Tootfinder

Turning to Online Forums for Legal Information: A Case Study of GDPR's Legitimate Interests
Lin Kyi, Cristiana Santos, Sushil Ammanaghatta Shivakumar, Franziska Roesner, Asia Biega
https://arxiv.org/abs/2506.04260

Turning to Online Forums for Legal Information: A Case Study of GDPR's Legitimate Interests
Practitioners building online services and tools often turn to online forums such as Reddit, Law Stack Exchange, and Stack Overflow for legal guidance to ensure compliance with the GDPR. The legal information presented in these forums directly impact present-day industry practitioner's decisions. Online forums can serve as gateways that, depending on the accuracy and quality of the answers provided, may either support or undermine the protection of privacy and data protection fundamental rights…

Current State in Privacy-Preserving Text Preprocessing for Domain-Agnostic NLP
Abhirup Sinha, Pritilata Saha, Tithi Saha
https://arxiv.org/abs/2508.03204 https://

Current State in Privacy-Preserving Text Preprocessing for Domain-Agnostic NLP
Privacy is a fundamental human right. Data privacy is protected by different regulations, such as GDPR. However, modern large language models require a huge amount of data to learn linguistic variations, and the data often contains private information. Research has shown that it is possible to extract private information from such language models. Thus, anonymizing such private and sensitive information is of utmost importance. While complete anonymization may not be possible, a number of diffe…

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Andrea Munari, Cedomir Stefanovic
https://arxiv.org/abs/2506.04793

On the Role of Early-Termination for Age of Information in Tree-Based Random Access Protocols
Age of Information (AoI) has emerged as a key metric for assessing data freshness in IoT applications, where a large number of devices report time-stamped updates to a monitor. Such systems often rely on random access protocols based on variations of ALOHA at the link layer, where collision resolution algorithms play a fundamental role to enable reliable delivery of packets. In this context, we provide the first analytical characterization of average AoI for the classical Capetanakis tree-based…

Decomposing Words for Enhanced Compression: Exploring the Number of Runs in the Extended Burrows-Wheeler Transform
Florian Ingels, Ana\"is Denis, Bastien Cazaux
https://arxiv.org/abs/2506.04926

Decomposing Words for Enhanced Compression: Exploring the Number of Runs in the Extended Burrows-Wheeler Transform
The Burrows-Wheeler Transform (BWT) is a fundamental component in many data structures for text indexing and compression, widely used in areas such as bioinformatics and information retrieval. The extended BWT (eBWT) generalizes the classical BWT to multisets of strings, providing a flexible framework that captures many BWT-like constructions. Several known variants of the BWT can be viewed as instances of the eBWT applied to specific decompositions of a word. A central property of the BWT, ess…

Product-State Manifolds for M Quantum Systems with N Levels using the Fano form and the Induced Euclidean Metric
Fotios D. Oikonomou
https://arxiv.org/abs/2509.02891 https://

Product-State Manifolds for M Quantum Systems with N Levels using the Fano form and the Induced Euclidean Metric
In quantum mechanics separable states can be characterized as convex combinations of product states whereas non-separable states exhibit entanglement. Quantum entanglement has played a pivotal role in both theoretical investigations and practical applications within quantum information science. In this study, we explore the connection between product states and geometric structures, specifically manifolds and their associated geometric properties such as the first fundamental form (metric). We …

Token Communication in the Era of Large Models: An Information Bottleneck-Based Approach
Hao Wei, Wanli Ni, Wen Wang, Wenjun Xu, Dusit Niyato, Ping Zhang
https://arxiv.org/abs/2507.01728

Token Communication in the Era of Large Models: An Information Bottleneck-Based Approach
This letter proposes UniToCom, a unified token communication paradigm that treats tokens as the fundamental units for both processing and wireless transmission. Specifically, to enable efficient token representations, we propose a generative information bottleneck (GenIB) principle, which facilitates the learning of tokens that preserve essential information while supporting reliable generation across multiple modalities. By doing this, GenIB-based tokenization is conducive to improving the com…

Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI
Dilruk Perera, Gousia Habib, Qianyi Xu, Daniel J. Tan, Kai He, Erik Cambria, Mengling Feng
https://arxiv.org/abs/2508.21101

Beyond Prediction: Reinforcement Learning as the Defining Leap in Healthcare AI
Reinforcement learning (RL) marks a fundamental shift in how artificial intelligence is applied in healthcare. Instead of merely predicting outcomes, RL actively decides interventions with long term goals. Unlike traditional models that operate on fixed associations, RL systems learn through trial, feedback, and long-term reward optimization, introducing transformative possibilities and new risks. From an information fusion lens, healthcare RL typically integrates multi-source signals such as v…

Optimising finite-time quantum information engines using Pareto bounds
Rasmus Hagman, Jonas Berx, Janine Splettstoesser, Henning Kirchberg
https://arxiv.org/abs/2507.00712

Optimising finite-time quantum information engines using Pareto bounds
Information engines harness measurement and feedback to convert energy into useful work. In this study, we investigate the fundamental trade-offs between ergotropic output power, thermodynamic efficiency and information-to-work conversion efficiency in such engines, explicitly accounting for the finite time required for measurement. As a model engine, we consider a two-level quantum system from which work is extracted via a temporarily coupled quantum harmonic oscillator that serves as the meas…

Towards a fundamental theory of modeling discrete systems
Peter Fettke, Wolfgang Reisig
https://arxiv.org/abs/2508.19803 https://arxiv.org/pdf/2508.19803…

Towards a fundamental theory of modeling discrete systems
Modeling is a central concern in both science and engineering. However, we need a new fundamental theory to address the challenges of the digital age. In this paper, we first explain why modeling is fundamental and which challenges must be addressed in the digital world. As a main contribution, we introduce the Heraklit modeling framework as a new approach to modeling. We conclude with some general remarks. Future work will involve the correctness of modeling, the notion of information, and the…

