Tootfinder

An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Ziteng Chen (Infrawaves), Xiaohe Hu (Infrawaves), Menghao Zhang (Beihang University), Yanmin Jia (Infrawaves), Yan Zhang (Infrawaves), Mingjun Zhang (Infrawaves), Da Liu (Infrawaves), Fangzheng Jiao (Beihang University), Jun Chen (Infrawaves), He Liu (Infrawaves), Aohan Zeng (Tsinghua University), Shuaixing Duan (Zhipu AI), Ruya Gu (Infrawaves), Yang Jing (Infrawaves), Bowen Han …

An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
Large-scale LLM training requires collective communication libraries to exchange data among distributed GPUs. As a company dedicated to building and operating large-scale GPU training clusters, we encounter several challenges when using NCCL in production, including 1) limited efficiency with costly and cumbersome P2P communication, 2) poor tolerance to frequent RNIC port failures, and 3) insufficient observability of transient collective communication anomalies. To address these issues, we pro…

A Robust Proactive Communication Strategy for Distributed Active Noise Control Systems
Junwei Ji, Dongyuan Shi, Zhengding Luo, Boxiang Wang, Ziyi Yang, Haowen Li, Woon-Seng Gan
https://arxiv.org/abs/2510.00934

A Robust Proactive Communication Strategy for Distributed Active Noise Control Systems
Distributed multichannel active noise control (DMCANC) systems assign the high computational load of conventional centralized algorithms across multiple processing nodes, leveraging inter-node communication to collaboratively suppress unwanted noise. However, communication overhead can undermine algorithmic stability and degrade overall performance. To address this challenge, we propose a robust communication framework that integrates adaptive-fixed-filter switching and the mixed-gradient combi…

OTFS for Joint Radar and Communication: Algorithms, Prototypes, and Experiments
Xiaojuan Zhang, Yonghong Zeng, Francois Chin Po Shin
https://arxiv.org/abs/2510.00668 https://

OTFS for Joint Radar and Communication: Algorithms, Prototypes, and Experiments
We propose an Joint Radar and Communication (JRC) system that utilizes the Orthogonal Time Frequency Space (OTFS) signals. The system features a fast radar sensing algorithm for detecting target range and speed by using the OTFS communication signals, and a self-interference cancellation for enhanced multi-target separation. In addition to target detection, we propose methods for monitoring human vital signs, such as breathing rate and heartbeat. Furthermore, we explore two approaches for disti…

Event-triggered control and communication for single-master multi-slave teleoperation systems with Try-Once-Discard protocol
Yuling Li, Chenxi Li, Kun Liu, Jie Dong, Rolf Johansson
https://arxiv.org/abs/2510.02072

Event-triggered control and communication for single-master multi-slave teleoperation systems with Try-Once-Discard protocol
Single-master multi-slave (SMMS) teleoperation systems can perform multiple tasks remotely in a shorter time, cover large-scale areas, and adapt more easily to single-point failures, thereby effectively encompassing a broader range of applications. As the number of slave manipulators sharing a communication network increases, the limitation of communication bandwidth becomes critical. To alleviate bandwidth usage, the Try-Once-Discard (TOD) scheduling protocol and event-triggered mechanisms are…

Assembling GW231123 in Star Clusters through the Combination of Stellar Binary Evolution and Hierarchical Mergers: #BlackHole mergers: https://www.gssi.it/communication/news-events/item/26044-gssi-astrophysicists-reveal-the-role-of-star-clusters-in-black-hole-mergers

Framing Unionization on Facebook: Communication around Representation Elections in the United States
Arianna Pera, Veronica Jude, Ceren Budak, Luca Maria Aiello
https://arxiv.org/abs/2510.01757

Framing Unionization on Facebook: Communication around Representation Elections in the United States
Digital media have become central to how labor unions communicate, organize, and sustain collective action. Yet little is known about how unions' online discourse relates to concrete outcomes such as representation elections. This study addresses the gap by combining National Labor Relations Board (NLRB) election data with 158k Facebook posts published by U.S. labor unions between 2015 and 2024. We focused on five discourse frames widely recognized in labor and social movement communication res…

SmartFLow: A Communication-Efficient SDN Framework for Cross-Silo Federated Learning
Osama Abu Hamdan, Hao Che, Engin Arslan, Md Arifuzzaman
https://arxiv.org/abs/2509.00603 htt…

SmartFLow: A Communication-Efficient SDN Framework for Cross-Silo Federated Learning
Cross-silo Federated Learning (FL) enables multiple institutions to collaboratively train machine learning models while preserving data privacy. In such settings, clients repeatedly exchange model weights with a central server, making the overall training time highly sensitive to network performance. However, conventional routing methods often fail to prevent congestion, leading to increased communication latency and prolonged training. Software-Defined Networking (SDN), which provides centrali…

Stealing AI Model Weights Through Covert Communication Channels
Valentin Barbaza, Alan Rodrigo Diaz-Rizo, Hassan Aboushady, Spyridon Raptis, Haralampos-G. Stratigopoulos
https://arxiv.org/abs/2510.00151

Stealing AI Model Weights Through Covert Communication Channels
AI models are often regarded as valuable intellectual property due to the high cost of their development, the competitive advantage they provide, and the proprietary techniques involved in their creation. As a result, AI model stealing attacks pose a serious concern for AI model providers. In this work, we present a novel attack targeting wireless devices equipped with AI hardware accelerators. The attack unfolds in two phases. In the first phase, the victim's device is compromised with a hardw…

KTBox: A Modular LaTeX Framework for Semantic Color, Structured Highlighting, and Scholarly Communication
Bhaskar Mangal, Ashutosh Bhatia, Yashvardhan Sharma, Kamlesh Tiwari, Rashmi Verma
https://arxiv.org/abs/2510.01961

KTBox: A Modular LaTeX Framework for Semantic Color, Structured Highlighting, and Scholarly Communication
The communication of technical insight in scientific manuscripts often relies on ad-hoc formatting choices, resulting in inconsistent visual emphasis and limited portability across document classes. This paper introduces ktbox, a modular LaTeX framework that unifies semantic color palettes, structured highlight boxes, taxonomy trees, and author metadata utilities into a coherent system for scholarly writing. The framework is distributed as a set of lightweight, namespaced components: ktcolor.st…

TASP: Topology-aware Sequence Parallelism
Yida Wang (Capital Normal University, Infinigence-AI), Ke Hong (Tsinghua University, Infinigence-AI), Xiuhong Li (Infinigence-AI), Yuanchao Xu (Capital Normal University), Wenxun Wang (Tsinghua University), Guohao Dai (Infinigence-AI, Shanghai Jiao Tong University), Yu Wang (Tsinghua University)
https://

TASP: Topology-aware Sequence Parallelism
Long-context large language models (LLMs) face constraints due to the quadratic complexity of the self-attention mechanism. The mainstream sequence parallelism (SP) method, Ring Attention, attempts to solve this by distributing the query into multiple query chunks across accelerators and enable each Q tensor to access all KV tensors from other accelerators via the Ring AllGather communication primitive. However, it exhibits low communication efficiency, restricting its practical applicability. …

Multi-Agent Data Visualization and Narrative Generation
Anton Wolter, Georgios Vidalakis, Michael Yu, Ankit Grover, Vaishali Dhanoa
https://arxiv.org/abs/2509.00481 https://

Multi-Agent Data Visualization and Narrative Generation
Recent advancements in the field of AI agents have impacted the way we work, enabling greater automation and collaboration between humans and agents. In the data visualization field, multi-agent systems can be useful for employing agents throughout the entire data-to-communication pipeline. We present a lightweight multi-agent system that automates the data analysis workflow, from data exploration to generating coherent visual narratives for insight communication. Our approach combines a hybrid…

Computing on Dirty Paper: Interference-Free Integrated Communication and Computing
Kuranage Roche Rayan Ranasinghe, Giuseppe Thadeu Freitas de Abreu, David Gonz\'alez G., Carlo Fischione
https://arxiv.org/abs/2510.02012

Computing on Dirty Paper: Interference-Free Integrated Communication and Computing
Inspired by Costa's pioneering work on dirty paper coding (DPC), this paper proposes a novel scheme for integrated communication and computing (ICC), named Computing on Dirty Paper, whereby the transmission of discrete data symbols for communication, and over-the-air computation (AirComp) of nomographic functions can be achieved simultaneously over common multiple-access channels. In particular, the proposed scheme allows for the integration of communication and computation in a manner that is …

PhotonIDs: ML-Powered Photon Identification System for Dark Count Elimination
Karl C. Linne (Kai Li), Sho Uemura, Yue Ji, Andrew Karmen, Allen Zang, Alex Kolar, Ian Chin, Martin Di Federico, Gustavo Cancelo, Orlando Quaranta, Debashri Roy, Tian Zhong
https://arxiv.org/abs/2509.26315

PhotonIDs: ML-Powered Photon Identification System for Dark Count Elimination
Reliable single photon detection is the foundation for practical quantum communication and networking. However, today's superconducting nanowire single photon detector(SNSPD) inherently fails to distinguish between genuine photon events and dark counts, leading to degraded fidelity in long-distance quantum communication. In this work, we introduce PhotonIDs, a machine learning-powered photon identification system that is the first end-to-end solution for real-time discrimination between photons…

Heartbroken, like countless across the world, to have woken up to the news of the passing of Jane Goodall. Her fierce passion and audacious hope in connection and communication across boundaries - human, animal, and otherwise - as the lifeforce is a lesson for us all.
I had the privilege of hearing her speak. Filled with incredible wit and compassion, she began her address with the call of a chimpanzee and by thanking her mother. 🤍
In humility and hope.

