Tootfinder

This https://arxiv.org/abs/2404.04162 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

Wireless Resource Optimization in Hybrid Semantic/Bit Communication Networks
Recently, semantic communication (SemCom) has shown great potential in significant resource savings and efficient information exchanges, thus naturally introducing a novel and practical cellular network paradigm where two modes of SemCom and conventional bit communication (BitCom) coexist. Nevertheless, the involved wireless resource management becomes rather complicated and challenging, given the unique background knowledge matching and time-consuming semantic coding requirements in SemCom. To…

Real-time observation of picosecond-timescale optical quantum entanglement toward ultrafast quantum information processing
Akito Kawasaki, Hector Brunel, Ryuhoh Ide, Takumi Suzuki, Takahiro Kashiwazaki, Asuka Inoue, Takeshi Umeki, Taichi Yamashima, Atsushi Sakaguchi, Kan Takase, Mamoru Endo, Warit Asavanant, Akira Furusawa
https://

Real-time observation of picosecond-timescale optical quantum entanglement toward ultrafast quantum information processing
Entanglement is a fundamental resource of various optical quantum-information-processing (QIP) applications. Towards high-speed QIP system, entanglement should be encoded in short wavepackets. We report real-time observation of ultrafast optical Einstein-Podolsky-Rosen (EPR) correlation at a picosecond timescale in a continuous-wave (CW) system. Optical phase-sensitive amplification using 6-THz-bandwidth waveguide-optical-parametric amplifier enhances the effective efficiency of 70-GHz-bandwidt…

four theoretical perspectives on how retrieval improves new learning: resource theories, metacognitive theories, context theories, and integration theories. https://www.learningscientists.org/blog/2024/3/7/how-does-retrieval-improve-new-learning<…

This https://arxiv.org/abs/2305.06543 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

QoE-based Semantic-Aware Resource Allocation for Multi-Task Networks
By transmitting task-related information only, semantic communications yield significant performance gains over conventional communications. However, the lack of mature semantic theory about semantic information quantification and performance evaluation makes it challenging to perform resource allocation for semantic communications, especially when multiple tasks coexist in the network. To cope with this challenge, we propose a quality-of-experience (QoE) based semantic-aware resource allocatio…

This https://arxiv.org/abs/2312.05561 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Nonreciprocal Photon-Phonon Entanglement in Kerr-Modified Spinning Cavity Magnomechanics
Cavity magnomechanics has shown great potential in studying macroscopic quantum effects, especially for quantum entanglement, which is a key resource for quantum information science. Here we propose to realize magnon mediated nonreciprocal photon-phonon entanglement, which exhibits asymmetry when opposite magnetic or driving fields are respectively applied to the magnons with the Kerr effect or the photons with the Sagnac effect. We find that the mean magnon number can selectively exhibit nonre…

MRL Parsing Without Tears: The Case of Hebrew
Shaltiel Shmidman, Avi Shmidman, Moshe Koppel, Reut Tsarfaty
https://arxiv.org/abs/2403.06970 https://…

MRL Parsing Without Tears: The Case of Hebrew
Syntactic parsing remains a critical tool for relation extraction and information extraction, especially in resource-scarce languages where LLMs are lacking. Yet in morphologically rich languages (MRLs), where parsers need to identify multiple lexical units in each token, existing systems suffer in latency and setup complexity. Some use a pipeline to peel away the layers: first segmentation, then morphology tagging, and then syntax parsing; however, errors in earlier layers are then propagated …

four theoretical perspectives on how retrieval improves new learning: resource theories, metacognitive theories, context theories, and integration theories. https://www.learningscientists.org/blog/2024/3/7/how-does-retrieval-improve-new-learning<…

Measuring Data Similarity for Efficient Federated Learning: A Feasibility Study
Fernanda Fam\'a, Charalampos Kalalas, Sandra Lagen, Paolo Dini
https://arxiv.org/abs/2403.07450

Measuring Data Similarity for Efficient Federated Learning: A Feasibility Study
In multiple federated learning schemes, a random subset of clients sends in each round their model updates to the server for aggregation. Although this client selection strategy aims to reduce communication overhead, it remains energy and computationally inefficient, especially when considering resource-constrained devices as clients. This is because conventional random client selection overlooks the content of exchanged information and falls short of providing a mechanism to reduce the transmi…

Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks
Minwoo Kim, Jonggyu Jang, Youngchol Choi, Hyun Jong Yang
https://arxiv.org/abs/2404.03154

Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks
The growth in artificial intelligence (AI) technology has attracted substantial interests in age-of-information (AoI)-aware task offloading of mobile edge computing (MEC)-namely, minimizing service latency. Additionally, the use of MEC systems poses an additional problem arising from limited battery resources of MDs. This paper tackles the pressing challenge of AoI-aware distributed task offloading optimization, where user association (UA), resource allocation (RA), full-task offloading, and ba…

S-box Security Analysis of NIST Lightweight Cryptography Candidates: A Critical Empirical Study
Mahnoor Naseer, Sundas Tariq, Naveed Riaz, Naveed Ahmed, Mureed Hussain
https://arxiv.org/abs/2404.06094

S-box Security Analysis of NIST Lightweight Cryptography Candidates: A Critical Empirical Study
In the resource-constrained world of the digital landscape, lightweight cryptography plays a critical role in safeguarding information and ensuring the security of various systems, devices, and communication channels. Its efficient and resource-friendly nature makes it the ideal solution for applications where computational power is limited. In response to the growing need for platform-specific implementations, NIST issued a call for standardization of Lightweight cryptography algorithms in 201…

Age of Information Minimization using Multi-agent UAVs based on AI-Enhanced Mean Field Resource Allocation
Yousef Emami, Hao Gao, Kai Li, Luis Almeida, Eduardo Tovar, Zhu Han
https://arxiv.org/abs/2405.00056