Algorithm for computing the partition function of the Potts model for SP-graphs
Sofya Mukhamedzhanova, Bulat Sabirov, Amir Mukhamedzhanov
https://arxiv.org/abs/2507.22579 https:…

Algorithm for computing the partition function of the Potts model for SP-graphs
The q-state Potts model is a fundamental framework in statistical physics and graph theory, with its partition function encoding rich information about spin configurations. The multivariate Tutte polynomial (known as the partition function of the Potts model) can be defined on an arbitrary finite graph $G$ and encodes a lot of important combinatorial information about the graph. As a special case, it contains the familiar Tutte polynomial with two variables and, consequently, its specialization…

Fractional Shapiro steps in a Cavity-Coupled Josephson ring condensate
Nalinikanta Pradhan, Rina Kanamoto, M. Bhattacharya, Pankaj Kumar Mishra
https://arxiv.org/abs/2507.01188

Fractional Shapiro steps in a Cavity-Coupled Josephson ring condensate
The Josephson effect presents a fundamental example of macroscopic quantum coherence as well as a crucial enabler for metrology (e.g. voltage standard), sensing (e.g. Superconducting Quantum Interference Device) and quantum information processing (Josephson qubits). Recently, there has been a major renewal of interest in the effect, following its observation in Bose, Fermi, and dipolar atomic condensates, in exciton-polariton condensates, and in momentum space. We present theoretically a nondes…

New Bounds for Linear Codes with Applications
Liren Lin, Guanghui Zhang, Bocong Chen, Hongwei Liu
https://arxiv.org/abs/2509.03337 https://arxiv.org/pdf/25…

New Bounds for Linear Codes with Applications
Bounds on linear codes play a central role in coding theory, as they capture the fundamental trade-off between error-correction capability (minimum distance) and information rate (dimension relative to length). Classical results characterize this trade-off solely in terms of the parameters $n$, $k$, $d$ and $q$. In this work we derive new bounds under the additional assumption that the code contains a nonzero codeword of weight $w$.By combining residual-code techniques with classical results su…

A survey of multi-agent geosimulation methodologies: from ABM to LLM
Virginia Padilla, Jacinto D\'avila
https://arxiv.org/abs/2507.23694 https://arxiv.…

A survey of multi-agent geosimulation methodologies: from ABM to LLM
We provide a comprehensive examination of agent-based approaches that codify the principles and linkages underlying multi-agent systems, simulations, and information systems. Based on two decades of study, this paper confirms a framework intended as a formal specification for geosimulation platforms. Our findings show that large language models (LLMs) can be effectively incorporated as agent components if they follow a structured architecture specific to fundamental agent activities such as per…

Community-Based Efficient Algorithms for User-Driven Competitive Influence Maximization in Social Networks
Rahul Kumar Gautam
https://arxiv.org/abs/2506.23179

Community-Based Efficient Algorithms for User-Driven Competitive Influence Maximization in Social Networks
Nowadays, people in the modern world communicate with their friends, relatives, and colleagues through the internet. Persons/nodes and communication/edges among them form a network. Social media networks are a type of network where people share their views with the community. There are several models that capture human behavior, such as a reaction to the information received from friends or relatives. The two fundamental models of information diffusion widely discussed in the social networks ar…

Entangling Power and Its Deviation: A Quantitative Analysis on Input-State Dependence and Variability in Entanglement Generation
Kyoungho Cho, Jeongho Bang
https://arxiv.org/abs/2508.00301

Entangling Power and Its Deviation: A Quantitative Analysis on Input-State Dependence and Variability in Entanglement Generation
Quantifying the entangling capability of quantum operations is a fundamental task in quantum information science. Traditionally, this capability is measured by the entangling power (EP), defined as the average entanglement generated when a quantum operation acts uniformly on all possible product states. However, EP alone cannot capture the intricate input-state-dependent nature of entanglement generation. To address this, we define a complementary metric -- entangling power deviation (EPD) -- a…

DIO: Refining Mutual Information and Causal Chain to Enhance Machine Abstract Reasoning Ability
Ruizhuo Song, Beiming Yuan
https://arxiv.org/abs/2508.15387 https://

DIO: Refining Mutual Information and Causal Chain to Enhance Machine Abstract Reasoning Ability
Despite the outstanding performance of current deep learning models across various domains, their fundamental bottleneck in abstract reasoning remains unresolved. To address this challenge, the academic community has introduced Raven's Progressive Matrices (RPM) problems as an authoritative benchmark for evaluating the abstract reasoning capabilities of deep learning algorithms, with a focus on core intelligence dimensions such as abstract reasoning, pattern recognition, and complex problem-sol…

Proposal for High-Dimensional Entanglement Swapping with Linear Optics and Ancillary Photons
Baghdasar Baghdasaryan, Kaushik Joarder, Fabian Steinlechner
https://arxiv.org/abs/2509.02817

Proposal for High-Dimensional Entanglement Swapping with Linear Optics and Ancillary Photons
Quantum teleportation and entanglement swapping are fundamental building blocks for realizing global quantum networks. Both protocols have been extensively studied and experimentally demonstrated using two-dimensional qubit systems. Their implementation in high-dimensional (HD) systems offers significant advantages, such as enhanced noise resilience, greater robustness against eavesdropping, and increased information capacity. Generally, HD photonic entanglement swapping requires ancilla photon…

Racing to Idle: Energy Efficiency of Matrix Multiplication on Heterogeneous CPU and GPU Architectures
Mufakir Qamar Ansari (Department of Electrical Engineering and Computer Science, The University of Toledo, Toledo, OH, USA), Mudabir Qamar Ansari (Department of School of Accounting and Information Systems, Lamar University, Beaumont, TX, USA)
https://