Lattica: A Decentralized Cross-NAT Communication Framework for Scalable AI Inference and Training
Ween Yang, Jason Liu, Suli Wang, Xinyuan Song, Lynn Ai, Eric Yang, Tianyu Shi
https://arxiv.org/abs/2510.00183

Lattica: A Decentralized Cross-NAT Communication Framework for Scalable AI Inference and Training
The rapid expansion of distributed Artificial Intelligence (AI) workloads beyond centralized data centers creates a demand for new communication substrates. These substrates must operate reliably in heterogeneous and permissionless environments, where Network Address Translators (NATs) and firewalls impose significant constraints. Existing solutions, however, are either designed for controlled data center deployments or implemented as monolithic systems that tightly couple machine learning logi…

Efficient Geometry Compression and Communication for 3D Gaussian Splatting Point Clouds
Liang Xie, Yanting Li, Luyang Tang, Wei Gao
https://arxiv.org/abs/2509.02232 https://

Efficient Geometry Compression and Communication for 3D Gaussian Splatting Point Clouds
Storage and transmission challenges in dynamic 3D scene representation based on the i3DV platform, With increasing scene complexity, the explosive growth of 3D Gaussian data volume causes excessive storage space occupancy. To address this issue, we propose adopting the AVS PCRM reference software for efficient compression of Gaussian point cloud geometry data. The strategy deeply integrates the advanced encoding capabilities of AVS PCRM into the i3DV platform, forming technical complementarity …

Movable Antenna-Enhanced Secure Communication: Opportunities, Challenges, and Solutions
Yaodong Ma, Kai Liu, Lipeng Zhu, Yanming Liu, Yanbo Zhu, Daniel Benevides da Costa
https://arxiv.org/abs/2509.00894

Movable Antenna-Enhanced Secure Communication: Opportunities, Challenges, and Solutions
The broadcast nature of wireless communication renders it inherently vulnerable to security threats such as jamming and eavesdropping. While traditional array beamforming techniques help to mitigate these threats, they usually incur high hardware and processing costs, particularly in large-scale arrays with fixed-position antennas (FPAs). In contrast, movable antenna (MA) arrays can fully exploit the channel variation in spatial regions by enabling flexible antenna movement, which has emerged a…

NeuroBridge: Using Generative AI to Bridge Cross-neurotype Communication Differences through Neurotypical Perspective-taking
Rukhshan Haroon, Kyle Wigdor, Katie Yang, Nicole Toumanios, Eileen T. Crehan, Fahad Dogar
https://arxiv.org/abs/2509.23434

NeuroBridge: Using Generative AI to Bridge Cross-neurotype Communication Differences through Neurotypical Perspective-taking
Communication challenges between autistic and neurotypical individuals stem from a mutual lack of understanding of each other's distinct, and often contrasting, communication styles. Yet, autistic individuals are expected to adapt to neurotypical norms, making interactions inauthentic and mentally exhausting for them. To help redress this imbalance, we build NeuroBridge, an online platform that utilizes large language models (LLMs) to simulate: (a) an AI character that is direct and literal, a …

Evolutionary Kuramoto dynamics unravels origins of chimera states in neural populations
Thomas Zdyrski, Scott Pauls, Feng Fu
https://arxiv.org/abs/2510.00423 https://

Evolutionary Kuramoto dynamics unravels origins of chimera states in neural populations
Neural synchronization is central to cognition However, incomplete synchronization often produces chimera states where coherent and incoherent dynamics coexist. While previous studies have explored such patterns using networks of coupled oscillators, it remains unclear why neurons commit to communication or how chimera states persist. Here, we investigate the coevolution of neuronal phases and communication strategies on directed, weighted networks, where interaction payoffs depend on phase ali…

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Global Communication:
🎵 Sublime Creation
#GlobalCommunication
https://markpritchard.bandcamp.com/track/sublime-creation-original-mix
https://open.spotify.com/track/4ETjsVcQuKa0gx4CG5muSC

as_skitter: Skitter IP graph (2005)
An aggregate snapshot of the Internet Protocol (IP) graph, as measured by the traceroute tool on CAIDA's skitter infrastructure, in 2005.
This network has 1696415 nodes and 11095298 edges.
Tags: Technological, Communication, Unweighted
https://networks.skewed.de/net/as_s…

Category Theory for Supercomputing: The Tensor Product of Linear BSP Algorithms
Thomas Koopman, Rob H. Bisseling, Sven-Bodo Scholz
https://arxiv.org/abs/2510.00979 https://

Category Theory for Supercomputing: The Tensor Product of Linear BSP Algorithms
We show that a particular class of parallel algorithm for linear functions can be straightforwardly generalized to a parallel algorithm of their tensor product. The central idea is to take a model of parallel algorithms -- Bulk Synchronous Parallel (BSP) -- that decomposes parallel algorithms into so-called supersteps that are one of two types: a computation superstep that only does local computations, or a communication superstep that only communicates between processors. We connect each type …

US in contact with Belarus to 'ensure lines of communication' with Putin, Kellogg says: https://benborges.xyz/2025/09/30/us-in-contact-with-belarus.html

Un avenir commun au sein de la soci\'et\'e num\'erique
Miguel Vanvlasselaer
https://arxiv.org/abs/2509.01014 https://arxiv.org/pdf/2509.01014…

Un avenir commun au sein de la société numérique
Today, data and information have become overabundant resources within a global network of machines that exchange signals at speeds approaching that of light. In this highly saturated environment, communication has emerged as the most central form of interaction, supported by a rapidly evolving technical infrastructure. These new communication tools have created an overwhelming surplus of information so much so that no human could process it all. In response, platforms like Facebook, YouTube, an…

DeMuon: A Decentralized Muon for Matrix Optimization over Graphs
Chuan He, Shuyi Ren, Jingwei Mao, Erik G. Larsson
https://arxiv.org/abs/2510.01377 https://

DeMuon: A Decentralized Muon for Matrix Optimization over Graphs
In this paper, we propose DeMuon, a method for decentralized matrix optimization over a given communication topology. DeMuon incorporates matrix orthogonalization via Newton-Schulz iterations-a technique inherited from its centralized predecessor, Muon-and employs gradient tracking to mitigate heterogeneity among local functions. Under heavy-tailed noise conditions and additional mild assumptions, we establish the iteration complexity of DeMuon for reaching an approximate stochastic stationary …

A Hierarchy for Constant Communication Complexity
Andris Ambainis, Hartmut Klauck, Debbie Lim
https://arxiv.org/abs/2509.22004 https://arxiv.org/pdf/2509.2…

A Hierarchy for Constant Communication Complexity
Similarly to the Chomsky hierarchy, we offer a classification of communication complexity measures such that these measures are organized into equivalence classes. Different from previous attempts of this endeavor, we consider two communication complexity measures as equivalent, if, when one is constant, then the other is constant as well, and vice versa. Most previous considerations of similar topics have been using polylogarithmic input length as a defining characteristic of equivalence. In t…

Radiation Pattern Reconfigurable FAS-Empowered Interference-Resilient UAV Communication
Zhuoran Li, Zhen Gao, Boyu Ning, Zhaocheng Wang
https://arxiv.org/abs/2510.00581 https://…