Age of Information Minimization using Multi-agent UAVs based on AI-Enhanced Mean Field Resource Allocation
Unmanned Aerial Vehicle (UAV) swarms play an effective role in timely data collection from ground sensors in remote and hostile areas. Optimizing the collective behavior of swarms can improve data collection performance. This paper puts forth a new mean field flight resource allocation optimization to minimize age of information (AoI) of sensory data, where balancing the trade-off between the UAVs movements and AoI is formulated as a mean field game (MFG). The MFG optimization yields an expansi…

This https://arxiv.org/abs/2403.01564 has been replaced.
link: https://scholar.google.com/scholar?q=a

ComTraQ-MPC: Meta-Trained DQN-MPC Integration for Trajectory Tracking with Limited Active Localization Updates
Optimal decision-making for trajectory tracking in partially observable, stochastic environments where the number of active localization updates -- the process by which the agent obtains its true state information from the sensors -- are limited, presents a significant challenge. Traditional methods often struggle to balance resource conservation, accurate state estimation and precise tracking, resulting in suboptimal performance. This problem is particularly pronounced in environments with lar…

Metabolism, information, and viability in a simulated physically-plausible protocell
Kristoffer R. Thomsen, Artemy Kolchinsky, Steen Rasmussen
https://arxiv.org/abs/2405.04654

Metabolism, information, and viability in a simulated physically-plausible protocell
Critical experimental design issues connecting energy transduction and inheritable information within a protocell are explored and elucidated. The protocell design utilizes a photo-driven energy transducer (a ruthenium complex) to turn resource molecules into building blocks, in a manner that is modulated by a combinatorial DNA-based co-factor. This co-factor molecule serves as part of an electron relay for the energy transduction mechanism, where the charge-transport rates depend on the sequen…

Exact Analysis of the Age of Information in the Multi-Source M/GI/1 Queueing System
Yoshiaki Inoue, Tetsuya Takine
https://arxiv.org/abs/2404.05167 https:/…

Exact Analysis of the Age of Information in the Multi-Source M/GI/1 Queueing System
We consider a situation that multiple monitoring applications (each with a different sensor-monitor pair) compete for a common service resource such as a communication link. Each sensor reports the latest state of its own time-varying information source to its corresponding monitor, incurring queueing and processing delays at the shared resource. The primary performance metric of interest is the age of information (AoI) of each sensor-monitor pair, which is defined as the elapsed time from the …

This https://arxiv.org/abs/2305.06543 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

QoE-based Semantic-Aware Resource Allocation for Multi-Task Networks
By transmitting task-related information only, semantic communications yield significant performance gains over conventional communications. However, the lack of mature semantic theory about semantic information quantification and performance evaluation makes it challenging to perform resource allocation for semantic communications, especially when multiple tasks coexist in the network. To cope with this challenge, we propose a quality-of-experience (QoE) based semantic-aware resource allocatio…

This https://arxiv.org/abs/2402.01068 has been replaced.
link: https://scholar.google.com/scholar?q=a

Unbreakable and breakable quantum censorship
A protocol for regulating the distribution of quantum information between multiple parties is put forward. In order to prohibit the unrestricted distribution of quantum-resource states in a public quantum network, agents can apply a resource-destroying map to each sender's channel. Since resource-destroying maps only exist for affine quantum resource theories, censorship of a nonaffine resource theory is established on an operationally motivated subspace of free states. This is achieved by usin…

Exploiting CPU Clock Modulation for Covert Communication Channel
Shariful Alam, Jidong Xiao, Nasir U. Eisty
https://arxiv.org/abs/2404.05823 https://

Exploiting CPU Clock Modulation for Covert Communication Channel
Covert channel attacks represent a significant threat to system security, leveraging shared resources to clandestinely transmit information from highly secure systems, thereby violating the system's security policies. These attacks exploit shared resources as communication channels, necessitating resource partitioning and isolation techniques as countermeasures. However, mitigating attacks exploiting modern processors' hardware features to leak information is challenging because successful atta…

CoRAST: Towards Foundation Model-Powered Correlated Data Analysis in Resource-Constrained CPS and IoT
Yi Hu, Jinhang Zuo, Alanis Zhao, Bob Iannucci, Carlee Joe-Wong
https://arxiv.org/abs/2403.18451

CoRAST: Towards Foundation Model-Powered Correlated Data Analysis in Resource-Constrained CPS and IoT
Foundation models (FMs) emerge as a promising solution to harness distributed and diverse environmental data by leveraging prior knowledge to understand the complicated temporal and spatial correlations within heterogeneous datasets. Unlike distributed learning frameworks such as federated learning, which often struggle with multimodal data, FMs can transform diverse inputs into embeddings. This process facilitates the integration of information from various modalities and the application of pr…

This https://arxiv.org/abs/2311.04560 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Fast Generation of GHZ-like States Using Collective-Spin XYZ Model
The Greenberger-Horne-Zeilinger (GHZ) state is a key resource for quantum information processing and quantum metrology. The atomic GHZ state can be generated by one-axis twisting (OAT) interaction $H_{\mathrm{OAT}}=χJ_{z}^{2}$ with $χ$ the interaction strength, but it requires a long evolution time $χt=π/2$ and is thus seriously influenced by decoherence and losses. Here we propose a three-body collective-spin XYZ model which creates a GHZ-like state in a very short timescale $χt\sim \ln {…

This https://arxiv.org/abs/2403.16512 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

LLMs Are Few-Shot In-Context Low-Resource Language Learners
In-context learning (ICL) empowers large language models (LLMs) to perform diverse tasks in underrepresented languages using only short in-context information, offering a crucial avenue for narrowing the gap between high-resource and low-resource languages. Nonetheless, there is only a handful of works explored ICL for low-resource languages with most of them focusing on relatively high-resource languages, such as French and Spanish. In this work, we extensively study ICL and its cross-lingual …