Racing to Idle: Energy Efficiency of Matrix Multiplication on Heterogeneous CPU and GPU Architectures
The paradigm shift towards multi-core and heterogeneous computing, driven by the fundamental power and thermal limits of single-core processors, has established energy efficiency as a first-class design constraint in high-performance computing (HPC). Heterogeneous systems, integrating traditional multi-core CPUs with specialized accelerators like discrete (dGPU) and integrated (iGPU) graphics processing units, offer a compelling path to navigating the trade-offs between performance and power. H…

EU's Frontex has published a children's book for children who are about to be deported
😲
https://op.europa.eu/en/publication-detail/-/publication/6eea0e99-e464-11ef-be2a-01aa75ed71a1
Official PDFs availabl…

Toolbox for children in return - Publications Office of the EU
Addressing the return of unaccompanied minors or children within families is a delicate matter that demands a humane approach. This approach must not only respect fundamental rights but also prioritise the child's best interests. Additionally, clear and comprehensive information about the return procedures is essential for those involved, enabling them to prepare as effectively as possible. One of the primary objectives of Frontex is to assist MS throughout all stages of the return procedures. …

The Goldbach Conjecture as an Informational Economy Principle: A Heuristic Framework from Computational Physics
Ricardo Adonis Caraccioli Abrego
https://arxiv.org/abs/2508.18273

The Goldbach Conjecture as an Informational Economy Principle: A Heuristic Framework from Computational Physics
This paper presents a heuristic framework for analyzing the Goldbach Conjecture (GC) from the perspective of the physics of information. Through empirical analysis, we propose an Informational Economy Principle (IEP), which posits that differences between prime numbers tend to be resolved by pairs with a minimal sum with over- whelmingly high probability. We argue that this tendency is analogous to least-action principles in physics and is consistent with the fundamental physical limits of comp…

The complexity of Ford domains of $\Gamma_0(N)$
Pengcheng Zhang
https://arxiv.org/abs/2508.18511 https://arxiv.org/pdf/2508.18511

The complexity of Ford domains of $Γ_0(N)$
For each integer $N>1$, we define a notion of complexity $c(N)$, which is a nonnegative integer and carries some information on the shape of the Ford fundamental domain of the congruence subgroup $Γ_0(N)$. The property that $c(N)=0$ first appeared as a technical assumption in a paper by Anke Pohl, which is closely related to a conjecture of Don Zagier on the "reduction theory" of $Γ_0(N)$. In this paper, we give a complete classification of integers $N>1$ with $c(N)=0$, and we also show that …

Sliding Engineering Spin-Valley-Layer Coupling and Altermagnetism in Bilayer Antiferromagnetic Honeycomb Lattices
Wen-Xin Jiang, Zhen-Hao Gong, Yuantao Chen, Zhigang Gui, Li Huang
https://arxiv.org/abs/2507.20690

Sliding Engineering Spin-Valley-Layer Coupling and Altermagnetism in Bilayer Antiferromagnetic Honeycomb Lattices
Valley polarization and altermagnetism are two emerging fundamental phenomena in condensed matter physics, offering unprecedented opportunites for information encoding and processing in novel energy-efficient devices. By coupling valley and spin degrees of freedom with ferroic orders such as ferroelectricity, nonvolatile memory functionalities can be achieved. Here, we propose a way to realize ferroelectric-valley (FE-valley) and FE-altermagnetic coupling in a bilayer antiferromagnetic (AFM) ho…

On the Virtues of Information Security in the UK Climate Movement
Mikaela Brough, Rikke Bjerg Jensen, Martin R. Albrecht
https://arxiv.org/abs/2506.09719 h…

On the Virtues of Information Security in the UK Climate Movement
We report on an ethnographic study with members of the climate movement in the United Kingdom (UK). We conducted participant observation and interviews at protests and in various activist settings. Reporting on the findings as they relate to information security, we show that members of the UK climate movement wrestled with (i) a fundamental tension between openness and secrecy; (ii) tensions between autonomy and collective interdependence in information-security decision-making; (iii) conflict…

From Representation to Mediation: A New Agenda for Conceptual Modeling Research in A Digital World
J. Recker, R. Lukyanenko, M. A. Jabbari, B. M. Samuel, A. Castellanos
https://arxiv.org/abs/2506.18743

From Representation to Mediation: A New Agenda for Conceptual Modeling Research in A Digital World
The role of information systems (IS) as representations of real-world systems is changing in an increasingly digitalized world, suggesting that conceptual modeling is losing its relevance to the IS field. We argue the opposite: Conceptual modeling research is more relevant to the IS field than ever, but it requires an update with current theory. We develop a new theoretical framework of conceptual modeling that delivers a fundamental shift in the assumptions that govern research in this area. T…

Directed Cycles as Higher-Order Units of Information Processing in Complex Networks
Hardik Rajpal, Paul Expert, Vaiva Vasiliauskaite
https://arxiv.org/abs/2508.09808 https://

Directed Cycles as Higher-Order Units of Information Processing in Complex Networks
Directed cycles form the fundamental motifs in natural, social and artificial networks, yet their distinct computational roles remain under-explored, particularly in the context of higher-order structure and function. In this work, we investigate how two types of directed cycles - feedforward and feedback - can act as higher-order structures to facilitate the flow and integration of information in sparse random networks, and how these roles depend on the environment of the cycles. Using informa…

Controlling the Flow of Information in Optical Metrology
Maximilian Weimar, Huanli Zhou, Luca Neubacher, Thomas A. Grant, Jakob H\"upfl, Kevin F. MacDonald, Stefan Rotter, Nikolay I. Zheludev
https://arxiv.org/abs/2508.13640

