely question me on this. That inspired me to ask a simple question: ignoring for one moment the ethical objections (which we shouldn't, of course; they're very stark), at what level in the CS major could I expect to teach a course about programming with AI assistance, and expect students to succeed at a more technically demanding final project than a course at the same level where students were banned from using AI? In other words, at what level would I expect students to actually benefit from AI coding "assistance?"
To be clear, I'm assuming that students aren't using AI in other aspects of coursework: the topic of using AI to "help you study" is a separate one (TL;DR it's gross value is not negative, but it's mostly not worth the harm to your metacognitive abilities, which AI-induced changes to the digital commons are making more important than ever).
So what's my answer to this question?
If I'm being incredibly optimistic, senior year. Slightly less optimistic, second year of a masters program. Realistic? Maybe never.
The interesting bit for you-the-reader is: why is this my answer? (Especially given that students would probably self-report significant gains at lower levels.) To start with, [this paper where experienced developers thought that AI assistance sped up their work on real tasks when in fact it slowed it down] (https://arxiv.org/abs/2507.09089) is informative. There are a lot of differences in task between experienced devs solving real bugs and students working on a class project, but it's important to understand that we shouldn't have a baseline expectation that AI coding "assistants" will speed things up in the best of circumstances, and we shouldn't trust self-reports of productivity (or the AI hype machine in general).
Now we might imagine that coding assistants will be better at helping with a student project than at helping with fixing bugs in open-source software, since it's a much easier task. For many programming assignments that have a fixed answer, we know that many AI assistants can just spit out a solution based on prompting them with the problem description (there's another elephant in the room here to do with learning outcomes regardless of project success, but we'll ignore this over too, my focus here is on project complexity reach, not learning outcomes). My question is about more open-ended projects, not assignments with an expected answer. Here's a second study (by one of my colleagues) about novices using AI assistance for programming tasks. It showcases how difficult it is to use AI tools well, and some of these stumbling blocks that novices in particular face.
But what about intermediate students? Might there be some level where the AI is helpful because the task is still relatively simple and the students are good enough to handle it? The problem with this is that as task complexity increases, so does the likelihood of the AI generating (or copying) code that uses more complex constructs which a student doesn't understand. Let's say I have second year students writing interactive websites with JavaScript. Without a lot of care that those students don't know how to deploy, the AI is likely to suggest code that depends on several different frameworks, from React to JQuery, without actually setting up or including those frameworks, and of course three students would be way out of their depth trying to do that. This is a general problem: each programming class carefully limits the specific code frameworks and constructs it expects students to know based on the material it covers. There is no feasible way to limit an AI assistant to a fixed set of constructs or frameworks, using current designs. There are alternate designs where this would be possible (like AI search through adaptation from a controlled library of snippets) but those would be entirely different tools.
So what happens on a sizeable class project where the AI has dropped in buggy code, especially if it uses code constructs the students don't understand? Best case, they understand that they don't understand and re-prompt, or ask for help from an instructor or TA quickly who helps them get rid of the stuff they don't understand and re-prompt or manually add stuff they do. Average case: they waste several hours and/or sweep the bugs partly under the rug, resulting in a project with significant defects. Students in their second and even third years of a CS major still have a lot to learn about debugging, and usually have significant gaps in their knowledge of even their most comfortable programming language. I do think regardless of AI we as teachers need to get better at teaching debugging skills, but the knowledge gaps are inevitable because there's just too much to know. In Python, for example, the LLM is going to spit out yields, async functions, try/finally, maybe even something like a while/else, or with recent training data, the walrus operator. I can't expect even a fraction of 3rd year students who have worked with Python since their first year to know about all these things, and based on how students approach projects where they have studied all the relevant constructs but have forgotten some, I'm not optimistic seeing these things will magically become learning opportunities. Student projects are better off working with a limited subset of full programming languages that the students have actually learned, and using AI coding assistants as currently designed makes this impossible. Beyond that, even when the "assistant" just introduces bugs using syntax the students understand, even through their 4th year many students struggle to understand the operation of moderately complex code they've written themselves, let alone written by someone else. Having access to an AI that will confidently offer incorrect explanations for bugs will make this worse.
To be sure a small minority of students will be able to overcome these problems, but that minority is the group that has a good grasp of the fundamentals and has broadened their knowledge through self-study, which earlier AI-reliant classes would make less likely to happen. In any case, I care about the average student, since we already have plenty of stuff about our institutions that makes life easier for a favored few while being worse for the average student (note that our construction of that favored few as the "good" students is a large part of this problem).
To summarize: because AI assistants introduce excess code complexity and difficult-to-debug bugs, they'll slow down rather than speed up project progress for the average student on moderately complex projects. On a fixed deadline, they'll result in worse projects, or necessitate less ambitious project scoping to ensure adequate completion, and I expect this remains broadly true through 4-6 years of study in most programs (don't take this as an endorsement of AI "assistants" for masters students; we've ignored a lot of other problems along the way).
There's a related problem: solving open-ended project assignments well ultimately depends on deeply understanding the problem, and AI "assistants" allow students to put a lot of code in their file without spending much time thinking about the problem or building an understanding of it. This is awful for learning outcomes, but also bad for project success. Getting students to see the value of thinking deeply about a problem is a thorny pedagogical puzzle at the best of times, and allowing the use of AI "assistants" makes the problem much much worse. This is another area I hope to see (or even drive) pedagogical improvement in, for what it's worth.
1/2