Deploying Graph Neural Networks in Wireless Networks: A Link Stability Viewpoint
Jun Li, Weiwei Zhang, Kang Wei, Guangji Chen, Long Shi, Wen Chen
https://arxiv.org/abs/2405.05802 …

Deploying Graph Neural Networks in Wireless Networks: A Link Stability Viewpoint
As an emerging artificial intelligence technology, graph neural networks (GNNs) have exhibited promising performance across a wide range of graph-related applications. However, information exchanges among neighbor nodes in GNN pose new challenges in the resource-constrained scenario, especially in wireless systems. In practical wireless systems, the communication links among nodes are usually unreliable due to wireless fading and receiver noise, consequently resulting in performance degradation…

Resource-Aware Collaborative Monte Carlo Localization with Distribution Compression
Nicky Zimmerman, Alessandro Giusti, J\'er\^ome Guzzi
https://arxiv.org/abs/2404.02010

Resource-Aware Collaborative Monte Carlo Localization with Distribution Compression
Global localization is essential in enabling robot autonomy, and collaborative localization is key for multi-robot systems. In this paper, we address the task of collaborative global localization under computational and communication constraints. We propose a method which reduces the amount of information exchanged and the computational cost. We also analyze, implement and open-source seminal approaches, which we believe to be a valuable contribution to the community. We exploit techniques for …

Actionable forecasting as a determinant of function in noisy biological systems
Jose M. G. Vilar, Leonor Saiz
https://arxiv.org/abs/2404.07895 https://

Actionable forecasting as a determinant of function in noisy biological systems
Continuous adaptation to variable environments is crucial for the survival of living organisms. Here, we analyze how adaptation, forecasting, and resource mobilization towards a target state, termed actionability, interact to determine biological function. We develop a general theory and show that it is possible for organisms to continuously track their optimal state in a dynamic environment by adapting towards an actionable target that incorporates just current information on the optimal state…

This https://arxiv.org/abs/2405.00056 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Age of Information Minimization using Multi-agent UAVs based on AI-Enhanced Mean Field Resource Allocation
Unmanned Aerial Vehicle (UAV) swarms play an effective role in timely data collection from ground sensors in remote and hostile areas. Optimizing the collective behavior of swarms can improve data collection performance. This paper puts forth a new mean field flight resource allocation optimization to minimize age of information (AoI) of sensory data, where balancing the trade-off between the UAVs movements and AoI is formulated as a mean field game (MFG). The MFG optimization yields an expansi…

Potentials of Green Coding -- Findings and Recommendations for Industry, Education and Science -- Extended Paper
Dennis JungerHTW Berlin, Max WestingUmwelt-Campus Birkenfeld, Christopher P. FreitagHTW Berlin, Achim GuldnerUmwelt-Campus Birkenfeld, Konstantin MittelbachHTW Berlin, Kira Oberg\"okerUmwelt-Campus Birkenfeld, Sebastian WeberUmwelt-Campus Birkenfeld, Stefan NaumannUmwelt-Campus Birkenfeld, Volker WohlgemuthHTW Berlin

Potentials of Green Coding -- Findings and Recommendations for Industry, Education and Science -- Extended Paper
Progressing digitalization and increasing demand and use of software cause rises in energy- and resource consumption from information and communication technologies (ICT). This raises the issue of sustainability in ICT, which increasingly includes the sustainability of the software products themselves and the art of creating sustainable software. To this end, we conducted an analysis to gather and present existing literature on three research questions relating to the production of ecologically…

Deterministic Weighted Automata under Partial Observability
Jakub Michaliszyn, Jan Otop
https://arxiv.org/abs/2403.00390 https://arxi…

Deterministic Weighted Automata under Partial Observability
Weighted automata is a basic tool for specification in quantitative verification, which allows to express quantitative features of analysed systems such as resource consumption. Quantitative specification can be assisted by automata learning as there are classic results on Angluin-style learning of weighted automata. The existing work assumes perfect information about the values returned by the target weighted automaton. In assisted synthesis of a quantitative specification, knowledge of the ex…

MIND Your Language: A Multilingual Dataset for Cross-lingual News Recommendation
Andreea Iana, Goran Glava\v{s}, Heiko Paulheim
https://arxiv.org/abs/2403.17876

MIND Your Language: A Multilingual Dataset for Cross-lingual News Recommendation
Digital news platforms use news recommenders as the main instrument to cater to the individual information needs of readers. Despite an increasingly language-diverse online community, in which many Internet users consume news in multiple languages, the majority of news recommendation focuses on major, resource-rich languages, and English in particular. Moreover, nearly all news recommendation efforts assume monolingual news consumption, whereas more and more users tend to consume information in…

This https://arxiv.org/abs/2207.03612 has been replaced.
link: https://scholar.google.com/scholar?q=a

Trajectory Class Fluctuation Theorem
The Trajectory Class Fluctuation Theorem (TCFT) substantially strengthens the Second Law of Thermodynamics -- that, in point of fact, can be a rather weak bound on resource fluxes. Practically, it improves empirical estimates of free energies, a task known to be statistically challenging, and has diagnosed successful and failed information processing in experimentally-implemented Josephson-junction information engines. The development here justifies that empirical analysis, explicating its math…

Bayesian Simultaneous Localization and Multi-Lane Tracking Using Onboard Sensors and a SD Map
Yuxuan Xia, Erik Stenborg, Junsheng Fu, Gustaf Hendeby
https://arxiv.org/abs/2405.04290

Bayesian Simultaneous Localization and Multi-Lane Tracking Using Onboard Sensors and a SD Map
High-definition map with accurate lane-level information is crucial for autonomous driving, but the creation of these maps is a resource-intensive process. To this end, we present a cost-effective solution to create lane-level roadmaps using only the global navigation satellite system (GNSS) and a camera on customer vehicles. Our proposed solution utilizes a prior standard-definition (SD) map, GNSS measurements, visual odometry, and lane marking edge detection points, to simultaneously estimate…