Controlling the Flow of Information in Optical Metrology
Optical metrology has progressed beyond the Abbe-Rayleigh limit, unlocking (sub)atomic precision by leveraging nonlinear phenomena, statistical accumulation, and AI-estimators trained on measurand variations. Here, we reveal that Fisher information, which defines the fundamental precision limit, can be viewed as a physical entity that propagates through space, and we derive the wave equation for sensitivity fields defining the flow of Fisher information, which can resonate, diffract, and interf…

Kullback-Leibler Divergence as a Measure of Irreversible Information Loss Near Black Hole Horizons
Tatsuaki Tsuruyama
https://arxiv.org/abs/2508.04348 https://

Kullback-Leibler Divergence as a Measure of Irreversible Information Loss Near Black Hole Horizons
We present a unified theoretical framework that integrates information theory, thermodynamics, and general relativity to analyze the fundamental limit of decoding time-encoded signals in curved spacetime. In particular, we introduce the Kullback-Leibler divergence (KLD) as a quantitative measure of the mismatch between the transmitted and received symbol distributions induced by gravitational time dilation. Using a minimal communication model, we derive the critical radius at which information …

From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems
Sawan Kumar, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
https://arxiv.org/abs/2506.15906

From Local Interactions to Global Operators: Scalable Gaussian Process Operator for Physical Systems
Operator learning offers a powerful paradigm for solving parametric partial differential equations (PDEs), but scaling probabilistic neural operators such as the recently proposed Gaussian Processes Operators (GPOs) to high-dimensional, data-intensive regimes remains a significant challenge. In this work, we introduce a novel, scalable GPO, which capitalizes on sparsity, locality, and structural information through judicious kernel design. Addressing the fundamental limitation of cubic computat…

RedMaPPer Cluster Properties from Two-Dimensional Lensing Shear Maps in the HSC-SSP Survey
Chenxu Cui, Xiangkun Liu, Huanyuan Shan, Ziwei Li, Zuhui Fan
https://arxiv.org/abs/2508.17042

RedMaPPer Cluster Properties from Two-Dimensional Lensing Shear Maps in the HSC-SSP Survey
Dark matter halos are fundamental cosmological structures whose properties-such as concentration, ellipticity, and mass centroid-encode information about their formation and evolution. Concentration traces collapse time and internal structure, while ellipticity and centroid offsets reflect halo shape and dynamical state. Accurate characterization of these properties improves mass estimates and tests dark matter models. Gravitational lensing, which directly probes projected mass distributions, p…

Rethinking the Privacy of Text Embeddings: A Reproducibility Study of "Text Embeddings Reveal (Almost) As Much As Text"
Dominykas Seputis, Yongkang Li, Karsten Langerak, Serghei Mihailov
https://arxiv.org/abs/2507.07700

Rethinking the Privacy of Text Embeddings: A Reproducibility Study of "Text Embeddings Reveal (Almost) As Much As Text"
Text embeddings are fundamental to many natural language processing (NLP) tasks, extensively applied in domains such as recommendation systems and information retrieval (IR). Traditionally, transmitting embeddings instead of raw text has been seen as privacy-preserving. However, recent methods such as Vec2Text challenge this assumption by demonstrating that controlled decoding can successfully reconstruct original texts from black-box embeddings. The unexpectedly strong results reported by Vec2…

QuMAB: Query-based Multi-annotator Behavior Pattern Learning
Liyun Zhang, Zheng Lian, Hong Liu, Takanori Takebe, Yuta Nakashima
https://arxiv.org/abs/2507.17653 https://

QuMAB: Query-based Multi-annotator Behavior Pattern Learning
Multi-annotator learning traditionally aggregates diverse annotations to approximate a single ground truth, treating disagreements as noise. However, this paradigm faces fundamental challenges: subjective tasks often lack absolute ground truth, and sparse annotation coverage makes aggregation statistically unreliable. We introduce a paradigm shift from sample-wise aggregation to annotator-wise behavior modeling. By treating annotator disagreements as valuable information rather than noise, mode…

Research Knowledge Graphs: the Shifting Paradigm of Scholarly Information Representation
Matth\"aus Zloch, Danilo Dess\`i, Jennifer D'Souza, Leyla Jael Castro, Benjamin Zapilko, Saurav Karmakar, Brigitte Mathiak, Markus Stocker, Wolfgang Otto, S\"oren Auer, Stefan Dietze
https://arxiv.org/abs/2506.07285

Research Knowledge Graphs: the Shifting Paradigm of Scholarly Information Representation
Sharing and reusing research artifacts, such as datasets, publications, or methods is a fundamental part of scientific activity, where heterogeneity of resources and metadata and the common practice of capturing information in unstructured publications pose crucial challenges. Reproducibility of research and finding state-of-the-art methods or data have become increasingly challenging. In this context, the concept of Research Knowledge Graphs (RKGs) has emerged, aiming at providing an easy to u…

The Democratic Paradox in Large Language Models' Underestimation of Press Freedom
I. Loaiza, R. Vestrelli, A. Fronzetti Colladon, R. Rigobon
https://arxiv.org/abs/2506.18045

The Democratic Paradox in Large Language Models' Underestimation of Press Freedom
As Large Language Models (LLMs) increasingly mediate global information access for millions of users worldwide, their alignment and biases have the potential to shape public understanding and trust in fundamental democratic institutions, such as press freedom. In this study, we uncover three systematic distortions in the way six popular LLMs evaluate press freedom in 180 countries compared to expert assessments of the World Press Freedom Index (WPFI). The six LLMs exhibit a negative misalignmen…

ASCMamba: Multimodal Time-Frequency Mamba for Acoustic Scene Classification
Bochao Sun, Dong Wang, Han Yin
https://arxiv.org/abs/2508.15632 https://arxiv.o…