Radiation Pattern Reconfigurable FAS-Empowered Interference-Resilient UAV Communication
The widespread use of uncrewed aerial vehicles (UAVs) has propelled the development of advanced techniques on countering unauthorized UAV flights. However, the resistance of legal UAVs to illegal interference remains under-addressed. This paper proposes radiation pattern reconfigurable fluid antenna systems (RPR-FAS)-empowered interference-resilient UAV communication scheme. This scheme integrates the reconfigurable pixel antenna technology, which provides each antenna with an adjustable radiat…

Two-Dimensional XOR-Based Secret Sharing for Layered Multipath Communication
Wai Ming Chan, Remi Chou, Taejoon Kim
https://arxiv.org/abs/2509.25113 https://

Two-Dimensional XOR-Based Secret Sharing for Layered Multipath Communication
This paper introduces the first two-dimensional XOR-based secret sharing scheme for layered multipath communication networks. We present a construction that guarantees successful message recovery and perfect privacy when an adversary observes and disrupts any single path at each transmission layer. The scheme achieves information-theoretic security using only bitwise XOR operations with linear $O(|S|)$ complexity, where $|S|$ is the message length. We provide mathematical pr…

Scalable Asynchronous Federated Modeling for Spatial Data
Jianwei Shi, Sameh Abdulah, Ying Sun, Marc G. Genton
https://arxiv.org/abs/2510.01771 https://arx…

Scalable Asynchronous Federated Modeling for Spatial Data
Spatial data are central to applications such as environmental monitoring and urban planning, but are often distributed across devices where privacy and communication constraints limit direct sharing. Federated modeling offers a practical solution that preserves data privacy while enabling global modeling across distributed data sources. For instance, environmental sensor networks are privacy- and bandwidth-constrained, motivating federated spatial modeling that shares only privacy-preserving s…

Semantic disambiguation of scientific assertions in the form of nanopublications* is, thus far, under-utilised in scientific communication.
*nanoplublication: https://nanopub.net/

Pilot design, channel estimation, and target detection for integrated sensing and communication with OTFS
Dazhuo Wang, Yonghong Zeng, Yuhong Wang, Francois Chin, Yugang Ma, Sumei Sun
https://arxiv.org/abs/2509.25846

Pilot design, channel estimation, and target detection for integrated sensing and communication with OTFS
Recent studies shows that the orthogonal time frequency space (OTFS) waveform is a promising candidate for future communication. To meet users' potential demand for Integrated Sensing and Communication (ISAC) applications in 6G, the usage of OTFS for both radar sensing and wireless communication needs to be explored. In this paper, we propose a Fast Algorithm OTFS radar (FAOR) that can perform radar sensing in low complexity to detect the range and speed of the targets. It computes the 2D cycli…

Communication-Efficient and Interoperable Distributed Learning
Mounssif Krouka, Mehdi Bennis
https://arxiv.org/abs/2509.22823 https://arxiv.org/pdf/2509.22…

Communication-Efficient and Interoperable Distributed Learning
Collaborative learning across heterogeneous model architectures presents significant challenges in ensuring interoperability and preserving privacy. We propose a communication-efficient distributed learning framework that supports model heterogeneity and enables modular composition during inference. To facilitate interoperability, all clients adopt a common fusion-layer output dimension, which permits each model to be partitioned into a personalized base block and a generalized modular block. C…

Eye-Tracking and BCI Integration for Assistive Communication in Locked-In Syndrome: Pilot Study with Healthy Participants
Ana Patr\'icia Pinto, Rute Bettencourt, Urbano J. Nunes, Gabriel Pires
https://arxiv.org/abs/2509.23518

Eye-Tracking and BCI Integration for Assistive Communication in Locked-In Syndrome: Pilot Study with Healthy Participants
Patients with Amyotrophic Lateral Sclerosis (ALS) progressively lose voluntary motor control, often leading to a Locked-In State (LIS), or in severe cases, a Completely Locked-in State (CLIS). Eye-tracking (ET) systems are common communication tools in early LIS but become ineffective as oculomotor function declines. EEG-based Brain-Computer Interfaces (BCIs) offer a non-muscular communication alternative, but delayed adoption may reduce performance due to diminished goal-directed thinking. Thi…

Purcell-enhanced single-photon generation from CsPbBr$_3$ quantum dots in in-situ selected Laguerre-Gaussian modes
Virginia Oddi, Darius Urbonas, Etsuki Kobiyama, Ioannis Georgakilas, Ihor Cherniukh, Kseniia Shcherbak, Chenglian Zhu, Maryna I. Bodnarchuk, Maksym V. Kovalenko, Rainer F. Mahrt, Gabriele Rain\`o, Thilo St\"oferle
https://

Purcell-enhanced single-photon generation from CsPbBr$_3$ quantum dots in in-situ selected Laguerre-Gaussian modes
Single photons in Laguerre-Gaussian (LG) beams, which carry orbital angular momentum (OAM), could enable more robust and efficient photonic quantum communication and information processing, as well as enhanced sensitivity in quantum metrology and imaging. However, as most implementations are indirect or require additional mode-shaping elements, direct generation of single photons with OAM has received growing interest. Colloidal lead halide perovskite quantum dots (QDs) have recently emerged as…

Good Morning #Canada
Sunday mornings should include some relaxation, a good cup of coffee, and a tale of one man forging a legacy of independence. Today we present to you the story of American businessman Russell Arundel who, in 1949, claimed sovereignty over approximately 4 acres of Outer Bald Tusket Island, off the southern tip of Nova Scotia. After purchasing the island for $750, Arundel announced the principality of Outer Baldonia with its own charter, a flag, currency, passports, and an organized military that consisted of 69 fishermen (all Admirals). Citizens of the principality who caught a Bluefin tuna and paid a $50 fee were accorded the rank of prince. Government officials included Prince of Princes Russell Arundel, Chancellor Elson Boudreau, and Ambassador Extraordinary and Minister Plenipotentiary Ron Wallace. The Canadian government mostly ignored the farce but an official Russian communication declared Outer Baldonia a fascist state.
#CanadaIsAwesome #History
https://backyardhistory.ca/f/the-nova-scotian-island-that-declared-independence

Coherence restoring in communication line via controlled interaction with environment
E. B. Fel'dman, I. D. Lazarev, A. N. Pechen, A. I. Zenchuk
https://arxiv.org/abs/2509.25861

Coherence restoring in communication line via controlled interaction with environment
We consider the state-restoring protocol based on the controlled interaction of a linear chain with environment through the specially adjusted step-wise time dependent Lindblad operators. We show that the best restoring result (maximal scale factors in the restored state) corresponds to the symmetrical Lindblad equation. (0,1)-excitation dynamics is considered numerically, and restoring protocol for the 1-order coherence matrix is proposed for the case of the two-qubit sender (receiver). The st…

Adaptive Source-Channel Coding for Multi-User Semantic and Data Communications
Kai Yuan, Dongxu Li, Jianhao Huang, Han Zhang, Chuan Huang
https://arxiv.org/abs/2509.24247 https:…

Adaptive Source-Channel Coding for Multi-User Semantic and Data Communications
This paper considers a multi-user semantic and data communication (MU-SemDaCom) system, where a base station (BS) simultaneously serves users with different semantic and data tasks through a downlink multi-user multiple-input single-output (MU-MISO) channel. The coexistence of heterogeneous communication tasks, diverse channel conditions, and the requirements for digital compatibility poses significant challenges to the efficient design of MU-SemDaCom systems. To address these issues, we propos…

Stochastic Self-Organization in Multi-Agent Systems
Nurbek Tastan, Samuel Horvath, Karthik Nandakumar
https://arxiv.org/abs/2510.00685 https://arxiv.org/pd…

Stochastic Self-Organization in Multi-Agent Systems
Multi-agent systems (MAS) based on Large Language Models (LLMs) have the potential to solve tasks that are beyond the reach of any single LLM. However, this potential can only be realized when the collaboration mechanism between agents is optimized. Specifically, optimizing the communication structure between agents is critical for fruitful collaboration. Most existing approaches rely on fixed topologies, pretrained graph generators, optimization over edges, or employ external LLM judges, there…

The Dialogue That Heals: A Comprehensive Evaluation of Doctor Agents' Inquiry Capability
Linlu Gong, Ante Wang, Yunghwei Lai, Weizhi Ma, Yang Liu
https://arxiv.org/abs/2509.24958