How Lexical is Bilingual Lexicon Induction?
Harsh Kohli, Helian Feng, Nicholas Dronen, Calvin McCarter, Sina Moeini, Ali Kebarighotbi
https://arxiv.org/abs/2404.04221

How Lexical is Bilingual Lexicon Induction?
In contemporary machine learning approaches to bilingual lexicon induction (BLI), a model learns a mapping between the embedding spaces of a language pair. Recently, retrieve-and-rank approach to BLI has achieved state of the art results on the task. However, the problem remains challenging in low-resource settings, due to the paucity of data. The task is complicated by factors such as lexical variation across languages. We argue that the incorporation of additional lexical information into the…

This https://arxiv.org/abs/2312.11615 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Universal structure of measurement-induced information in many-body ground states
Unlike unitary dynamics, measurements of a subsystem can induce long-range entanglement via quantum teleportation. The amount of measurement-induced entanglement or mutual information depends jointly on the measurement basis and the entanglement structure of the state (before measurement), and has operational significance for whether the state is a resource for measurement-based quantum computing, as well as for the computational complexity of simulating the state using quantum or classical com…

Neural network prediction of model parameters for strong lensing samples from Hyper Suprime-Cam Survey
Priyanka Gawade, Anupreeta More, Surhud More, Akisato Kimura, Alessandro Sonnenfeld, Masamune Oguri, Naoki Yoshida
https://arxiv.org/abs/2404.18897

Neural network prediction of model parameters for strong lensing samples from Hyper Suprime-Cam Survey
Galaxies that cause the strong gravitational lensing of background galaxies provide us crucial information about the distribution of matter around them. Traditional modelling methods that analyse such strong lenses are both time and resource consuming, require sophisticated lensing codes and modelling expertise. To study the large lens population expected from imaging surveys such as LSST, we need fast and automated analysis methods. In this work, we build and train a simple convolutional neura…

Improved Methods of Task Assignment and Resource Allocation with Preemption in Edge Computing Systems
Caroline Rublein, Fidan Mehmeti, Mark Mahon, Thomas F. La Porta
https://arxiv.org/abs/2403.15665

Improved Methods of Task Assignment and Resource Allocation with Preemption in Edge Computing Systems
Edge computing has become a very popular service that enables mobile devices to run complex tasks with the help of network-based computing resources. However, edge clouds are often resource-constrained, which makes resource allocation a challenging issue. In addition, edge cloud servers must make allocation decisions with only limited information available, since the arrival of future client tasks might be impossible to predict, and the states and behavior of neighboring servers might be obscur…

Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction
Xingyu Xu, Yuejie Chi
https://arxiv.org/abs/2403.17042 http…

Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction
In a great number of tasks in science and engineering, the goal is to infer an unknown image from a small number of measurements collected from a known forward model describing certain sensing or imaging modality. Due to resource constraints, this task is often extremely ill-posed, which necessitates the adoption of expressive prior information to regularize the solution space. Score-based diffusion models, due to its impressive empirical success, have emerged as an appealing candidate of an ex…

This https://arxiv.org/abs/2401.07644 has been replaced.
link: https://scholar.google.com/scholar?q=a

Resource Allocation in STAR-RIS-Aided SWIPT with RSMA via Meta-Learning
Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is a cutting-edge concept for the sixth-generation (6G) wireless networks. In this paper, we propose a novel system that incorporates STAR-RIS with simultaneous wireless information and power transfer (SWIPT) using rate splitting multiple access (RSMA). The proposed system facilitates communication from a multi-antenna base station (BS) to single-antenna users in a downlink transmission. The BS concurrently…

This https://arxiv.org/abs/2311.02658 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Nonparametric Estimation and Comparison of Distance Distributions from Censored Data
Transportation distance information is a powerful resource, but location records are often censored due to privacy concerns or regulatory mandates. We outline methods to approximate, sample from, and compare distributions of distances between censored location pairs, a task with applications to public health informatics, logistics, and more. We validate empirically via simulation and demonstrate applicability to practical geospatial data analysis tasks.

Improved Methods of Task Assignment and Resource Allocation with Preemption in Edge Computing Systems
Caroline Rublein, Fidan Mehmeti, Mark Mahon, Thomas F. La Porta
https://arxiv.org/abs/2403.15665

Improved Methods of Task Assignment and Resource Allocation with Preemption in Edge Computing Systems
Edge computing has become a very popular service that enables mobile devices to run complex tasks with the help of network-based computing resources. However, edge clouds are often resource-constrained, which makes resource allocation a challenging issue. In addition, edge cloud servers must make allocation decisions with only limited information available, since the arrival of future client tasks might be impossible to predict, and the states and behavior of neighboring servers might be obscur…

Mitigating Collisions in Sidelink NR V2X: A Study on Cooperative Resource Allocation
Mohammadsaleh Nikooroo, Juan Estrada-Jimenez, Aurel Machalek, Jerome Harri, Thomas Engel, Ion Turcanu
https://arxiv.org/abs/2404.17532

Mitigating Collisions in Sidelink NR V2X: A Study on Cooperative Resource Allocation
New Radio (NR) Vehicle-to-Everything (V2X) Sidelink (SL), an integral part of the 5G NR standard, is expected to revolutionize the automotive and rail industries by enabling direct and low-latency exchange of critical information between traffic participants independently of cellular networks. However, this advancement depends primarily on efficient SL resource allocation. Mode 2(a) is a well-known method for this purpose, where each node autonomously selects resources. However, this method is …

Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource Limitations
Gregor Donabauer, Udo Kruschwitz
https://arxiv.org/abs/2402.18179

Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource Limitations
Pre-training of neural networks has recently revolutionized the field of Natural Language Processing (NLP) and has before demonstrated its effectiveness in computer vision. At the same time, advances around the detection of fake news were mainly driven by the context-based paradigm, where different types of signals (e.g. from social media) form graph-like structures that hold contextual information apart from the news article to classify. We propose to merge these two developments by applying p…