ASCMamba: Multimodal Time-Frequency Mamba for Acoustic Scene Classification
Acoustic Scene Classification (ASC) is a fundamental problem in computational audition, which seeks to classify environments based on the distinctive acoustic features. In the ASC task of the APSIPA ASC 2025 Grand Challenge, the organizers introduce a multimodal ASC task. Unlike traditional ASC systems that rely solely on audio inputs, this challenge provides additional textual information as inputs, including the location where the audio is recorded and the time of recording. In this paper, we…

Information Transmission and Processing in G-Protein-Coupled-Receptor Complexes
Roger D. Jones, Achille Giacometti, Alan M. Jones
https://arxiv.org/abs/2508.11039 https://

Information Transmission and Processing in G-Protein-Coupled-Receptor Complexes
G-protein-coupled receptors (GPCRs) are central to cellular information processing, yet the physical principles governing their switching behavior remain incompletely understood. We present a first principles theoretical framework, grounded in nonequilibrium thermodynamics, to describe GPCR switching as observed in light-controlled impedance assays. The model identifies two fundamental control parameters: (1) ATP/GTP-driven chemical flux through the receptor complex, and (2) the free-energy dif…

This https://arxiv.org/abs/2411.18970 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems
Selecting an appropriate prior to compensate for information loss due to the measurement operator is a fundamental challenge in imaging inverse problems. Implicit priors based on denoising neural networks have become central to widely-used frameworks such as Plug-and-Play (PnP) algorithms. In this work, we introduce Fixed-points of Restoration (FiRe) priors as a new framework for expanding the notion of priors in PnP to general restoration models beyond traditional denoising models. The key ins…

MapKD: Unlocking Prior Knowledge with Cross-Modal Distillation for Efficient Online HD Map Construction
Ziyang Yan, Ruikai Li, Zhiyong Cui, Bohan Li, Han Jiang, Yilong Ren, Aoyong Li, Zhenning Li, Sijia Wen, Haiyang Yu
https://arxiv.org/abs/2508.15653

MapKD: Unlocking Prior Knowledge with Cross-Modal Distillation for Efficient Online HD Map Construction
Online HD map construction is a fundamental task in autonomous driving systems, aiming to acquire semantic information of map elements around the ego vehicle based on real-time sensor inputs. Recently, several approaches have achieved promising results by incorporating offline priors such as SD maps and HD maps or by fusing multi-modal data. However, these methods depend on stale offline maps and multi-modal sensor suites, resulting in avoidable computational overhead at inference. To address t…

The ''Telephone Game'' Effect in Modern Gravity Research
Andronikos Paliathanasis
https://arxiv.org/abs/2508.16682 https://arxiv.org/pdf/25…

The ''Telephone Game'' Effect in Modern Gravity Research
Triggered by some recent studies within the framework of nonmetricity gravity, I discuss how the basic information regarding the equivalence of the gravitational theories forming the \textquotedblleft Trinity of Gravity\textquotedblright\ has been lost in parts of the literature. As a result, several studies with focus in modified theories of gravity have research investigated the case of STEGR/GR, often without acknowledging this fundamental equivalence or recognizing that their results can be…

Chimera baryons and mesons on the lattice: a spectral density analysis
Ed Bennett, Luigi Del Debbio, Niccol\`o Forzano, Ryan Hill, Deog Ki Hong, Ho Hsiao, Jong-Wan Lee, C. -J. David Lin, Biagio Lucini, Alessandro Lupo, Maurizio Piai, Davide Vadacchino, Fabian Zierler
https://arxiv.org/abs/2506.19804

Chimera baryons and mesons on the lattice: a spectral density analysis
We develop and test a spectral-density analysis method, based on the introduction of smeared energy kernels, to extract physical information from two-point correlation functions computed numerically in lattice field theory. We apply it to a $Sp(4)$ gauge theory and fermion matter fields transforming in distinct representations, with $N_{\rm f}=2$ Dirac fermions in the fundamental and $N_{\rm as}=3$ in the 2-index antisymmetric representation. The corresponding continuum theory provides the mini…

User Invariant Preference Learning for Multi-Behavior Recommendation
Mingshi Yan, Zhiyong Cheng, Fan Liu, Yingda Lyu, Yahong Han
https://arxiv.org/abs/2507.14925

User Invariant Preference Learning for Multi-Behavior Recommendation
In multi-behavior recommendation scenarios, analyzing users' diverse behaviors, such as click, purchase, and rating, enables a more comprehensive understanding of their interests, facilitating personalized and accurate recommendations. A fundamental assumption of multi-behavior recommendation methods is the existence of shared user preferences across behaviors, representing users' intrinsic interests. Based on this assumption, existing approaches aim to integrate information from various behavi…

Adaptique: Multi-objective and Context-aware Online Adaptation of Selection Techniques in Virtual Reality
Chao-Jung Lai, Mauricio Sousa, Tianyu Zhang, Ludwig Sidenmark, Tovi Grossman
https://arxiv.org/abs/2508.08505

Adaptique: Multi-objective and Context-aware Online Adaptation of Selection Techniques in Virtual Reality
Selection is a fundamental task that is challenging in virtual reality due to issues such as distant and small targets, occlusion, and target-dense environments. Previous research has tackled these challenges through various selection techniques, but complicates selection and can be seen as tedious outside of their designed use case. We present Adaptique, an adaptive model that infers and switches to the most optimal selection technique based on user and environmental information. Adaptique con…

Self-Supervised Temporal Super-Resolution of Energy Data using Generative Adversarial Transformer
Xuanhao Mu, G\"okhan Demirel, Yuzhe Zhang, Jianlei Liu, Thorsten Schlachter, Veit Hagenmeyer
https://arxiv.org/abs/2508.10587

Self-Supervised Temporal Super-Resolution of Energy Data using Generative Adversarial Transformer
To bridge the temporal granularity gap in energy network design and operation based on Energy System Models, resampling of time series is required. While conventional upsampling methods are computationally efficient, they often result in significant information loss or increased noise. Advanced models such as time series generation models, Super-Resolution models and imputation models show potential, but also face fundamental challenges. The goal of time series generative models is to learn the…