Fact2Fiction: Targeted Poisoning Attack to Agentic Fact-checking System
Haorui He, Yupeng Li, Bin Benjamin Zhu, Dacheng Wen, Reynold Cheng, Francis C. M. Lau
https://arxiv.org/abs/2508.06059

Fact2Fiction: Targeted Poisoning Attack to Agentic Fact-checking System
State-of-the-art fact-checking systems combat misinformation at scale by employing autonomous LLM-based agents to decompose complex claims into smaller sub-claims, verify each sub-claim individually, and aggregate the partial results to produce verdicts with justifications (explanatory rationales for the verdicts). The security of these systems is crucial, as compromised fact-checkers, which tend to be easily underexplored, can amplify misinformation. This work introduces Fact2Fiction, the firs…

Have you ever looked at clouds or water and tried to understand the complex system of swirls and ribbons?
To take it a step further: Jupiter, the largest planet in our solar system, and its moons still pose puzzles of this kind, which we hope to unravel with the instruments aboard the JUICE spacecraft on its journey there.
Here's a hands-on experiment that explains how the gas giant's cloud swirls are formed.
@…

Life as a backup NFL QB is a mental and emotional whirlwind https://www.nytimes.com/athletic/6602281/2025/09/11/nfl-backup-qb-inside-mentorship-jimmy-garoppolo/

Absolute Parameters of Young Stars: NO Puppis
Ahmet Erdem, Volkan Bak{\i}\c{s}, John Southworth, Michael D. Rhodes, Filiz Kahraman Ali\c{c}avu\c{s}, Edwin Budding, Mark Blackford, Timothy Banks, Murray Alexander
https://arxiv.org/abs/2508.05893

Absolute Parameters of Young Stars: NO Puppis
The southern early-type, young, eccentric-orbit eclipsing binary NO Puppis forms the A component of the multiple star Gaia DR3 552\-8147999779517568. The B component is an astrometric binary now at a separation of about 8.1 arcsec. There may be other fainter stars in this interesting but complex stellar system. We have combined several lines of evidence, including TESS data from 4 sectors, new ground-based BVR photometry, HARPS (ESO) and HERCULES (UCMJO) high-resolution spectra and astrometry o…

Matisse: Visualizing Measured Internet Latencies as Manifolds
Stephen Jasina, Loqman Salamatian, Joshua Mathews, Scott Anderson, Paul Barford, Mark Crovella, Walter Willinger
https://arxiv.org/abs/2509.08097