Transactive Local Energy Markets Enable Community-Level Resource Coordination Using Individual Rewards
Daniel C. May, Petr Musilek
https://arxiv.org/abs/2403.15617

Transactive Local Energy Markets Enable Community-Level Resource Coordination Using Individual Rewards
ALEX (Autonomous Local Energy eXchange) is an economy-driven, transactive local energy market where each participating building is represented by a rational agent. Relying solely on building-level information, this agent minimizes its electricity bill by automating distributed energy resource utilization and trading. This study examines ALEX's capabilities to align participant and grid-stakeholder interests and assesses ALEX's impact on short- and long-term intermittence using a set of communit…

This https://arxiv.org/abs/2310.09321 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Robustness- and weight-based resource measures without convexity restriction: Multicopy witness and operational advantage in static and dynamical quantum resource theories
Quantum resource theories (QRTs) provide a unified framework to analyze quantum properties as resources for achieving advantages in quantum information processing. The generalized robustness and the weight of resource have been gaining increasing attention as useful resource quantifiers. However, the existing analyses of these measures were restricted to the cases where convexity of the set of free states is assumed, and physically motivated resources do not necessarily satisfy this restriction…

This https://arxiv.org/abs/2307.01057 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Robust Beamforming Design for Fairness-Aware Energy Efficiency Maximization in RIS-Assisted mmWave Communications
Users in millimeter-wave (mmWave) systems often exhibit diverse channel strengths, which can negatively impact user fairness in resource allocation. Moreover, exact channel state information (CSI) may not be available at the transmitter, rendering suboptimal resource allocation. In this paper, we address these issues within the context of energy efficiency maximization in RIS-assisted mmWave systems. We first derive a tractable lower bound on the achievable sum rate, taking into account CSI err…

Utilizing Large Language Models to Identify Reddit Users Considering Vaping Cessation for Digital Interventions
Sai Krishna Revanth Vuruma, Dezhi Wu, Saborny Sen Gupta, Lucas Aust, Valerie Lookingbill, Caleb Henry, Yang Ren, Erin Kasson, Li-Shiun Chen, Patricia Cavazos-Rehg, Dian Hu, Ming Huang
https://arxiv.org/abs/2404.17607…

Utilizing Large Language Models to Identify Reddit Users Considering Vaping Cessation for Digital Interventions
The widespread adoption of social media platforms globally not only enhances users' connectivity and communication but also emerges as a vital channel for the dissemination of health-related information, thereby establishing social media data as an invaluable organic data resource for public health research. The surge in popularity of vaping or e-cigarette use in the United States and other countries has caused an outbreak of e-cigarette and vaping use-associated lung injury (EVALI), leading to…

This https://arxiv.org/abs/2401.16414 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Causal Model for Quantifying Multipartite Classical and Quantum Correlations
We give an operational definition of information-theoretic resources within a given multipartite classical or quantum correlation. We present our causal model that serves as the source coding side of this correlation and introduce a novel concept of resource rate. We argue that, beyond classical secrecy, additional resources exist that are useful for the security of distributed computing problems, which can be captured by the resource rate. Furthermore, we establish a relationship between resou…

S\~onajaht: Definition Embeddings and Semantic Search for Reverse Dictionary Creation
Aleksei Dorkin, Kairit Sirts
https://arxiv.org/abs/2404.19430 https://arxiv.org/pdf/2404.19430
arXiv:2404.19430v1 Announce Type: new
Abstract: We present an information retrieval based reverse dictionary system using modern pre-trained language models and approximate nearest neighbors search algorithms. The proposed approach is applied to an existing Estonian language lexicon resource, S\~onaveeb (word web), with the purpose of enhancing and enriching it by introducing cross-lingual reverse dictionary functionality powered by semantic search.
The performance of the system is evaluated using both an existing labeled English dataset of words and definitions that is extended to contain also Estonian and Russian translations, and a novel unlabeled evaluation approach that extracts the evaluation data from the lexicon resource itself using synonymy relations.
Evaluation results indicate that the information retrieval based semantic search approach without any model training is feasible, producing median rank of 1 in the monolingual setting and median rank of 2 in the cross-lingual setting using the unlabeled evaluation approach, with models trained for cross-lingual retrieval and including Estonian in their training data showing superior performance in our particular task.

This https://arxiv.org/abs/2403.18790 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Squeezing below the ground state of motion of a continuously monitored levitating nanoparticle
Squeezing is a crucial resource for quantum information processing and quantum sensing. In levitated nanomechanics, squeezed states of motion can be generated via temporal control of the trapping frequency of a massive particle. However, the amount of achievable squeezing typically suffers from detrimental environmental effects. We analyze the performance of a scheme that, by embedding careful time-control of trapping potentials and fully accounting for the most relevant sources of noise -- inc…

Deciphering the Digital Veil: Exploring the Ecosystem of DNS HTTPS Resource Records
Hongying Dong (University of Virginia), Yizhe Zhang (University of Virginia), Hyeonmin Lee (University of Virginia), Shumon Huque (Salesforce), Yixin Sun (University of Virginia)
https://arxiv.org/abs/2403.15672

Deciphering the Digital Veil: Exploring the Ecosystem of DNS HTTPS Resource Records
The DNS HTTPS resource record is a new DNS record type designed for the delivery of configuration information and parameters required to initiate connections to HTTPS network services. It provides the ability to perform zone apex redirection to a third-party provider, which the existing CNAME record cannot do. In addition, it is a key enabler for TLS Encrypted ClientHello (ECH) by providing the cryptographic keying material needed to encrypt the initial exchange. To understand the adoption and …