The use of open boundaries in stochastic hydrodynamic models of nucleation
James F. Lutsko
https://arxiv.org/abs/2508.05528 https://arxiv.org/pdf/2508.0552…

The use of open boundaries in stochastic hydrodynamic models of nucleation
Stochastic hydrodynamics is a central tool in the study of first order phase transitions at a fundamental level. Combined with sophisticated free energy models, e.g. as developed in classical Density Functional Theory, complex processes such as crystallization can be modeled and information such as free energy barriers, nucleation pathways and the unstable eigenvector and eigenvalues determined. The latter are particularly interesting as they play key roles in defining the natural (unbiased) or…

A Study of Privacy-preserving Language Modeling Approaches
Pritilata Saha, Abhirup Sinha
https://arxiv.org/abs/2508.15421 https://arxiv.org/pdf/2508.15421

A Study of Privacy-preserving Language Modeling Approaches
Recent developments in language modeling have increased their use in various applications and domains. Language models, often trained on sensitive data, can memorize and disclose this information during privacy attacks, raising concerns about protecting individuals' privacy rights. Preserving privacy in language models has become a crucial area of research, as privacy is one of the fundamental human rights. Despite its significance, understanding of how much privacy risk these language models p…

Weak Lensing Approximation of Wave-optics Effects from General Symmetric Lens Profiles
Zhao-Feng Wu, Otto A. Hannuksela, Martin Hendry, Quynh Lan Nguyen
https://arxiv.org/abs/2508.17486

Weak Lensing Approximation of Wave-optics Effects from General Symmetric Lens Profiles
Gravitational lensing of electromagnetic (EM) waves has yielded many profound discoveries across fundamental physics, astronomy, astrophysics, and cosmology. Similar to EM waves, gravitational waves (GWs) can also be lensed. When their wavelength is comparable to the characteristic scale of the lens, wave-optics (WO) effects manifest as frequency-dependent modulations in the GW waveform. These WO features encode valuable information about the lensing system but are challenging to model, especia…

AI, AGI, and learning efficiency
My 4-month-old kid is not DDoSing Wikipedia right now, nor will they ever do so before learning to speak, read, or write. Their entire "training corpus" will not top even 100 million "tokens" before they can speak & understand language, and do so with real intentionally.
Just to emphasize that point: 100 words-per-minute times 60 minutes-per-hour times 12 hours-per-day times 365 days-per-year times 4 years is a mere 105,120,000 words. That's a ludicrously *high* estimate of words-per-minute and hours-per-day, and 4 years old (the age of my other kid) is well after basic speech capabilities are developed in many children, etc. More likely the available "training data" is at least 1 or 2 orders of magnitude less than this.
The point here is that large language models, trained as they are on multiple *billions* of tokens, are not developing their behavioral capabilities in a way that's remotely similar to humans, even if you believe those capabilities are similar (they are by certain very biased ways of measurement; they very much aren't by others). This idea that humans must be naturally good at acquiring language is an old one (see e.g. #AI #LLM #AGI

Enhanced interferometric resolution via N-fold intensity-product measurements without sacrificing phase sensitivity
S. Kim, J. Stohr, B. S. Ham
https://arxiv.org/abs/2506.06061

Enhanced interferometric resolution via N-fold intensity-product measurements without sacrificing phase sensitivity
The Fisher information theory sets a fundamental bound on the minimum measurement error achievable from independent and identically distributed (i.i.d.) measurement events. The assumption of identical and independent distribution often implies a Gaussian distribution, as seen in classical scenarios like coin tossing and an optical system exhibiting Poisson statistics. In an interferometric optical sensing platform, this translates to a fundamental limit in phase sensitivity, known as the shot-n…

STFT-based Time-Frequency Mode Decomposition: A Fast and Robust Method for Multicomponent Signal Analysis
Wei Zhou, Wei-Jian Li, Wei-Xin Ren
https://arxiv.org/abs/2507.11919

STFT-based Time-Frequency Mode Decomposition: A Fast and Robust Method for Multicomponent Signal Analysis
The decomposition of complex, multicomponent, and non-stationary signals into their constituent modes is a fundamental yet significant challenge in science and engineering. Existing methods often struggle with a trade-off among accuracy, computational cost, and the need for prior information such as the number of modes. This paper introduces time-frequency mode decomposition (TFMD), a novel framework for the fast, robust, and adaptive decomposition of such signals. TFMD operates on the principl…

Quantum Fisher information from tensor network integration of Lyapunov equation
Gabriela W\'ojtowicz, Susana F. Huelga, Marek M. Rams, Martin B. Plenio
https://arxiv.org/abs/2506.11330

Quantum Fisher information from tensor network integration of Lyapunov equation
The Quantum Fisher Information (QFI) is a geometric measure of state deformation calculated along the trajectory parameterizing an ensemble of quantum states. It serves as a key concept in quantum metrology, where it is linked to the fundamental limit on the precision of the parameter that we estimate. However, the QFI is notoriously difficult to calculate due to its non-linear mathematical form. For mixed states, standard numerical procedures based on eigendecomposition quickly become impracti…

Beer Path Problems in Temporal Graphs
Andrea D'Ascenzo, Giuseppe F. Italiano, Sotiris Kanellopoulos, Anna Mpanti, Aris Pagourtzis, Christos Pergaminelis
https://arxiv.org/abs/2507.08685

Beer Path Problems in Temporal Graphs
Computing paths in graph structures is a fundamental operation in a wide range of applications, from transportation networks to data analysis. The beer path problem, which captures the option of visiting points of interest, such as gas stations or convenience stops, prior to reaching the final destination, has been recently introduced and extensively studied in static graphs. However, existing approaches do not account for temporal information, which is often crucial in real-world scenarios. Fo…