Matisse: Visualizing Measured Internet Latencies as Manifolds
Manifolds are complex topological spaces that can be used to represent datasets of real-world measurements. Visualizing such manifolds can help with illustrating their topological characteristics (e.g., curvature) and providing insights into important properties of the underlying data (e.g., anomalies in the measurements). In this paper, we describe a new methodology and system for generating and visualizing manifolds that are inferred from actual Internet latency measurements between different…

GlyphWeaver: Unlocking Glyph Design Creativity with Uniform Glyph DSL and AI
Can Liu, Shiwei Chen, Zhibang Jiang, Yong Wang
https://arxiv.org/abs/2509.08444 https://

GlyphWeaver: Unlocking Glyph Design Creativity with Uniform Glyph DSL and AI
Expressive glyph visualizations provide a powerful and versatile means to represent complex multivariate data through compact visual encodings, but creating custom glyphs remains challenging due to the gap between design creativity and technical implementation. We present GlyphWeaver, a novel interactive system to enable an easy creation of expressive glyph visualizations. Our system comprises three key components: a glyph domain-specific language (GDSL), a GDSL operation management mechanism, …

Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis
Aina Ferr\`a Marc\'us, Robert Jankowski, Meritxell Vila Mi\~nana, Carles Casacuberta, M. \'Angeles Serrano
https://arxiv.org/abs/2509.08350

Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis
Many complex networks, ranging from social to biological systems, exhibit structural patterns consistent with an underlying hyperbolic geometry. Revealing the dimensionality of this latent space can disentangle the structural complexity of communities, impact efficient network navigation, and fundamentally shape connectivity and system behavior. We introduce a novel topological data analysis weighting scheme for graphs, based on chordless cycles, aimed at estimating the dimensionality of networ…

Voltage Support Procurement in Transmission Grids: Incentive Design via Online Bilevel Games
Zhisen Jiang, Saverio Bolognani, Giuseppe Belgioioso
https://arxiv.org/abs/2508.05378

Voltage Support Procurement in Transmission Grids: Incentive Design via Online Bilevel Games
The integration of distributed energy resources into transmission grid operations presents a complex challenge, particularly in the context of reactive power procurement for voltage support. This paper addresses this challenge by formulating the voltage regulation problem as a Stackelberg game, where the Transmission System Operator (TSO) designs incentives to guide the reactive power responses of Distribution System Operators (DSOs). We utilize a gradient-based iterative algorithm that updates…

How Complex is a Complex Network? Insights from Linear Systems Theory
Giacomo Baggio, Marco Fabris
https://arxiv.org/abs/2507.06389 https://

How Complex is a Complex Network? Insights from Linear Systems Theory
This paper leverages linear systems theory to propose a principled measure of complexity for network systems. We focus on a network of first-order scalar linear systems interconnected through a directed graph. By locally filtering out the effect of nodal dynamics in the interconnected system, we propose a new quantitative index of network complexity rooted in the notion of McMillan degree of a linear system. First, we show that network systems with the same interconnection structure share the s…

Recomposer: Event-roll-guided generative audio editing
Daniel P. W. Ellis, Eduardo Fonseca, Ron J. Weiss, Kevin Wilson, Scott Wisdom, Hakan Erdogan, John R. Hershey, Aren Jansen, R. Channing Moore, Manoj Plakal
https://arxiv.org/abs/2509.05256

Recomposer: Event-roll-guided generative audio editing
Editing complex real-world sound scenes is difficult because individual sound sources overlap in time. Generative models can fill-in missing or corrupted details based on their strong prior understanding of the data domain. We present a system for editing individual sound events within complex scenes able to delete, insert, and enhance individual sound events based on textual edit descriptions (e.g., ``enhance Door'') and a graphical representation of the event timing derived from an ``event ro…

Mint Deluxe – Occident Accident
#byncnd

Data-driven Kinematic Modeling in Soft Robots: System Identification and Uncertainty Quantification
Zhanhong Jiang, Dylan Shah, Hsin-Jung Yang, Soumik Sarkar
https://arxiv.org/abs/2507.07370