The Dialogue That Heals: A Comprehensive Evaluation of Doctor Agents' Inquiry Capability
An effective physician should possess a combination of empathy, expertise, patience, and clear communication when treating a patient. Recent advances have successfully endowed AI doctors with expert diagnostic skills, particularly the ability to actively seek information through inquiry. However, other essential qualities of a good doctor remain overlooked. To bridge this gap, we present MAQuE(Medical Agent Questioning Evaluation), the largest-ever benchmark for the automatic and comprehensive …

Towards Human Engagement with Realistic AI Combat Pilots
Ardian Selmonaj, Giacomo Del Rio, Adrian Schneider, Alessandro Antonucci
https://arxiv.org/abs/2509.26002 https://

Towards Human Engagement with Realistic AI Combat Pilots
We present a system that enables real-time interaction between human users and agents trained to control fighter jets in simulated 3D air combat scenarios. The agents are trained in a dedicated environment using Multi-Agent Reinforcement Learning. A communication link is developed to allow seamless deployment of trained agents into VR-Forces, a widely used defense simulation tool for realistic tactical scenarios. This integration allows mixed simulations where human-controlled entities engage w…

FlowMoE: A Scalable Pipeline Scheduling Framework for Distributed Mixture-of-Experts Training
Yunqi Gao, Bing Hu, Mahdi Boloursaz Mashhadi, A-Long Jin, Yanfeng Zhang, Pei Xiao, Rahim Tafazolli, Merouane Debbah
https://arxiv.org/abs/2510.00207

FlowMoE: A Scalable Pipeline Scheduling Framework for Distributed Mixture-of-Experts Training
The parameter size of modern large language models (LLMs) can be scaled up via the sparsely-activated Mixture-of-Experts (MoE) technique to avoid excessive increase of the computational costs. To further improve training efficiency, pipelining computation and communication has become a promising solution for distributed MoE training. However, existing work primarily focuses on scheduling tasks within the MoE layer, such as expert computing and all-to-all (A2A) communication, while neglecting ot…

Collective is different: Information exchange and speed-accuracy trade-offs in self-organized patterning
Ashutosh Tripathi, J\"orn Dunkel, Dominic J. Skinner
https://arxiv.org/abs/2510.01397

Collective is different: Information exchange and speed-accuracy trade-offs in self-organized patterning
During development, highly ordered structures emerge as cells collectively coordinate with each other. While recent advances have clarified how individual cells process and respond to external signals, understanding collective cellular decision making remains a major challenge. Here, we introduce a minimal, analytically tractable, model of cell patterning via local cell-cell communication. Using this framework, we identify a trade-off between the speed and accuracy of collective pattern formati…

Communication-aware Wide-Area Damping Control using Risk-Constrained Reinforcement Learning
Kyung-bin Kwon, Lintao Ye, Vijay Gupta, Hao Zhu
https://arxiv.org/abs/2509.23620 http…

Communication-aware Wide-Area Damping Control using Risk-Constrained Reinforcement Learning
Non-ideal communication links, especially delays, critically affect fast networked controls in power systems, such as the wide-area damping control (WADC). Traditionally, a delay estimation and compensation approach is adopted to address this cyber-physical coupling, but it demands very high accuracy for the fast WADC and cannot handle other cyber concerns like link failures or {cyber perturbations}. Hence, we propose a new risk-constrained framework that can target the communication delays, ye…

uni_email: Email network (Uni. R-V, Spain, 2003)
A network representing the exchange of emails among members of the Rovira i Virgili University in Spain, in 2003. The KONECT version is undirected.
This network has 1133 nodes and 10903 edges.
Tags: Social, Communication, Unweighted
https://networks.skewed.de/net…

An Adaptive cmWave/FR3 Channel Sounder for Integrated Sensing and Communication
K. F. Nieman, O. Kanhere, R. Shiu, W. Xu, C. Duan, S. S. Ghassemzadeh
https://arxiv.org/abs/2510.00257

An Adaptive cmWave/FR3 Channel Sounder for Integrated Sensing and Communication
In this paper, we present an advanced channel sounding system designed for sensing and propagation experiments in all types of cellular deployment scenarios. The system's exceptional adaptability, high resolution, and sensitivity makes it an invaluable tool for utilization in a variety of indoor and outdoor measurement campaigns. The sounder has a 2.5 ns delay resolution, 170 dB path loss measurement capability and is able to measure a {360\textdegree} power-angular delay profile of the channel…

Bridging Technical Capability and User Accessibility: Off-grid Civilian Emergency Communication
Karim Khamaisi, Oliver Kamer, Bruno Rodrigues, Jan von der Assen, Burkhard Stiller
https://arxiv.org/abs/2509.22568

Bridging Technical Capability and User Accessibility: Off-grid Civilian Emergency Communication
During large-scale crises disrupting cellular and Internet infrastructure, civilians lack reliable methods for communication, aid coordination, and access to trustworthy information. This paper presents a unified emergency communication system integrating a low-power, long-range network with a crisis-oriented smartphone application, enabling decentralized and off-grid civilian communication. Unlike previous solutions separating physical layer resilience from user layer usability, our design mer…

Graph Neural Networks in Large Scale Wireless Communication Networks: Scalability Across Random Geometric Graphs
Romina Garcia Camargo, Zhiyang Wang, Alejandro Ribeiro
https://arxiv.org/abs/2510.00896 …

Graph Neural Networks in Large Scale Wireless Communication Networks: Scalability Across Random Geometric Graphs
The growing complexity of wireless systems has accelerated the move from traditional methods to learning-based solutions. Graph Neural Networks (GNNs) are especially well-suited here, since wireless networks can be naturally represented as graphs. A key property of GNNs is transferability: models trained on one graph often generalize to much larger graphs with little performance loss. While empirical studies have shown that GNN-based wireless policies transfer effectively, existing theoretical …

Enhancing Communication Efficiency in FL with Adaptive Gradient Quantization and Communication Frequency Optimization
Asadullah Tariq, Tariq Qayyum, Mohamed Adel Serhani, Farag Sallabi, Ikbal Taleb, Ezedin S. Barka
https://arxiv.org/abs/2509.23419

Enhancing Communication Efficiency in FL with Adaptive Gradient Quantization and Communication Frequency Optimization
Federated Learning (FL) enables participant devices to collaboratively train deep learning models without sharing their data with the server or other devices, effectively addressing data privacy and computational concerns. However, FL faces a major bottleneck due to high communication overhead from frequent model updates between devices and the server, limiting deployment in resource-constrained wireless networks. In this paper, we propose a three-fold strategy. Firstly, an Adaptive Feature-Eli…

Asynchronous Nonlinear Sheaf Diffusion for Multi-Agent Coordination
Yichen Zhao, Tyler Hanks, Hans Riess, Samuel Cohen, Matthew Hale, James Fairbanks
https://arxiv.org/abs/2510.00270

Asynchronous Nonlinear Sheaf Diffusion for Multi-Agent Coordination
Cellular sheaves and sheaf Laplacians provide a far-reaching generalization of graphs and graph Laplacians, resulting in a wide array of applications ranging from machine learning to multi-agent control. In the context of multi-agent systems, so called coordination sheaves provide a unifying formalism that models heterogeneous agents and coordination goals over undirected communication topologies, and applying sheaf diffusion drives agents to achieve their coordination goals. Existing literatur…

Zero-Shot Decentralized Federated Learning
Alessio Masano, Matteo Pennisi, Federica Proietto Salanitri, Concetto Spampinato, Giovanni Bellitto
https://arxiv.org/abs/2509.26462 h…

Zero-Shot Decentralized Federated Learning
CLIP has revolutionized zero-shot learning by enabling task generalization without fine-tuning. While prompting techniques like CoOp and CoCoOp enhance CLIP's adaptability, their effectiveness in Federated Learning (FL) remains an open challenge. Existing federated prompt learning approaches, such as FedCoOp and FedTPG, improve performance but face generalization issues, high communication costs, and reliance on a central server, limiting scalability and privacy. We propose Zero-shot Decentrali…

uni_email: Email network (Uni. R-V, Spain, 2003)
A network representing the exchange of emails among members of the Rovira i Virgili University in Spain, in 2003. The KONECT version is undirected.
This network has 1133 nodes and 10903 edges.
Tags: Social, Communication, Unweighted
https://networks.skewed.de/net…

A Secure Affine Frequency Division Multiplexing for Wireless Communication Systems
Ping Wang, Zulin Wang, Yuanhan Ni, Qu Luo, Yuanfang Ma, Xiaosi Tian, Pei Xiao
https://arxiv.org/abs/2510.02023