Organic Electronic Classifiers for Sensing
S\'ebastien Pecqueur
https://arxiv.org/abs/2507.06660 https://arxiv.org/pdf/2507.06660…

Organic Electronic Classifiers for Sensing
This monograph describes nine years of research carried out at the Institute for Electronics, Micro-electronics and Nanotechnologies (IEMN), developed around defining a generic concept for detection, filling a void between metrological sensors and biological senses, sensing an environment's qualities along with their measurable properties in information generation technologies. The first chapter introduces fundamental notions of recognition for complex environments, such as for their chemistry,…

High-Efficiency Tunable Microwave Photon Detector Based on a Semiconductor Double Quantum Dot Coupled to a Superconducting High-Impedance Cavity
Fabian Oppliger, Wonjin Jang, Aldo Tarascio, Franco De Palma, Christian Reichl, Werner Wegscheider, Ville F. Maisi, Dominik Zumb\"uhl, Pasquale Scarlino
https://arxiv.org/abs/2506.…

High-Efficiency Tunable Microwave Photon Detector Based on a Semiconductor Double Quantum Dot Coupled to a Superconducting High-Impedance Cavity
High-efficiency single-photon detection in the microwave domain is a key enabling technology for quantum sensing, communication, and information processing. However, the extremely low energy of microwave photons (~μeV) presents a fundamental challenge, preventing direct photon-to-charge conversion as achieved in optical systems using semiconductors. Semiconductor quantum dot (QD) charge qubits offer a compelling solution due to their highly tunable energy levels in the microwave regime, enabli…

What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains
Chanakya Ekbote, Marco Bondaschi, Nived Rajaraman, Jason D. Lee, Michael Gastpar, Ashok Vardhan Makkuva, Paul Pu Liang
https://arxiv.org/abs/2508.07208

What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains
In-context learning (ICL) is a hallmark capability of transformers, through which trained models learn to adapt to new tasks by leveraging information from the input context. Prior work has shown that ICL emerges in transformers due to the presence of special circuits called induction heads. Given the equivalence between induction heads and conditional k-grams, a recent line of work modeling sequential inputs as Markov processes has revealed the fundamental impact of model depth on its ICL capa…

Graph Representations for Reading Comprehension Analysis using Large Language Model and Eye-Tracking Biomarker
Yuhong Zhang, Jialu Li, Shilai Yang, Yuchen Xu, Gert Cauwenberghs, Tzyy-Ping Jung
https://arxiv.org/abs/2507.11972

Graph Representations for Reading Comprehension Analysis using Large Language Model and Eye-Tracking Biomarker
Reading comprehension is a fundamental skill in human cognitive development. With the advancement of Large Language Models (LLMs), there is a growing need to compare how humans and LLMs understand language across different contexts and apply this understanding to functional tasks such as inference, emotion interpretation, and information retrieval. Our previous work used LLMs and human biomarkers to study the reading comprehension process. The results showed that the biomarkers corresponding to…

Additivity of quantum relative entropies as a single-copy criterion
Salman Beigi, Roberto Rubboli, Marco Tomamichel
https://arxiv.org/abs/2507.05696 https:…

Additivity of quantum relative entropies as a single-copy criterion
The fundamental goal of information theory is to characterize complex operational tasks using efficiently computable information quantities, Shannon's capacity formula being the prime example of this. However, many tasks in quantum information can only be characterized by regularized entropic measures that are often not known to be computable and for which efficient approximations are scarce. It is thus of fundamental importance to understand when regularization is not needed, opening the door …

Vortex Light at the Nanoscale: Twists, Spins, and Surprises -- A Review
Kayn A Forbes
https://arxiv.org/abs/2508.09564 https://arxiv.org/pdf/2508.09564

Vortex Light at the Nanoscale: Twists, Spins, and Surprises -- A Review
For over three decades, the study of optical vortex beams carrying orbital angular momentum (OAM) has been at the forefront of optics, driven by fundamental questions about optical momentum as well as diverse applications in quantum information, communications, and optical manipulation. Most work has focused on paraxial beams, whose transverse fields are accurately described by conventional wave optics and the Stokes formalism. By contrast, when light is confined to the nanoscale and tightly fo…

Phase-Driven Precision Boost in Quantum Compression for Postselected Metrology
Aiham M. Rostom, Saeed Haddadi, Vladimir A. Tomilin
https://arxiv.org/abs/2508.13934 https://

Phase-Driven Precision Boost in Quantum Compression for Postselected Metrology
We unveil the noncyclic Pancharatnam phase as a fundamental geometric criterion governing the optimal operation of quantum compression channels in postselected metrology. Harnessing this phase enables precise control over the interplay between orthogonal parameter sensitivity and parallel evolution in the meter state, thereby maximizing the quantum Fisher information per trial. Strikingly, fine-tuning the postselection parameter just below this optimal phase incurs substantial information loss,…

ParallelSearch: Train your LLMs to Decompose Query and Search Sub-queries in Parallel with Reinforcement Learning
Shu Zhao, Tan Yu, Anbang Xu, Japinder Singh, Aaditya Shukla, Rama Akkiraju
https://arxiv.org/abs/2508.09303

ParallelSearch: Train your LLMs to Decompose Query and Search Sub-queries in Parallel with Reinforcement Learning
Reasoning-augmented search agents such as Search-R1, trained via reinforcement learning with verifiable rewards (RLVR), demonstrate remarkable capabilities in multi-step information retrieval from external knowledge sources. These agents address the limitations of their parametric memory by dynamically gathering relevant facts to address complex reasoning tasks. However, existing approaches suffer from a fundamental architectural limitation: they process search queries strictly sequentially, ev…