Data-driven Kinematic Modeling in Soft Robots: System Identification and Uncertainty Quantification
Precise kinematic modeling is critical in calibration and controller design for soft robots, yet remains a challenging issue due to their highly nonlinear and complex behaviors. To tackle the issue, numerous data-driven machine learning approaches have been proposed for modeling nonlinear dynamics. However, these models suffer from prediction uncertainty that can negatively affect modeling accuracy, and uncertainty quantification for kinematic modeling in soft robots is underexplored. In this w…

Equivariant stability of vortices in Manton's Chern-Simons-Schr\"odinger system on the hyperbolic plane
Oussama Landoulsi, Sohrab Shahshahani
https://arxiv.org/abs/2509.06090

Equivariant stability of vortices in Manton's Chern-Simons-Schrödinger system on the hyperbolic plane
In this work we study magnetic vortices on the hyperbolic plane for a Chern-Simons-Schrödinger system introduced by Manton. The model can be thought of as the Schrödinger analogue of the Abalian-Higgs model. It consists of a system of partial differential equations, where the complex Higgs field $Φ$ evolves according to a nonlinear Schrödinger equation coupled to an electromagnetic field $A$. We restrict attention to the self-dual (Bogomolny) case under equivariance symmetry. For each $m\ge…

High-Resolution Optical IFU Spectroscopy of the Complex Galaxy Merger II Zw 096
C. Riesco (PUC), E. Treister (UTA), G. Venturi (SNS), F. Bauer (UTA), G. Privon (NRAO), C. Finlez (PUC), S. Zamora (SNS), D. Tubin (AIP), Y. Song (ESO), I. del Moral-Castro (PUC), C. Ricci (UDP), C. Ramos (IAC), N. Levenson (STScl), V. U (UCI), A. Medling (UToledo), S. Aalto (SEE), G. D'Ago (IoA), V. Olivares (USACH), L. Barcos-Mu\~noz (NRAO), F. Ricci (UNIROMA3), G. Olander (SEE), F. Muller-Sanchez (Uo…

High-Resolution Optical IFU Spectroscopy of the Complex Galaxy Merger II Zw 096
Luminous and Ultra-luminous IR galaxies ((U)LIRGs) are critical for investigating feedback mechanisms due to a combination of intense star formation (SF) episodes and active galactic nuclei (AGN), particularly in the context of complex galaxy interactions. We conduct a detailed analysis of the II ZW 096 merging system using the Multi-Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope (VLT), combining high-resolution Narrow Field Mode (NFM) and large-area Wide Field Mode (WFM) observ…

Efficient Training of Large-Scale AI Models Through Federated Mixture-of-Experts: A System-Level Approach
Xiaobing Chen, Boyang Zhang, Xiangwei Zhou, Mingxuan Sun, Shuai Zhang, Songyang Zhang, Geoffrey Ye Li
https://arxiv.org/abs/2507.05685

Efficient Training of Large-Scale AI Models Through Federated Mixture-of-Experts: A System-Level Approach
The integration of Federated Learning (FL) and Mixture-of-Experts (MoE) presents a compelling pathway for training more powerful, large-scale artificial intelligence models (LAMs) on decentralized data while preserving privacy. However, efficient federated training of these complex MoE-structured LAMs is hindered by significant system-level challenges, particularly in managing the interplay between heterogeneous client resources and the sophisticated coordination required for numerous specializ…

Dynamics of binding three independent ligands to a single scaffold
Eduardo D. Sontag
https://arxiv.org/abs/2508.06599 https://arxiv.org/pdf/2508.06599

Dynamics of binding three independent ligands to a single scaffold
This note considers a system in which three ligands can independently bind to a scaffold. Such systems arise in diverse applications, including immunotherapy and synthetic biology. It is shown that there are unique steady states in each conservation class, and these are asymptotically stable. The dependency of the steady-state amount of fully bound complex, as a function of total scaffold, is analyzed as well.

h-hi every1!!! im just a lil military-industrial complex in a big world uwu 😊 there any leaders here who, yknow, wanna use me..... for nukes? 👉👈