This https://arxiv.org/abs/2402.08819 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Infinite-horizon optimal scheduling for feedback control
Emerging cyber-physical systems impel the development of communication protocols to efficiently utilize resources. This paper investigates the optimal co-design of control and scheduling in networked control systems. The objective is to co-design the control law and the scheduling mechanism that jointly optimize the tradeoff between regulation performance and communication resource consumption in the long run. The concept of the value of information (VoI) is employed to evaluate the importance …

Graph Neural Networks for Wireless Networks: Graph Representation, Architecture and Evaluation
Yang Lu, Yuhang Li, Ruichen Zhang, Wei Chen, Bo Ai, Dusit Niyato
https://arxiv.org/abs/2404.11858

Graph Neural Networks for Wireless Networks: Graph Representation, Architecture and Evaluation
Graph neural networks (GNNs) have been regarded as the basic model to facilitate deep learning (DL) to revolutionize resource allocation in wireless networks. GNN-based models are shown to be able to learn the structural information about graphs representing the wireless networks to adapt to the time-varying channel state information and dynamics of network topology. This article aims to provide a comprehensive overview of applying GNNs to optimize wireless networks via answering three fundamen…

This https://arxiv.org/abs/2404.14217 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

General protocols for the efficient distillation of indistinguishable photons
Highly pure and indistinguishable photons are a prerequisite for use in quantum information processing. We introduce protocols for the distillation of indistinguishable photons that offer a significant improvement over previous work, reducing distinguishability error rates by a factor of $n$, with resource requirements scaling linearly in $n$. We present the protocols, based on the discrete Fourier transform, Hadamard (Sylvester) matrices, and more general Fourier transforms on finite abelian g…

Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping
Shubhra Aich, Wenshan Wang, Parv Maheshwari, Matthew Sivaprakasam, Samuel Triest, Cherie Ho, Jason M. Gregory, John G. Rogers III, Sebastian Scherer
https://arxiv.org/abs/2403.11876

Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping
The limited sensing resolution of resource-constrained off-road vehicles poses significant challenges towards reliable off-road autonomy. To overcome this limitation, we propose a general framework based on fusing the future information (i.e. future fusion) for self-supervision. Recent approaches exploit this future information alongside the hand-crafted heuristics to directly supervise the targeted downstream tasks (e.g. traversability estimation). However, in this paper, we opt for a more gen…

This https://arxiv.org/abs/2205.02422 has been replaced.
link: https://scholar.google.com/scholar?q=a

Quantum Semantic Communications for Resource-Efficient Quantum Networking
Quantum communication networks (QCNs) utilize quantum mechanics for secure information transmission, but the reliance on fragile and expensive photonic quantum resources renders QCN resource optimization challenging. Unlike prior QCN works that relied on blindly compressing direct quantum embeddings of classical data, this letter proposes a novel quantum semantic communications (QSC) framework exploiting advancements in quantum machine learning and quantum semantic representations to extracts a…

Universal Auto-encoder Framework for MIMO CSI Feedback
Jinhyun So, Hyukjoon Kwon
https://arxiv.org/abs/2403.00299 https://arxiv.org/p…

Universal Auto-encoder Framework for MIMO CSI Feedback
Existing auto-encoder (AE)-based channel state information (CSI) frameworks have focused on a specific configuration of user equipment (UE) and base station (BS), and thus the input and output sizes of the AE are fixed. However, in the real-world scenario, the input and output sizes may vary depending on the number of antennas of the BS and UE and the allocated resource block in the frequency dimension. A naive approach to support the different input and output sizes is to use multiple AE model…

Cleaner Pretraining Corpus Curation with Neural Web Scraping
Zhipeng Xu, Zhenghao Liu, Yukun Yan, Zhiyuan Liu, Chenyan Xiong, Ge Yu
https://arxiv.org/abs/2402.14652

Cleaner Pretraining Corpus Curation with Neural Web Scraping
The web contains large-scale, diverse, and abundant information to satisfy the information-seeking needs of humans. Through meticulous data collection, preprocessing, and curation, webpages can be used as a fundamental data resource for language model pretraining. However, when confronted with the progressively revolutionized and intricate nature of webpages, rule-based/feature-based web scrapers are becoming increasingly inadequate. This paper presents a simple, fast, and effective Neural web …

Mobile Edge Computing
Sohaib Ahmed, Hassan Khalid, Muhammad Hamza, Danyal Farhat
https://arxiv.org/abs/2404.17944 https://arxiv.org/p…

Mobile Edge Computing
Mobile Edge Computing (MEC) has emerged as a solution to the high latency and suboptimal Quality of Experience (QoE) associated with Mobile Cloud Computing (MCC). By processing data near the source, MEC reduces the need to send information to distant data centers, resulting in faster response times and lower latency. This paper explores the differences between MEC and traditional cloud computing, emphasizing architecture, data flow, and resource allocation. Key technologies like Network Functio…

Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping
Shubhra Aich, Wenshan Wang, Parv Maheshwari, Matthew Sivaprakasam, Samuel Triest, Cherie Ho, Jason M. Gregory, John G. Rogers III, Sebastian Scherer
https://arxiv.org/abs/2403.11876

Deep Bayesian Future Fusion for Self-Supervised, High-Resolution, Off-Road Mapping
The limited sensing resolution of resource-constrained off-road vehicles poses significant challenges towards reliable off-road autonomy. To overcome this limitation, we propose a general framework based on fusing the future information (i.e. future fusion) for self-supervision. Recent approaches exploit this future information alongside the hand-crafted heuristics to directly supervise the targeted downstream tasks (e.g. traversability estimation). However, in this paper, we opt for a more gen…

This https://arxiv.org/abs/2312.02184 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

Channel-Feedback-Free Transmission for Downlink FD-RAN: A Radio Map based Complex-valued Precoding Network Approach
As the demand for high-quality services proliferates, an innovative network architecture, the fully-decoupled RAN (FD-RAN), has emerged for more flexible spectrum resource utilization and lower network costs. However, with the decoupling of uplink base stations and downlink base stations in FD-RAN, the traditional transmission mechanism, which relies on real-time channel feedback, is not suitable as the receiver is not able to feedback accurate and timely channel state information to the transm…