Quantum State Preparation by Improved MPS Method
Chao Wang, Pengrui Zhou, Xi-Ning Zhuang, Ziwei Cui, Menghan Dou, Zhao-Yun Chen, Guo-Ping Guo
https://arxiv.org/abs/2508.12821 ht…

Quantum State Preparation by Improved MPS Method
Efficient encoding of classical information plays a fundamental role in numerous practical quantum algorithms. However, the preparation of an arbitrary amplitude-encoded state has been proven to be time-consuming, and its deployment on current noisy devices can be challenging. In this work, we propose an improved Matrix Product State(MPS) method preparation protocol with an exponential reduction on the circuit depth, as well as topological adaptability. By refined utilization of the disentangli…

Fidelity of entanglement and quantum entropies: unveiling their relationship in quantum states and channels
Komal Kumar, Bivas Mallick, Tapaswini Patro, Nirman Ganguly
https://arxiv.org/abs/2506.11506

Fidelity of entanglement and quantum entropies: unveiling their relationship in quantum states and channels
Entanglement serves as a fundamental resource for various quantum information processing tasks. Fidelity of entanglement (which measures the proximity to a maximally entangled state) and various quantum entropies are key indicators for certifying entanglement in a quantum state. Quantum states with high fidelity are particularly useful for numerous information-theoretic applications. Similarly, states possessing negative conditional entropy provide significant advantages in several quantum info…

Bargmann invariants of Gaussian states
Jianwei Xu
https://arxiv.org/abs/2508.07155 https://arxiv.org/pdf/2508.07155…

Bargmann invariants of Gaussian states
Given a set of ordered quantum states, described by density operators $% \{ρ_{j}\}_{j=1}^{n}$, the Bargmann invariant of $\{ρ_{j}\}_{j=1}^{n}$ is defined as tr($ρ_{1}ρ_{2}...ρ_{n}$). Bargmann invariant serves as a fundamental concept for quantum mechanics and has diverse applications in quantum information science. Bosonic Gaussian states are a class of quantum states on infinite-dimensional Hilbert space, widely used in quantum optics and quantum information science. Bosonic Gaussian stat…

Quantum Resource Complementarity in Finite-Dimensional Systems
Justin K. Edmondson
https://arxiv.org/abs/2506.11741 https://arxiv.org…

Quantum Resource Complementarity in Finite-Dimensional Systems
Quantum resources such as entanglement, information redundancy, and coherence enable revolutionary advantages but obey fundamental tradeoffs. We present a unified geometric constraint governing three core operational tasks: teleportation ($q_1$), cloning ($q_2$), and coherence-based metrology ($q_3$). For any tripartite quantum state $ρ_{ABC}$, we show the tight inequality $q_1^2 + q_2^2 + q_3^2 \leq 1$ confines all physically achievable resources to the positive octant of the unit ball. This …

This https://arxiv.org/abs/2407.09056 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

A Novel Quantum Realization of Jet Clustering in High-Energy Physics Experiments
Exploring the application of quantum technologies to fundamental sciences holds the key to fostering innovation for both sides. In high-energy particle collisions, quarks and gluons are produced and immediately form collimated particle sprays known as jets. Accurate jet clustering is crucial as it retains the information of the originating quark or gluon and forms the basis for studying properties of the Higgs boson, which underlies teh mechanism of mass generation for subatomic particles. For …

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

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

Unambiguous discrimination of the change point for quantum channels
Kenji Nakahira
https://arxiv.org/abs/2508.06785 https://arxiv.org/pdf/2508.06785…

Unambiguous discrimination of the change point for quantum channels
Identifying the precise moment when a quantum channel undergoes a change is a fundamental problem in quantum information theory. We study how accurately one can determine the time at which a channel transitions to another. We investigate the quantum limit of the average success probability in unambiguous discrimination, in which errors are completely avoided by allowing inconclusive results with a certain probability. This problem can be viewed as a quantum process discrimination task, where th…

Simulating discrete-time quantum walk with urn model
Surajit Saha
https://arxiv.org/abs/2506.06896 https://arxiv.org/pdf/2506.06896…

Simulating discrete-time quantum walk with urn model
Urn models have long been used to study stochastic processes, probability distributions, and reinforcement dynamics. Meanwhile, discrete time quantum walks (DTQW) serve as fundamental components in quantum computation and quantum information theory. This work explores a novel connection between an urn model and discrete-time quantum walks, focusing on how urn-based stochastic processes can provide insights into quantum state evolution and algorithmic behavior. Importantly, our model operates en…

Tailored First-order and Interior-point methods and a new semidefinite programming hierarchy for entanglement detection
Javier Pena, Vikesh Siddhu, Sridhar Tayur
https://arxiv.org/abs/2508.05854

Tailored First-order and Interior-point methods and a new semidefinite programming hierarchy for entanglement detection
Quantum entanglement lies at the heart of quantum information science, yet its reliable detection in high-dimensional or noisy systems remains a fundamental computational challenge. Semidefinite programming (SDP) hierarchies, such as the Doherty-Parrilo-Spedalieri (DPS) and Extension (EXT) hierarchies, offer complete methods for entanglement detection, but their practical use is limited by exponential growth in problem size. In this paper, we introduce a new SDP hierarchy, PST, that is sandwich…

Quantum Circuit Benchmarking on IBM Brisbane: Performance Insights from Superconducting Qubit Models
J. Thirunirai Selvam, S. Saravana Veni
https://arxiv.org/abs/2508.05331 http…

Quantum Circuit Benchmarking on IBM Brisbane: Performance Insights from Superconducting Qubit Models
This paper investigates quantum communication using superconducting qubits, emphasizing the simulation and control of quantum systems via IBM Brisbane quantum processor. We focus on implementing fundamental quantum gates and analyzing the evolution of entangled states, which are essential for secure and reliable information transfer. The study highlights the role of entanglement as a critical resource in quantum communication, enabling secure connectivity across quantum networks. Simulations in…