LUIVITON: Learned Universal Interoperable VIrtual Try-ON
Cong Cao, Xianhang Cheng, Jingyuan Liu, Yujian Zheng, Zhenhui Lin, Meriem Chkir, Hao Li
https://arxiv.org/abs/2509.05030

LUIVITON: Learned Universal Interoperable VIrtual Try-ON
We present LUIVITON, an end-to-end system for fully automated virtual try-on, capable of draping complex, multi-layer clothing onto diverse and arbitrarily posed humanoid characters. To address the challenge of aligning complex garments with arbitrary and highly diverse body shapes, we use SMPL as a proxy representation and separate the clothing-to-body draping problem into two correspondence tasks: 1) clothing-to-SMPL and 2) body-to-SMPL correspondence, where each has its unique challenges. Wh…

TNO colours provide new evidence for a past close flyby of another star to the Solar System
Susanne Pfalzner, Frank W. Wagner, Paul Gibbon
https://arxiv.org/abs/2507.06693

TNO colours provide new evidence for a past close flyby of another star to the Solar System
Thousands of small bodies, known as trans-Neptunian objects (TNOs), orbit the Sun beyond Neptune. TNOs are remnants of the planets' formation from a disc of gas and dust, so it is puzzling that they move mostly on eccentric orbits inclined to the planetary plane and show a complex red-to-grey colour distribution. A close stellar flyby can account for the TNOs' dynamics, but it is unclear if this can also explain the correlation between their colours and orbital characteristics. Assuming an init…

Discretizing linearized Einstein-Bianchi system by symmetric and traceless tensors
Yuyang Guo, Jun Hu, Ting Lin
https://arxiv.org/abs/2508.04560 https://ar…

Discretizing linearized Einstein-Bianchi system by symmetric and traceless tensors
The Einstein-Bianchi system uses symmetric and traceless tensors to reformulate Einstein's original field equations. However, preserving these algebraic constraints simultaneously remains a challenge for numerical methods. This paper proposes a new formulation that treats the linearized Einstein-Bianchi system (near the trivial Minkowski metric) as the Hodge wave equation associated with the conformal Hessian complex. To discretize this equation, a conforming finite element conformal Hessian co…

🎯 Why Developers Are Going Crazy For It
1. True Agentic Intelligence 🤝
Unlike traditional chatbots, Kimi K2 can: • Plan and execute multi-step tasks autonomously • Use tools and APIs intelligently • Handle complex workflows without human intervention • Adapt strategies based on real-time feedback

Improving AEBS Validation Through Objective Intervention Classification Leveraging the Prediction Divergence Principle
Daniel Betschinske, Steven Peters
https://arxiv.org/abs/2507.07872

Improving AEBS Validation Through Objective Intervention Classification Leveraging the Prediction Divergence Principle
The safety validation of automatic emergency braking system (AEBS) requires accurately distinguishing between false positive (FP) and true positive (TP) system activations. While simulations allow straightforward differentiation by comparing scenarios with and without interventions, analyzing activations from open-loop resimulations - such as those from field operational testing (FOT) - is more complex. This complexity arises from scenario parameter uncertainty and the influence of driver inter…

Signals in the Noise: Decoding Unexpected Engagement Patterns on Twitter
Yulin Yu, Houming Chen, Daniel Romero, Paramveer S. Dhillon
https://arxiv.org/abs/2509.08128 https://

Signals in the Noise: Decoding Unexpected Engagement Patterns on Twitter
Social media platforms offer users multiple ways to engage with content--likes, retweets, and comments--creating a complex signaling system within the attention economy. While previous research has examined factors driving overall engagement, less is known about why certain tweets receive unexpectedly high levels of one type of engagement relative to others. Drawing on Signaling Theory and Attention Economy Theory, we investigate these unexpected engagement patterns on Twitter (now known as "X"…

VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Mohammed Almutairi, Charles Chiang, Haoze Guo, Matthew Belcher, Nandini Banerjee, Maria Milkowski, Svitlana Volkova, Daniel Nguyen, Tim Weninger, Michael Yankoski, Trenton W. Ford, Diego Gomez-Zara
https://arxiv.org/abs/2508.04634

VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Simulating how team members collaborate within complex environments using Agentic AI is a promising approach to explore hypotheses grounded in social science theories and study team behaviors. We introduce VirtLab, a user-friendly, customizable, multi-agent, and scalable team simulation system that enables testing teams with LLM-based agents in spatial and temporal settings. This system addresses the current frameworks' design and technical limitations that do not consider flexible simulation s…

Thermalization with partial information
Philippe Faist, Sumeet Khatri
https://arxiv.org/abs/2508.03993 https://arxiv.org/pdf/2508.03993

Thermalization with partial information
A many-body system, whether in contact with a large environment or evolving under complex dynamics, can typically be modeled as occupying the thermal state singled out by Jaynes' maximum entropy principle. Here, we find analogous fundamental principles identifying a noisy quantum channel $\mathcal{T}$ to model the system's dynamics, going beyond the study of its final equilibrium state. Our maximum channel entropy principle states that $\mathcal{T}$ should maximize the channel's entropy, suitab…

Pacing Types: Safe Monitoring of Asynchronous Streams
Florian Kohn, Arthur Correnson, Jan Baumeister, Bernd Finkbeiner
https://arxiv.org/abs/2509.06724 https://

Pacing Types: Safe Monitoring of Asynchronous Streams
Stream-based monitoring is a real-time safety assurance mechanism for complex cyber-physical systems such as unmanned aerial vehicles. In this context, a monitor aggregates streams of input data from sensors and other sources to give real-time statistics and assessments of the system's health. Since monitors are safety-critical components, it is crucial to ensure that they are free of potential runtime errors. One of the central challenges in designing reliable stream-based monitors is to deal …

Exploit Tool Invocation Prompt for Tool Behavior Hijacking in LLM-Based Agentic System
Yu Liu, Yuchong Xie, Mingyu Luo, Zesen Liu, Zhixiang Zhang, Kaikai Zhang, Zongjie Li, Ping Chen, Shuai Wang, Dongdong She
https://arxiv.org/abs/2509.05755

Exploit Tool Invocation Prompt for Tool Behavior Hijacking in LLM-Based Agentic System
LLM-based agentic systems leverage large language models to handle user queries, make decisions, and execute external tools for complex tasks across domains like chatbots, customer service, and software engineering. A critical component of these systems is the Tool Invocation Prompt (TIP), which defines tool interaction protocols and guides LLMs to ensure the security and correctness of tool usage. Despite its importance, TIP security has been largely overlooked. This work investigates TIP-rela…

Comparative Model Fidelity Evaluation to Support Design Decisions for Complex, Novel Systems of Systems
Edward Louis, Gregory Mocko, Evan Taylor
https://arxiv.org/abs/2508.02456

Comparative Model Fidelity Evaluation to Support Design Decisions for Complex, Novel Systems of Systems
Systems design processes are increasingly reliant on simulation models to inform design decisions. A pervasive issue within the systems engineering community is trusting in the models used to make decisions about complex systems. This work presents a method of evaluating the trustworthiness of a model to provide utility to a designer making a decision within a design process. Trusting the results of a model is especially important in design processes where the system is complex, novel, or displ…

Recursive Hierarchical Networks and the Law of Functional Evolution: A Universal Framework for Complex Systems
Hui Li, Yanxin Li
https://arxiv.org/abs/2509.05567 https://…

Recursive Hierarchical Networks and the Law of Functional Evolution: A Universal Framework for Complex Systems
Understanding and predicting the evolution of across complex systems remains a fundamental challenge due to the absence of unified and computationally testable frameworks. Here we propose the Recursive Hierarchical Network(RHN), conceptualizing evolution as recursive encapsulation along a trajectory of node $\to$ module $\to$ system $\to$ new node, governed by gradual accumulation and abrupt transition. Theoretically, we formalize and prove the law of functional evolution, revealing an irrevers…

On the complex moment problem as a dynamic inverse problem for a discrete system
A. S. Mikhaylov, V. S. Mikhaylov
https://arxiv.org/abs/2509.02443 https://…

On the complex moment problem as a dynamic inverse problem for a discrete system
We consider the complex moment problem, that is the problem of constructing a positive Borel measure on $\mathbb{C}$ from a given set of moments. We relate this problem to the dynamic inverse problem for the discrete system associated with the complex Jacobi matrix. We show how the characterization of dynamic inverse data in solving the inverse problem provides sufficient conditions for solving the complex moment problem.