A Secure Affine Frequency Division Multiplexing for Wireless Communication Systems
Affine frequency division multiplexing (AFDM) has garnered significant attention due to its superior performance in high-mobility scenarios, coupled with multiple waveform parameters that provide greater degrees of freedom for system design. This paper introduces a novel secure affine frequency division multiplexing (SE-AFDM) system, which advances prior designs by dynamically varying an AFDM pre-chirp parameter to enhance physical-layer security. In the SE-AFDM system, the pre-chirp parameter …

A Review of Software for Designing and Operating Quantum Networks
Robert J. Hayek, Joaquin Chung, Rajkumar Kettimuthu
https://arxiv.org/abs/2510.00203 https://

A Review of Software for Designing and Operating Quantum Networks
Quantum network protocol development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around the three-p…

Coverage and Rate Performance Analysis of Multi-RIS-Assisted Dual-Hop mmWave Networks
Yuwen Cao, Xiaowen Wu, Jiguang He, Tomoaki Ohtsuki, Tony Q. S. Quek
https://arxiv.org/abs/2509.00717

Coverage and Rate Performance Analysis of Multi-RIS-Assisted Dual-Hop mmWave Networks
Millimeter-wave (mmWave) communication, which operates at high frequencies, has gained extensive research interest due to its significantly wide spectrum and short wavelengths. However, mmWave communication suffers from the notable drawbacks as follows: i) The mmWave signals are sensitive to the blockage, which is caused by the weak diffraction ability of mmWave propagation; ii) Even though the introduction of reconfigurable intelligent surfaces (RISs) can overcome the performance degradation c…

Fast, Secure, and High-Capacity Image Watermarking with Autoencoded Text Vectors
Gautier Evennou, Vivien Chappelier, Ewa Kijak
https://arxiv.org/abs/2510.00799 https://

Fast, Secure, and High-Capacity Image Watermarking with Autoencoded Text Vectors
Most image watermarking systems focus on robustness, capacity, and imperceptibility while treating the embedded payload as meaningless bits. This bit-centric view imposes a hard ceiling on capacity and prevents watermarks from carrying useful information. We propose LatentSeal, which reframes watermarking as semantic communication: a lightweight text autoencoder maps full-sentence messages into a compact 256-dimensional unit-norm latent vector, which is robustly embedded by a finetuned watermar…

Neural Network-Based Single-Carrier Joint Communication and Sensing: Loss Design, Constellation Shaping and Precoding
Charlotte Muth, Benedikt Geiger, Daniel Gil Gaviria, Laurent Schmalen
https://arxiv.org/abs/2509.26508

Neural Network-Based Single-Carrier Joint Communication and Sensing: Loss Design, Constellation Shaping and Precoding
We investigate the impact of higher-order modulation formats on the sensing performance of single-carrier joint communication and sensing (JCAS) systems. Several separate components such as a beamformer, a modulator, a target detector, an angle of arrival (AoA) estimator and a communication demapper are implemented as trainable neural networks (NNs). We compare geometrically shaped modulation formats to a classical quadrature amplitude modulation (QAM) scheme. We assess the influence of multi-s…

Partial Parameter Updates for Efficient Distributed Training
Anastasiia Filippova, Angelos Katharopoulos, David Grangier, Ronan Collobert
https://arxiv.org/abs/2509.22418 https:…

Partial Parameter Updates for Efficient Distributed Training
We introduce a memory- and compute-efficient method for low-communication distributed training. Existing methods reduce communication by performing multiple local updates between infrequent global synchronizations. We demonstrate that their efficiency can be significantly improved by restricting backpropagation: instead of updating all the parameters, each node updates only a fixed subset while keeping the remainder frozen during local steps. This constraint substantially reduces peak memory us…

User-Centric Communication Service Provision for Edge-Assisted Mobile Augmented Reality
Conghao Zhou, Jie Gao, Shisheng Hu, Nan Cheng, Weihua Zhuang, Xuemin Shen
https://arxiv.org/abs/2509.25905

User-Centric Communication Service Provision for Edge-Assisted Mobile Augmented Reality
Future 6G networks are envisioned to facilitate edge-assisted mobile augmented reality (MAR) via strengthening the collaboration between MAR devices and edge servers. In order to provide immersive user experiences, MAR devices must timely upload camera frames to an edge server for simultaneous localization and mapping (SLAM)-based device pose tracking. In this paper, to cope with user-specific and non-stationary uplink data traffic, we develop a digital twin (DT)-based approach for user-centric…

SlimPack: Fine-Grained Asymmetric Packing for Balanced and Efficient Variable-Length LLM Training
Yuliang Liu, Guohao Wu, Shenglong Zhang, Wei Zhang, Qianchao Zhu, Zhouyang Li, Chenyu Wang
https://arxiv.org/abs/2509.26246

SlimPack: Fine-Grained Asymmetric Packing for Balanced and Efficient Variable-Length LLM Training
The efficient distributed training of Large Language Models (LLMs) is severely hampered by the extreme variance in context lengths. This data heterogeneity, amplified by conventional packing strategies and asymmetric forward-backward costs, leads to critical inefficiencies such as cascading workload imbalances and severe hardware underutilization. Existing solutions attempt to mitigate these challenges, but often at the expense of memory or communication efficiency. To address these challenge…

route_views: Route Views AS graphs (1997-1998)
733 daily network snapshots denoting BGP traffic among autonomous systems (ASs) on the Internet, from the Oregon Route Views Project, spanning 8 November 1997 to 2 January 2000. Data collected by NLANR/MOAT.
This network has 3971 nodes and 7604 edges.
Tags: Technological, Communication, Unweighted, Temporal

Exponential Quantum Advantage for Message Complexity in Distributed Algorithms
Fran\c{c}ois Le Gall, Ma\"el Luce, Joseph Marchand, Mathieu Roget
https://arxiv.org/abs/2510.01657

Exponential Quantum Advantage for Message Complexity in Distributed Algorithms
We investigate how much quantum distributed algorithms can outperform classical distributed algorithms with respect to the message complexity (the overall amount of communication used by the algorithm). Recently, Dufoulon, Magniez and Pandurangan (PODC 2025) have shown a polynomial quantum advantage for several tasks such as leader election and agreement. In this paper, we show an exponential quantum advantage for a fundamental task: routing information between two specified nodes of a network.…

Joint Communication and Parameter Estimation in MIMO Channels
G\"okhan Y{\i}lmaz, Franz Lampel, Hamdi Joudeh, Giuseppe Caire
https://arxiv.org/abs/2509.26365 https://

Joint Communication and Parameter Estimation in MIMO Channels
We study a joint communication and sensing setting comprising a transmitter, a receiver, and a sensor, all equipped with multiple antennas. The transmitter sends an encoded signal over the channel with the dual purpose of communicating an information message to the receiver, and enabling the sensor to estimate a target parameter vector by generating back-scattered signals. We assume that the transmitter and sensor are co-located, or fully connected, giving the latter access to the transmitted s…

Secrecy-Driven Beamforming for Multi-User Integrated Sensing and Communication
Ali Khandan Boroujeni, Hyeon Seok Rou, Ghazal Bagheri, Kuranage Roche Rayan Ranasinghe, Giuseppe Thadeu Freitas de Abreu, Stefan K\"opsell, Rafael F. Schaefer
https://arxiv.org/abs/2509.26249

Secrecy-Driven Beamforming for Multi-User Integrated Sensing and Communication
This paper proposes a secure integrated sensing and communications (ISAC) framework for multi-user systems with multiple communication users (CUs) and adversarial targets, where the design problem is formulated to maximize secrecy rate under joint sensing and communication constraints. An efficient solution is presented based on an accelerated fractional programming method using a non-homogeneous complex quadratic transform (QT), which decomposes the problem into tractable subproblems for beamf…

Secure Multi-Modal Data Fusion in Federated Digital Health Systems via MCP
Aueaphum Aueawatthanaphisut
https://arxiv.org/abs/2510.01780 https://arxiv.org/p…

Secure Multi-Modal Data Fusion in Federated Digital Health Systems via MCP
Secure and interoperable integration of heterogeneous medical data remains a grand challenge in digital health. Current federated learning (FL) frameworks offer privacy-preserving model training but lack standardized mechanisms to orchestrate multi-modal data fusion across distributed and resource-constrained environments. This study introduces a novel framework that leverages the Model Context Protocol (MCP) as an interoperability layer for secure, cross-agent communication in multi-modal fede…