This https://arxiv.org/abs/2306.16261 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

SE-PQA: Personalized Community Question Answering
Personalization in Information Retrieval is a topic studied for a long time. Nevertheless, there is still a lack of high-quality, real-world datasets to conduct large-scale experiments and evaluate models for personalized search. This paper contributes to filling this gap by introducing SE-PQA (StackExchange - Personalized Question Answering), a new curated resource to design and evaluate personalized models related to the task of community Question Answering (cQA). The contributed dataset incl…

Multi-Agent Hybrid SAC for Joint SS-DSA in CRNs
David R. Nickel, Anindya Bijoy Das, David J. Love, Christopher G. Brinton
https://arxiv.org/abs/2404.14319 …

Multi-Agent Hybrid SAC for Joint SS-DSA in CRNs
Opportunistic spectrum access has the potential to increase the efficiency of spectrum utilization in cognitive radio networks (CRNs). In CRNs, both spectrum sensing and resource allocation (SSRA) are critical to maximizing system throughput while minimizing collisions of secondary users with the primary network. However, many works in dynamic spectrum access do not consider the impact of imperfect sensing information such as mis-detected channels, which the additional information available in …

This https://arxiv.org/abs/2402.16261 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrieval
Conversational retrieval refers to an information retrieval system that operates in an iterative and interactive manner, requiring the retrieval of various external resources, such as persona, knowledge, and even response, to effectively engage with the user and successfully complete the dialogue. However, most previous work trained independent retrievers for each specific resource, resulting in sub-optimal performance and low efficiency. Thus, we propose a multi-task framework function as a un…

This https://arxiv.org/abs/2403.09514 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Quantum Fourier Transform using Dynamic Circuits
In dynamic quantum circuits, classical information from mid-circuit measurements is fed forward during circuit execution. This emerging capability of quantum computers confers numerous advantages that can enable more efficient and powerful protocols by drastically reducing the resource requirements for certain core algorithmic primitives. In particular, in the case of the $n$-qubit quantum Fourier transform followed immediately by measurement, the scaling of resource requirements is reduced fro…

This https://arxiv.org/abs/2312.17628 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Joint User Scheduling, Power Allocation, and Rate Control for MC-RSMA in URLLC Services
This paper investigates the resource management problem in multi-carrier rate-splitting multiple access (MC-RSMA) systems with imperfect channel state information (CSI) and successive interference cancellation (SIC) for ultra-reliable and low-latency communications (URLLC) applications. To explore the trade-off between the decoding error probability and achievable rate, effective throughput (ET) is adopted as the utility function in this study. Then, a mixed-integer non-convex problem is formul…

Image Generative Semantic Communication with Multi-Modal Similarity Estimation for Resource-Limited Networks
Eri Hosonuma, Taku Yamazaki, Takumi Miyoshi, Akihito Taya, Yuuki Nishiyama, Kaoru Sezaki
https://arxiv.org/abs/2404.11280

Image Generative Semantic Communication with Multi-Modal Similarity Estimation for Resource-Limited Networks
To reduce network traffic and support environments with limited resources, a method for transmitting images with low amounts of transmission data is required. Machine learning-based image compression methods, which compress the data size of images while maintaining their features, have been proposed. However, in certain situations, reconstructing a part of semantic information of images at the receiver end may be sufficient. To realize this concept, semantic-information-based communication, cal…

This https://arxiv.org/abs/2304.05880 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Secure Key from Quantum Discord
The study of quantum information processing seeks to characterize the resources that enable quantum information processing to perform tasks that are unfeasible or inefficient for classical information processing. Quantum cryptography is one such task, and researchers have identified entanglement as a sufficient resource for secure key generation. However, quantum discord, another type of quantum correlation beyond entanglement, has been found to be necessary for guaranteeing secure communicatio…

This https://arxiv.org/abs/2402.16328 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

A Joint Communication and Computation Design for Probabilistic Semantic Communications
In this paper, the problem of joint transmission and computation resource allocation for a multi-user probabilistic semantic communication (PSC) network is investigated. In the considered model, users employ semantic information extraction techniques to compress their large-sized data before transmitting them to a multi-antenna base station (BS). Our model represents large-sized data through substantial knowledge graphs, utilizing shared probability graphs between the users and the BS for effic…

This https://arxiv.org/abs/2403.14811 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Analysis of optical loss thresholds in the fusion-based quantum computing architecture
Bell state measurements (BSM) play a significant role in quantum information and quantum computing, in particular, in fusion-based quantum computing (FBQC). The FBQC model is a framework for universal quantum computing provided that we are able to perform entangling measurements, called fusions, on qubits within small entangled resource states. Here we analyse the usage of different linear-optical BSM circuits as fusions in the FBQC schemes and numerically evaluate hardware requirements for fau…

This https://arxiv.org/abs/2401.07644 has been replaced.
link: https://scholar.google.com/scholar?q=a

Resource Allocation in STAR-RIS-Aided SWIPT with RSMA via Meta-Learning
Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is a cutting-edge concept for the sixth-generation (6G) wireless networks. In this letter, we propose a novel system that incorporates STAR-RIS with simultaneous wireless information and power transfer (SWIPT) using rate splitting multiple access (RSMA). The proposed system facilitates communication from a multi-antenna base station (BS) to single-antenna users in a downlink transmission. The BS concurrentl…

This https://arxiv.org/abs/2403.10564 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

All incompatible measurements on qubits lead to multiparticle Bell nonlocality
Bell nonlocality is a fundamental phenomenon of quantum physics as well as an essential resource for various tasks in quantum information processing. It is known that for the observation of nonlocality the measurements on a quantum system have to be incompatible, but the question which incompatible measurements are useful, remained open. Here we prove that any set of incompatible measurements on qubits leads to a violation of a suitable Bell inequality in a multiparticle scenario, where all par…