NFL Will Get a Stake in ESPN in a Complex Deal https://www.nytimes.com/2025/08/05/business/media/nfl-espn-disney-deal.html

Millisecond-Response Tracking and Gazing System for UAVs: A Domestic Solution Based on "Phytium Cambricon"
Yuchen Zhu, Longxiang Yin, Kai Zhao
https://arxiv.org/abs/2509.04043

Millisecond-Response Tracking and Gazing System for UAVs: A Domestic Solution Based on "Phytium + Cambricon"
In the frontier research and application of current video surveillance technology, traditional camera systems exhibit significant limitations of response delay exceeding 200 ms in dynamic scenarios due to the insufficient deep feature extraction capability of automatic recognition algorithms and the efficiency bottleneck of computing architectures, failing to meet the real-time requirements in complex scenes. To address this issue, this study proposes a heterogeneous computing architecture base…

LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving
Yuhang Zhang, Jiaqi Liu, Chengkai Xu, Peng Hang, Jian Sun
https://arxiv.org/abs/2507.05754

LeAD: The LLM Enhanced Planning System Converged with End-to-end Autonomous Driving
A principal barrier to large-scale deployment of urban autonomous driving systems lies in the prevalence of complex scenarios and edge cases. Existing systems fail to effectively interpret semantic information within traffic contexts and discern intentions of other participants, consequently generating decisions misaligned with skilled drivers' reasoning patterns. We present LeAD, a dual-rate autonomous driving architecture integrating imitation learning-based end-to-end (E2E) frameworks with l…

Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding
Jiarui Li, Zixiang Yin, Haley Smith, Zhengming Ding, Samuel J. Landry, Ramgopal R. Mettu
https://arxiv.org/abs/2507.03197

Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding
CD8+ "killer" T cells and CD4+ "helper" T cells play a central role in the adaptive immune system by recognizing antigens presented by Major Histocompatibility Complex (pMHC) molecules via T Cell Receptors (TCRs). Modeling binding between T cells and the pMHC complex is fundamental to understanding basic mechanisms of human immune response as well as in developing therapies. While transformer-based models such as TULIP have achieved impressive performance in this domain, their black-box nature …

PenTest2.0: Towards Autonomous Privilege Escalation Using GenAI
Haitham S. Al-Sinani, Chris J. Mitchell
https://arxiv.org/abs/2507.06742 https://

PenTest2.0: Towards Autonomous Privilege Escalation Using GenAI
Ethical hacking today relies on highly skilled practitioners executing complex sequences of commands, which is inherently time-consuming, difficult to scale, and prone to human error. To help mitigate these limitations, we previously introduced 'PenTest++', an AI-augmented system combining automation with generative AI supporting ethical hacking workflows. However, a key limitation of PenTest++ was its lack of support for privilege escalation, a crucial element of ethical hacking. In this paper…

AP-observation Automata for Abstraction-based Verification of Continuous-time Systems (Extended Version)
Sasinee Pruekprasert, Clovis Eberhart
https://arxiv.org/abs/2509.08343 h…

AP-observation Automata for Abstraction-based Verification of Continuous-time Systems (Extended Version)
A key challenge in abstraction-based verification and control under complex specifications such as Linear Temporal Logic (LTL) is that abstract models retain significantly less information than their original systems. This issue is especially true for continuous-time systems, where the system state trajectories are split into intervals of discrete actions, and satisfaction of atomic propositions is abstracted to a whole time interval. To tackle this challenge, this work introduces a novel trans…