Commmunication-Efficient and Accurate Approach for Aggregation in Federated Low-Rank Adaptation
Le-Tuan Nguyen, Minh-Duong Nguyen, Seon-Geun Jeong, Dung D. Le, Quoc-Viet Pham
https://arxiv.org/abs/2509.26399

Commmunication-Efficient and Accurate Approach for Aggregation in Federated Low-Rank Adaptation
With the rapid emergence of foundation models and the increasing need for fine-tuning across distributed environments, Federated Low-Rank Adaptation (FedLoRA) has recently gained significant attention. Despite enormous potential, current FedLoRA methods face notable challenges due to inexact updates. Existing approaches have attempted to mitigate this issue, but they often introduce a \emph{local-global generalization gap} and incur \emph{substantial communication overhead}, limiting their scal…

internet_as: Internet AS graph (2006)
A symmetrized snapshot of the structure of the Internet at the level of Autonomous Systems (ASs), reconstructed from BGP tables posted by the University of Oregon Route Views Project. This snapshot was created on 22 July 2006.
This network has 22963 nodes and 48436 edges.
Tags: Technological, Communication, Unweighted

Hybrid biphoton spectrometer for time-resolved quantum spectroscopy across visible and near-infrared regions
Ozora Iso, Koya Onoda, Nicola J. Fairbairn, Masahiro Yabuno, Hirotaka Terai, Shigehito Miki, Ryosuke Shimizu
https://arxiv.org/abs/2510.01836

Hybrid biphoton spectrometer for time-resolved quantum spectroscopy across visible and near-infrared regions
Joint spectral measurements are a powerful tool for characterising biphoton spectral correlation, which is crucial for quantum information and communication technologies. In these applications, highly pure biphoton states are essential in any time- and frequency-mode, often obviating the need for time-resolved measurements. Conversely, spectroscopy utilising entangled photon pairs is gaining significant attention for its ability to unveil molecular dynamics, a field that critically demands time…

Intelligent Spectrum Management in Satellite Communications
Rakshitha De Silva, Shiva Raj Pokhrel, Jonathan Kua, Sithamparanathan Kandeepan
https://arxiv.org/abs/2509.00286 http…

Intelligent Spectrum Management in Satellite Communications
Satellite Communication (SatCom) networks represent a fundamental pillar in modern global connectivity, facilitating reliable service and extensive coverage across a plethora of applications. The expanding demand for high-bandwidth services and the proliferation of mega satellite constellations highlight the limitations of traditional exclusive satellite spectrum allocation approaches. Cognitive Radio (CR) leading to Cognitive Satellite (CogSat) networks through Dynamic Spectrum Management (DSM…

Meta-Learning-Driven Resource Optimization in Full-Duplex ISAC with Movable Antennas
Ali Amhaz, Shreya Khisa, Mohamed Elhattab, Chadi Assi, Sanaa Sharafeddine
https://arxiv.org/abs/2510.01437

Meta-Learning-Driven Resource Optimization in Full-Duplex ISAC with Movable Antennas
This paper investigates a full-duplex (FD) scenario where a base station (BS) equipped with movable antennas (MAs) simultaneously provides communication services to a set of downlink (DL) and uplink (UL) users while also enabling sensing functionalities for target detection, thereby supporting integrated sensing and communication (ISAC) technology. Additionally, a receiving BS, also equipped with MAs (denoted as BS R), is responsible for capturing the reflected echo. To optimize this setup, we …

Physical Layer Security over Fluid Reconfigurable Intelligent Surface-assisted Communication Systems
Masoud Kaveh, Farshad Rostami Ghadi, Francisco Hernando-Gallego, Diego Mart\'in, Kai-Kit Wong, Riku J\"antti
https://arxiv.org/abs/2509.24845

Physical Layer Security over Fluid Reconfigurable Intelligent Surface-assisted Communication Systems
This letter investigates the secrecy performance of wireless communication systems assisted by a fluid reconfigurable intelligent surface (FRIS). Unlike conventional reconfigurable intelligent surfaces (RISs) with fixed geometries, FRISs dynamically select a subset of reflective elements based on real-time channel conditions, offering enhanced spatial diversity and adaptability. Using this foundation, we model a secure downlink scenario where a base station communicates with a legitimate user i…

QScale: Probabilistic Chained Consensus for Moderate-Scale Systems
Hasan Heydari, Alysson Bessani, Kartik Nayak
https://arxiv.org/abs/2510.01536 https://ar…

QScale: Probabilistic Chained Consensus for Moderate-Scale Systems
Existing distributed ledger protocols either incur a high communication complexity and are thus suited to systems with a small number of processes (e.g., PBFT), or rely on committee-sampling-based approaches that only work for a very large number of processes (e.g., Algorand). Neither of these lines of work is well-suited for moderate-scale distributed ledgers ranging from a few hundred to a thousand processes, which are common in production (e.g, Redbelly, Sui). The goal of this work is to des…

email_company: Manufacturing company email (2010)
A network of emails among employee email addresses at a mid-sized manufacturing company. Each directed edge represents an email sent from address i to address j. Edges are timestamped, and occurred over a 6 month period in an unspecified year.
This network has 167 nodes and 82927 edges.
Tags: Social, Communication, Unweighted, Multigraph, Timestamps

Photonic Simulation of Beyond-Quantum Nonlocal Correlations (e.g. Popescu-Rohrlich Box) with Non-Signaling Quantum Resources
Kunal Shukla, Anirudh Verma, Kanad Sengupta, Sanchari Chakraborti, Manik Banik, C. M. Chandrashekar
https://arxiv.org/abs/2509.26271

Photonic Simulation of Beyond-Quantum Nonlocal Correlations (e.g. Popescu-Rohrlich Box) with Non-Signaling Quantum Resources
Bell nonlocality exemplifies the most profound departure of quantum theory from classical realism. Yet, the extent of nonlocality in quantum theory is intrinsically bounded, falling short of the correlations permitted by the relativistic causality (the no-signaling) principle. A paradigmatic example is the Popescu-Rohrlich correlation: two distant parties sharing arbitrary entanglement cannot achieve this correlation, though it can be simulated with classical communication between them. Here we…

Ocior: Ultra-Fast Asynchronous Leaderless Consensus with Two-Round Finality, Linear Overhead, and Adaptive Security
Jinyuan Chen
https://arxiv.org/abs/2509.01118 https://…

Ocior: Ultra-Fast Asynchronous Leaderless Consensus with Two-Round Finality, Linear Overhead, and Adaptive Security
In this work, we propose Ocior, a practical asynchronous Byzantine fault-tolerant (BFT) consensus protocol that achieves the optimal performance in resilience, communication, computation, and round complexity. Unlike traditional BFT consensus protocols, Ocior processes incoming transactions individually and concurrently using parallel instances of consensus. While leader-based consensus protocols rely on a designated leader to propose transactions, Ocior is a leaderless consensus protocol that …

Intelligent Optimization of Wireless Access Point Deployment for Communication-Based Train Control Systems Using Deep Reinforcement Learning
Kunyu Wu, Qiushi Zhao, Zihan Feng, Yunxi Mu, Hao Qin, Xinyu Zhang, Xingqi Zhang
https://arxiv.org/abs/2509.24819

Intelligent Optimization of Wireless Access Point Deployment for Communication-Based Train Control Systems Using Deep Reinforcement Learning
Urban railway systems increasingly rely on communication based train control (CBTC) systems, where optimal deployment of access points (APs) in tunnels is critical for robust wireless coverage. Traditional methods, such as empirical model-based optimization algorithms, are hindered by excessive measurement requirements and suboptimal solutions, while machine learning (ML) approaches often struggle with complex tunnel environments. This paper proposes a deep reinforcement learning (DRL) driven f…

Make a Video Call with LLM: A Measurement Campaign over Five Mainstream Apps
Jiayang Xu, Xiangjie Huang, Zijie Li, Zili Meng
https://arxiv.org/abs/2510.00481 https://

Make a Video Call with LLM: A Measurement Campaign over Five Mainstream Apps
In 2025, Large Language Model (LLM) services have launched a new feature -- AI video chat -- allowing users to interact with AI agents via real-time video communication (RTC), just like chatting with real people. Despite its significance, no systematic study has characterized the performance of existing AI video chat systems. To address this gap, this paper proposes a comprehensive benchmark with carefully designed metrics across four dimensions: quality, latency, internal mechanisms, and syste…