This https://arxiv.org/abs/2401.16414 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Causal Model for Quantifying Multipartite Classical and Quantum Correlations
We give an operational definition of information-theoretic resources within a given multipartite classical or quantum correlation. We present our causal model that serves as the source coding side of this correlation and introduce a novel concept of resource rate. We argue that, beyond classical secrecy, additional resources exist that are useful for the security of distributed computing problems, which can be captured by the resource rate. Furthermore, we establish a relationship between resou…

Multi-qubit gates and 'Schr\"odinger cat' states in an optical clock
Alec Cao, William J. Eckner, Theodor Lukin Yelin, Aaron W. Young, Sven Jandura, Lingfeng Yan, Kyungtae Kim, Guido Pupillo, Jun Ye, Nelson Darkwah Oppong, Adam M. Kaufman
https://arxiv.org/abs/2402.16289

Multi-qubit gates and 'Schrödinger cat' states in an optical clock
Many-particle entanglement is a key resource for achieving the fundamental precision limits of a quantum sensor. Optical atomic clocks, the current state-of-the-art in frequency precision, are a rapidly emerging area of focus for entanglement-enhanced metrology. Augmenting tweezer-based clocks featuring microscopic control and detection with the high-fidelity entangling gates developed for atom-array information processing offers a promising route towards leveraging highly entangled quantum sta…

Multi-qubit gates and 'Schr\"odinger cat' states in an optical clock
Alec Cao, William J. Eckner, Theodor Lukin Yelin, Aaron W. Young, Sven Jandura, Lingfeng Yan, Kyungtae Kim, Guido Pupillo, Jun Ye, Nelson Darkwah Oppong, Adam M. Kaufman
https://arxiv.org/abs/2402.16289

Multi-qubit gates and 'Schrödinger cat' states in an optical clock
Many-particle entanglement is a key resource for achieving the fundamental precision limits of a quantum sensor. Optical atomic clocks, the current state-of-the-art in frequency precision, are a rapidly emerging area of focus for entanglement-enhanced metrology. Augmenting tweezer-based clocks featuring microscopic control and detection with the high-fidelity entangling gates developed for atom-array information processing offers a promising route towards leveraging highly entangled quantum sta…

Semantic Extraction Model Selection for IoT Devices in Edge-assisted Semantic Communications
Hong Chen, Fang Fang, Xianbin Wang
https://arxiv.org/abs/2403.10537

Semantic Extraction Model Selection for IoT Devices in Edge-assisted Semantic Communications
Semantic communications offer the potential to alleviate communication loads by exchanging meaningful information. However, semantic extraction (SE) is computationally intensive, posing challenges for resource-constrained Internet of Things (IoT) devices. To address this, leveraging computing resources at the edge servers (ESs) is essential. ESs can support multiple SE models for various tasks, making it crucial to select appropriate SE models based on diverse requirements of IoT devices and li…

Semantic Extraction Model Selection for IoT Devices in Edge-assisted Semantic Communications
Hong Chen, Fang Fang, Xianbin Wang
https://arxiv.org/abs/2403.10537

Semantic Extraction Model Selection for IoT Devices in Edge-assisted Semantic Communications
Semantic communications offer the potential to alleviate communication loads by exchanging meaningful information. However, semantic extraction (SE) is computationally intensive, posing challenges for resource-constrained Internet of Things (IoT) devices. To address this, leveraging computing resources at the edge servers (ESs) is essential. ESs can support multiple SE models for various tasks, making it crucial to select appropriate SE models based on diverse requirements of IoT devices and li…

This https://arxiv.org/abs/2403.10564 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

All incompatible measurements on qubits lead to multiparticle Bell nonlocality
Bell nonlocality is a fundamental phenomenon of quantum physics as well as an essential resource for various tasks in quantum information processing. It is known that for the observation of nonlocality the measurements on a quantum system have to be incompatible, but the question which incompatible measurements are useful, remained open. Here we prove that any set of incompatible measurements on qubits leads to a violation of a suitable Bell inequality in a multiparticle scenario, where all par…

This https://arxiv.org/abs/2309.01181 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Polarization-entangled quantum frequency comb from a silicon nitride microring resonator
Integrated microresonator facilitates the realization of quantum frequency comb (QFC), which provides a large number of discrete frequency modes with broadband spectral range and narrow linewidth. However, all previous demonstrations have focused on the generation of energy-time or time-bin entangled photons from QFC. Realizing polarization-entangled quantum frequency comb, which is the important resource for fundamental study of quantum mechanics and quantum information applications, remains c…

This https://arxiv.org/abs/2309.01181 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Polarization-entangled quantum frequency comb from a silicon nitride microring resonator
Integrated microresonator facilitates the realization of quantum frequency comb (QFC), which provides a large number of discrete frequency modes with broadband spectral range and narrow linewidth. However, all previous demonstrations have focused on the generation of energy-time or time-bin entangled photons from QFC. Realizing polarization-entangled quantum frequency comb, which is the important resource for fundamental study of quantum mechanics and quantum information applications, remains c…

Fusion of deterministically generated photonic graph states
Philip Thomas, Leonardo Ruscio, Olivier Morin, Gerhard Rempe
https://arxiv.org/abs/2403.11950 h…

Fusion of deterministically generated photonic graph states
Entanglement has evolved from an enigmatic concept of quantum physics to a key ingredient of quantum technology. It explains correlations between measurement outcomes that contradict classical physics, and has been widely explored with small sets of individual qubits. Multi-partite entangled states build up in gate-based quantum-computing protocols, and $\unicode{x2013}$ from a broader perspective $\unicode{x2013}$ were proposed as the main resource for measurement-based quantum-information pro…