GoldMind: A Teacher-Centered Knowledge Management System for Higher Education -- Lessons from Iterative Design
Gloria Fern\'andez-Nieto, Lele Sha, Yuheng Li, Yi-Shan Tsai, Guanliang Chen, Yinwei Wei, Weiqing Wang, Jinchun Wen, Shaveen Singh, Ivan Silva, Yuanfang Li, Dragan Gas\v{e}vi\'c, Zachari Swiecki
https://arxiv.org/abs/2508.0…

GoldMind: A Teacher-Centered Knowledge Management System for Higher Education -- Lessons from Iterative Design
Designing Knowledge Management Systems (KMSs) for higher education requires addressing complex human-technology interactions, especially where staff turnover and changing roles create ongoing challenges for reusing knowledge. While advances in process mining and Generative AI enable new ways of designing features to support knowledge management, existing KMSs often overlook the realities of educators' workflows, leading to low adoption and limited impact. This paper presents findings from a two…

🎯 #StateMachine Pattern in #PHP: Transform Complex Workflows Into Clean, Predictable Code
⚡ Replace tangled if/else statements with explicit states, events & transition rules for order processing, article workflows & business logic
🔒 Built-in safety: Forbidden transitions (…

TemporalFlowViz: Parameter-Aware Visual Analytics for Interpreting Scramjet Combustion Evolution
Yifei Jia, Shiyu Cheng, Yu Dong, Guan Li, Dong Tian, Ruixiao Peng, Xuyi Lu, Yu Wang, Wei Yao, Guihua Shan
https://arxiv.org/abs/2509.04834

TemporalFlowViz: Parameter-Aware Visual Analytics for Interpreting Scramjet Combustion Evolution
Understanding the complex combustion dynamics within scramjet engines is critical for advancing high-speed propulsion technologies. However, the large scale and high dimensionality of simulation-generated temporal flow field data present significant challenges for visual interpretation, feature differentiation, and cross-case comparison. In this paper, we present TemporalFlowViz, a parameter-aware visual analytics workflow and system designed to support expert-driven clustering, visualization, …

Feedback Linearisation with State Constraints
Songlin Jin, Yuanbo Nie, Morgan Jones
https://arxiv.org/abs/2509.05191 https://arxiv.org/pdf/2509.05191

Feedback Linearisation with State Constraints
Feedback Linearisation (FBL) is a widely used technique that applies feedback laws to transform input-affine nonlinear dynamical systems into linear dynamical systems, allowing for the use of linear controller design methods such as pole placement. However, for problems with state constraints, controlling the linear system induced by FBL can be more challenging than controlling the original system. This is because simple state constraints in the original nonlinear system become complex nonlinea…

TransMPC: Transformer-based Explicit MPC with Variable Prediction Horizon
Sichao Wu, Jiang Wu, Xingyu Cao, Fawang Zhang, Guangyuan Yu, Junjie Zhao, Yue Qu, Fei Ma, Jingliang Duan
https://arxiv.org/abs/2509.07381

TransMPC: Transformer-based Explicit MPC with Variable Prediction Horizon
Traditional online Model Predictive Control (MPC) methods often suffer from excessive computational complexity, limiting their practical deployment. Explicit MPC mitigates online computational load by pre-computing control policies offline; however, existing explicit MPC methods typically rely on simplified system dynamics and cost functions, restricting their accuracy for complex systems. This paper proposes TransMPC, a novel Transformer-based explicit MPC algorithm capable of generating highl…

Human-Hardware-in-the-Loop simulations for systemic resilience assessment in cyber-socio-technical systems
Francesco Simone, Marco Bortolini, Giovanni Mazzuto, Giulio di Gravio, Riccardo Patriarca
https://arxiv.org/abs/2509.06657

Human-Hardware-in-the-Loop simulations for systemic resilience assessment in cyber-socio-technical systems
Modern industrial systems require updated approaches to safety management, as the tight interplay between cyber-physical, human, and organizational factors has driven their processes toward increasing complexity. In addition to dealing with known risks, managing system resilience acquires great value to address complex behaviors pragmatically. This manuscript starts from the System-Theoretic Accident Model and Processes (STAMP) as a modelling initiative for such complexity. The STAMP can be nat…