HiCR, an Abstract Model for Distributed Heterogeneous Programming
Sergio Miguel Martin, Luca Terracciano, Kiril Dichev, Noah Baumann, Jiashu Lin, Albert-Jan Yzelman
https://arxiv.org/abs/2509.01425

HiCR, an Abstract Model for Distributed Heterogeneous Programming
We present HiCR, a model to represent the semantics of distributed heterogeneous applications and runtime systems. The model describes a minimal set of abstract operations to enable hardware topology discovery, kernel execution, memory management, communication, and instance management, without prescribing any implementation decisions. The goal of the model is to enable execution in current and future systems without the need for significant refactoring, while also being able to serve any gover…

Enhancing Connectivity for Emergency Vehicles Through UAV Trajectory and Resource Allocation Optimization
S. Fatemeh Bozorgi, S. Mohammad Razavizadeh, Mohsen Rezaee
https://arxiv.org/abs/2509.26067

Enhancing Connectivity for Emergency Vehicles Through UAV Trajectory and Resource Allocation Optimization
Effective communication for emergency vehicles - such as ambulances and fire trucks - is essential to support their operations in various traffic and environmental conditions. In this context, this paper investigates a vehicular communication system assisted by an Unmanned Aerial Vehicle (UAV), which adjusts its trajectory and resource allocation according to communication needs. The system classifies vehicles into two groups to address their varying service requirements: emergency vehicles, wh…

Prediction-Powered Communication with Distortion Guarantees
Matteo Zecchin, Unnikrishnan Kunnath Ganesan, Giuseppe Durisi, Petar Popovski, Osvaldo Simeone
https://arxiv.org/abs/2509.24373

Prediction-Powered Communication with Distortion Guarantees
The development of 6G wireless systems is taking place alongside the development of increasingly intelligent wireless devices and network nodes. The changing technological landscape is motivating a rethinking of classical Shannon information theory that emphasizes semantic and task-oriented paradigms. In this paper, we study a prediction-powered communication setting, in which devices, equipped with artificial intelligence (AI)-based predictors, communicate under zero-delay constraints with str…

Replaced article(s) found for cs.NI. https://arxiv.org/list/cs.NI/new
[1/1]:
- A Modular and Scalable Simulator for Connected-UAVs Communication in 5G Networks
Yong Su, Yiyi Chen, Shenghong Yi, Hui Feng, Yuedong Xu, Wang Xiang, Bo Hu

IoT-MCP: Bridging LLMs and IoT Systems Through Model Context Protocol
Ningyuan Yang, Guanliang Lyu, Mingchen Ma, Yiyi Lu, Yiming Li, Zhihui Gao, Hancheng Ye, Jianyi Zhang, Tingjun Chen, Yiran Chen
https://arxiv.org/abs/2510.01260

IoT-MCP: Bridging LLMs and IoT Systems Through Model Context Protocol
The integration of Large Language Models (LLMs) with Internet-of-Things (IoT) systems faces significant challenges in hardware heterogeneity and control complexity. The Model Context Protocol (MCP) emerges as a critical enabler, providing standardized communication between LLMs and physical devices. We propose IoT-MCP, a novel framework that implements MCP through edge-deployed servers to bridge LLMs and IoT ecosystems. To support rigorous evaluation, we introduce IoT-MCP Bench, the first bench…

Enhancing Urban VANETs Stability: A Single-Hop Clustering Strategy in Metropolitan Environments
Pouya Firouzmakan, Suprakash Datta
https://arxiv.org/abs/2510.00939 https://

Enhancing Urban VANETs Stability: A Single-Hop Clustering Strategy in Metropolitan Environments
Vehicular Ad-hoc Networks (VANETs), a subclass of Mobile Ad-hoc Networks (MANETs), are expected to play a crucial role in the future of intelligent transportation systems (ITSs). A key objective of VANETs is to enable efficient and cost-effective communication among vehicles while supporting a large number of network participants and minimizing infrastructure dependency. However, the highly dynamic nature of vehicular networks poses significant challenges to their deployment. Clustering techniq…

Accuracy vs Performance: An abstraction model for deadline constrained offloading at the mobile-edge
Jamie Cotter, Ignacio Castineiras, Victor Cionca
https://arxiv.org/abs/2510.01885

Accuracy vs Performance: An abstraction model for deadline constrained offloading at the mobile-edge
In this paper, we present a solution for low-latency deadline-constrained DNN offloading on mobile edge devices. We design a scheduling algorithm with lightweight network state representation, considering device availability, communication on the network link, priority-aware pre-emption, and task deadlines. The scheduling algorithm aims to reduce latency by designing a resource availability representation, as well as a network discretisation and a dynamic bandwidth estimation mechanism. We impl…

Movable Antenna Empowered Secure Near-Field MIMO Communications
Yaodong Ma, Kai Liu, Yanming Liu, Lipeng Zhu
https://arxiv.org/abs/2509.00901 https://arxiv…

Movable Antenna Empowered Secure Near-Field MIMO Communications
This paper investigates movable antenna (MA) empowered secure transmission in near-field multiple-input multiple-output (MIMO) communication systems, where the base station (BS) equipped with an MA array transmits confidential information to a legitimate user under the threat of a potential eavesdropper. To enhance physical layer security (PLS) of the considered system, we aim to maximize the secrecy rate by jointly designing the hybrid digital and analog beamformers, as well as the positions o…

Dual-Function Beam Pattern Design for Multi-Target ISAC Systems: A Decoupled Approach
Wilson de Souza Junior, Taufik Abrao, Amine Mezghani, Ekram Hossain
https://arxiv.org/abs/2509.23302

Dual-Function Beam Pattern Design for Multi-Target ISAC Systems: A Decoupled Approach
We investigate the beampattern design problem for mono-static multi-user (MU) multi-point-target integrated sensing and communication (ISAC) systems, where a dual-function multiple-input multiple-output (DF-MIMO) base station (BS) performs downlink communication and radar sensing simultaneously. In ISAC systems, sensing and communication inherently compete for resources. As communication demand increases, the beam pattern is reshaped, which might degrade the direction of arrival (DoA) sensing a…

Odontoceti: Ultra-Fast DAG Consensus with Two Round Commitment
Preston Vander Vos
https://arxiv.org/abs/2510.01216 https://arxiv.org/pdf/2510.01216

Odontoceti: Ultra-Fast DAG Consensus with Two Round Commitment
Users of blockchains value scalability, expecting fast confirmations and immediate transaction processing. Odontoceti, the latest in DAG-based consensus, addresses these concerns by prioritizing low latency and high throughput, making a strategic trade-off in security by operating with a 20% fault tolerance instead of the established 33% level. It is the first DAG-based protocol to achieve commitment in just two communication rounds, delivering median latency of 300 milliseconds while processin…

On the Resilience of Direction-Shift Keying Against Phase Noise and Short Channel Coherence Time at mmWave Frequencies
Mohaned Chraiti, Ozgur Ercetin, Ali Ghrayeb, Ali Gorcin
https://arxiv.org/abs/2509.01103

On the Resilience of Direction-Shift Keying Against Phase Noise and Short Channel Coherence Time at mmWave Frequencies
The rapid variation of the wireless channel (short channel coherence time) and the phase noise are two prominent concerns in Millimeter-wave (mmWave) and sub-Terahertz systems communication systems. Equalizing the channel effect and tracking the phase noise necessitate dense pilot insertion. Direction-Shift Keying (DSK), a recent variant of Spatial Modulation (SM), addresses these challenges by encoding information in the Direction-of-Arrival (DoA) using a distributed antenna system (DAS), rath…

GRACE-MoE: Grouping and Replication with Locality-Aware Routing for Efficient Distributed MoE Inference
Yu Han, Lehan Pan, Jie Peng, Ziyang Tao, Wuyang Zhang, Yanyong Zhang
https://arxiv.org/abs/2509.25041

GRACE-MoE: Grouping and Replication with Locality-Aware Routing for Efficient Distributed MoE Inference
Sparse Mixture of Experts (SMoE) performs conditional computation by selectively activating a subset of experts, thereby enabling scalable parameter growth in large language models (LLMs). However, the expanded parameter scale exceeds the memory capacity of a single device, necessitating distributed deployment for inference. This setup introduces two critical challenges: (1) Communication Issue: Transferring features to devices with activated experts leads to significant communication overhead.…

Collaborative Edge Inference via Semantic Grouping under Wireless Channel Constraints
Mateus P. Mota, Mattia Merluzzi, Emilio Calvanese Strinati
https://arxiv.org/abs/2510.02222

Collaborative Edge Inference via Semantic Grouping under Wireless Channel Constraints
In this paper, we study the framework of collaborative inference, or edge ensembles. This framework enables multiple edge devices to improve classification accuracy by exchanging intermediate features rather than raw observations. However, efficient communication strategies are essential to balance accuracy and bandwidth limitations. Building upon a key-query mechanism for selective information exchange, this work extends collaborative inference by studying the impact of channel noise in featur…

Sensing-Secure ISAC: Ambiguity Function Engineering for Impairing Unauthorized Sensing
Kawon Han, Kaitao Meng, Christos Masouros
https://arxiv.org/abs/2510.02103 https://…

Sensing-Secure ISAC: Ambiguity Function Engineering for Impairing Unauthorized Sensing
The deployment of integrated sensing and communication (ISAC) brings along unprecedented vulnerabilities to authorized sensing, necessitating the development of secure solutions. Sensing parameters are embedded within the target-reflected signal leaked to unauthorized passive radar sensing eavesdroppers (Eve), implying that they can silently extract sensory information without prior knowledge of the information data. To overcome this limitation, we propose a sensing-secure ISAC framework that e…

Joint Channel and Semantic-aware Grouping for Effective Collaborative Edge Inference
Mateus P. Mota, Mattia Merluzzi, Emilio Calvanese Strinati
https://arxiv.org/abs/2510.02191 …

Joint Channel and Semantic-aware Grouping for Effective Collaborative Edge Inference
We focus on collaborative edge inference over wireless, which enables multiple devices to cooperate to improve inference performance in the presence of corrupted data. Exploiting a key-query mechanism for selective information exchange (or, group formation for collaboration), we recall the effect of wireless channel impairments in feature communication. We argue and show that a disjoint approach, which only considers either the semantic relevance or channel state between devices, performs poorl…

Secure ISAC with Fluid Antenna Systems: Joint Precoding and Port Selection
Abdelhamid Salem, Hao Xu, Kai-Kit Wong, Chan-Byoung Chae, Yangyang Zhang
https://arxiv.org/abs/2509.26572

Secure ISAC with Fluid Antenna Systems: Joint Precoding and Port Selection
This paper presents a novel framework for enhancing physical-layer security in integrated sensing and communication (ISAC) systems by leveraging the reconfigurability of fluid antenna systems (FAS). We propose a joint precoding and port selection (JPPS) strategy that maximizes the sum secrecy rate while simultaneously ensuring reliable radar sensing. The problem is formulated using fractional programming (FP) and solved through an iterative algorithm that integrates FP transformations with succ…

Joint Hybrid Beamforming and Artificial Noise Design for Secure Multi-UAV ISAC Networks
Runze Dong, Buhong Wang, Cunqian Feng, Jiang Weng, Chen Han, Jiwei Tian
https://arxiv.org/abs/2509.23687

Joint Hybrid Beamforming and Artificial Noise Design for Secure Multi-UAV ISAC Networks
Integrated sensing and communication (ISAC) emerges as a key enabler for next-generation applications such as smart cities and autonomous systems. Its integration with unmanned aerial vehicles (UAVs) unlocks new potentials for reliable communication and precise sensing in dynamic aerial environments. However, existing research predominantly treats UAVs as aerial base stations, overlooking their role as ISAC users, and fails to leverage large-scale antenna arrays at terrestrial base stations to …

Machine Learning-based Path Loss Prediction in Suburban Environment in the Sub-6 GHz Band
Ferdaous Tarhouni, Muneer AlZubi, Mohamed-Slim Alouini
https://arxiv.org/abs/2510.00696

Machine Learning-based Path Loss Prediction in Suburban Environment in the Sub-6 GHz Band
Accurate path loss (PL) prediction is crucial for successful network planning, antenna design, and performance optimization in wireless communication systems. Several conventional approaches for PL prediction have been adopted, but they have been demonstrated to lack flexibility and accuracy. In this work, we investigate the effectiveness of Machine Learning (ML) models in predicting PL, particularly for the sub-6 GHz band in a suburban campus of King Abdullah University of Science and Technolo…

NGGAN: Noise Generation GAN Based on the Practical Measurement Dataset for Narrowband Powerline Communications
Ying-Ren Chien, Po-Heng Chou, You-Jie Peng, Chun-Yuan Huang, Hen-Wai Tsao, Yu Tsao
https://arxiv.org/abs/2510.01850

NGGAN: Noise Generation GAN Based on the Practical Measurement Dataset for Narrowband Powerline Communications
Capturing comprehensive statistics of nonperiodic asynchronous impulsive noise is a critical issue in enhancing impulse noise processing for narrowband powerline communication (NB-PLC) transceivers. However, existing mathematical noise generative models capture only some of the characteristics of additive noise. Therefore, we propose a generative adversarial network (GAN), called the noise-generation GAN (NGGAN), that learns the complicated characteristics of practically measured noise samples …

Composite Generalized Quadratic Noise Modulation via Signal Addition: Towards Higher Dimensional Noise Modulations
Hadi Zayyani, Mohammad Salman, Felipe A. P. de Figueiredo, Rausley A. A. de Souza
https://arxiv.org/abs/2510.01776

Composite Generalized Quadratic Noise Modulation via Signal Addition: Towards Higher Dimensional Noise Modulations
This letter proposes superposing two Generalized Quadratic Noise Modulators (GQNM) by simply adding their outputs. It creates a 16-ary noise modulator that resembles QAM modulators in classical communication. It modulates the information bits on four different means and four different variances. It could also be applied to reach higher-order modulations than 16-ary schemes by adding the outputs of more than two modulators, which is not discussed in detail in this letter and left for future work…

A Graph-based Hybrid Beamforming Framework for MIMO Cell-Free ISAC Networks
Yanan Du, Sai Xu, Jagmohan Chauhan
https://arxiv.org/abs/2509.25385 https://arx…

A Graph-based Hybrid Beamforming Framework for MIMO Cell-Free ISAC Networks
This paper develops a graph-based hybrid beamforming framework for multiple-input multiple-output (MIMO) cell-free integrated sensing and communication (ISAC) networks. Specifically, we construct a novel MIMO cell-free ISAC network model. In this model, multiple dual-function base station (BS) transmitters employ distributed hybrid beamforming to enable simultaneous communication and sensing, while maintaining physical separation between the transmitters and the radar receiver. Building on this…

Joint Jammer Mitigation and Data Detection
Gian Marti, Christoph Studer
https://arxiv.org/abs/2510.02021 https://arxiv.org/pdf/2510.02021

Joint Jammer Mitigation and Data Detection
Multi-antenna (or MIMO) processing is a promising solution to the problem of jammer mitigation. Existing methods mitigate the jammer based on an estimate of its spatial signature that is acquired through a dedicated training phase. This strategy has two main drawbacks: (i) it reduces the communication rate since no data can be transmitted during the training phase and (ii) it can be evaded by smart or multi-antenna jammers that do not transmit during the training phase or that dynamically chang…

Transmitter-Side Beyond-Diagonal RIS-Enabled Integrated Sensing and Communications
Kexin Chen, Yijie Mao, Wonjae Shin
https://arxiv.org/abs/2509.26333 https://

Transmitter-Side Beyond-Diagonal RIS-Enabled Integrated Sensing and Communications
Beyond diagonal reconfigurable intelligent surfaces (BD-RIS) have emerged as a promising technology for 6G wireless networks, offering more advanced control over electromagnetic wave propagation than conventional diagonal RIS. This paper proposes a novel integrated sensing and communication (ISAC) framework that incorporates BD-RIS at the transmitter. This not only opens the door to enhanced sensing and communication performance, but also alleviates the need for large-scale fully digital radio …

Neural Integrated Sensing and Communication for the MIMO-OFDM Downlink
Ziyi Wang, Frederik Zumegen, Christoph Studer
https://arxiv.org/abs/2509.21118 https://

Neural Integrated Sensing and Communication for the MIMO-OFDM Downlink
The ongoing convergence of spectrum and hardware requirements for wireless sensing and communication applications has fueled the integrated sensing and communication (ISAC) paradigm in next-generation networks. Neural-network-based ISAC leverages data-driven learning techniques to add sensing capabilities to existing communication infrastructure. This paper presents a novel signal-processing framework for such neural ISAC systems based on the multiple-input multiple-output (MIMO) and orthogonal…