Tootfinder

Good " morning after FarmAid"
At 92, Willie Nelson
At 84, Bob Dylan
At 79, Neil Young
https://www.startribune.com/live-farm-aid-40-kicks-off-at-huntington-bank-stadium-in-minneapolis/601475512

Willie Nelson, Bob Dylan perform at Farm Aid 40
The Farm Aid founder and his friends closed out the night at Huntington Bank Stadium.

Vivo demos Vivo Vision, its first MR headset, which looks like an Apple Vision Pro clone but is ~40% lighter with micro-OLED displays, and could cost ~$1,400 (David Heaney/UploadVR)
https://www.uploadvr.com/vivo-vision-discovery-edition-launches-as-store-demo/

Vivo Vision Is 40% Lighter Than Apple Vision Pro & "Could" Be 1/3 The Price
China's Vivo Vision is 40% lighter than Apple Vision Pro, and "could" be one third the price. But for now, it's just an in-store demo, not a product.

Replaced article(s) found for cs.IT. https://arxiv.org/list/cs.IT/new
[1/1]:
- Bounds on Covert Capacity with Sub-Exponential Random Slot Selection
Shi-Yuan Wang, Keerthi S. K. Arumugam, Matthieu R. Bloch

@… you can Go or you can C yourself out 😅

IP2: Entity-Guided Interest Probing for Personalized News Recommendation
Youlin Wu, Yuanyuan Sun, Xiaokun Zhang, Haoxi Zhan, Bo Xu, Liang Yang, Hongfei Lin
https://arxiv.org/abs/2507.13622

IP2: Entity-Guided Interest Probing for Personalized News Recommendation
News recommender systems aim to provide personalized news reading experiences for users based on their reading history. Behavioral science studies suggest that screen-based news reading contains three successive steps: scanning, title reading, and then clicking. Adhering to these steps, we find that intra-news entity interest dominates the scanning stage, while the inter-news entity interest guides title reading and influences click decisions. Unfortunately, current methods overlook the unique …

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems
Guillaume Garrigos, Daniel Cortild, Lucas Ketels, Juan Peypouquet
https://arxiv.org/abs/2507.14122

Last-Iterate Complexity of SGD for Convex and Smooth Stochastic Problems
Most results on Stochastic Gradient Descent (SGD) in the convex and smooth setting are presented under the form of bounds on the ergodic function value gap. It is an open question whether bounds can be derived directly on the last iterate of SGD in this context. Recent advances suggest that it should be possible. For instance, it can be achieved by making the additional, yet unverifiable, assumption that the variance of the stochastic gradients is uniformly bounded. In this paper, we show that …

Iran seeks Belarus help to restore air defense systems, Ukraine's intelligence says: https://benborges.xyz/2025/08/22/iran-seeks-belarus-help-to.html

Just spent some time explaining that while I’m very happy to show off my setup, “which tool do you use?” is not the same question at all as “what tool would you recommend I try?”
I can only use tools with accessibility support and I’m terminal-minded. I also refuse to perpetuate the myth that “real” tech must look like this.

Hier gibt es keine Gardinen (Perde) mehr... 😢
Gerichtstr./Müllerstr.
#meinwedding #berlinwedding #wedding65

Supreme Court allows Trump administration to terminate $783 million in NIH grants linked to DEI initiatives - SCOTUSblog
https://www.scotusblog.com/2025/08/supreme-court-allows-trump-administration-to-terminate-783-million-in-nih-grants-linked-to-dei-initiatives/

Replaced article(s) found for math-ph. https://arxiv.org/list/math-ph/new
[1/1]:
- The Coleman correspondence at the free fermion point
Roland Bauerschmidt, Christian Webb

Energy Giants Abandon Global Net Zero Group Over Oil and Gas Clampdown | OilPrice.com
https://oilprice.com/Energy/Energy-General/Energy-Giants-Abandon-Global-Net-Zero-Group-Over-Oil-and-Gas-Clampdown.html

Energy Giants Abandon Global Net Zero Group Over Oil and Gas Clampdown
Shell and other oil majors have withdrawn from the SBTi climate standard effort, triggering a pause in its oil and gas guidelines.

I love #GNOME! Deal with it!
#Linux

Guten Morgen, Selbstverliebte.

"while the pen might be mightier than the sword, the wallet is mightier than the pen." — @georgemonbiot@bsky.brid.gy
Ain't that the truth.
https://www.theguardian.com/commentisfree/2025/sep/20/journalist-40-years-forces-pr…

In recent years, Oklahoma has emerged as a pop-cultural locus for America’s hidden racial sins.

💸 Agency for college athlete payment deals agrees to loosen third-party restrictions
https://www.theguardian.com/sport/2025/jul/31/agency-for-college-athlete-payment-deals-agrees-to-loosen-third-party-restrictio…

Work continues on the Dice Parser. Added a ton of features:
- Raw rolls
- Dice rerolls
- Keeping the nth lowest/highest dice
You can literally now do some craziness like "roll 10d10, reroll all rolls 3 or less, keep the two highest as fire damage, then roll 3d4, keep the lowest two values, keep those as piercing damage"
```python
dice.roll("10d10 reroll 3 keep 2[fire] 3d4 keep -2[piercing]")
dice.roll("10d10!3k2[fire] 3d4k-2[pi…

"Trump administration ends government’s annual report on hunger in America"
There. Hunger problem solved. Next.
/s
#hunger #uspol #sarcasm

🇺🇦 #NowPlaying on BBCRadio3's #RoundMidnight
Isaiah J. Thompson:
🎵 VII. A Prayer
#IsaiahJThompson
https://open.spotify.com/track/0pgQjmPPdnQ6EhKOw3ciFO

Trump inside: Intel teilverstaatlicht
Intel wird ein teilstaatlicher Konzern. 9,9 Prozent der Aktien gehen an die USA, dafür darf Intel-Chef Tan seinen Job behalten.
https://www.heise.de/news/Trump-inside…

Secretive Hotplug Coded Caching
Mallikharjuna Chinnapadamala, Charul Rajput, B. Sundar Rajan
https://arxiv.org/abs/2507.13961 https://

Secretive Hotplug Coded Caching
In this work, we consider a coded caching model called \textit{hotplug coded caching}, in which some users are offline during the delivery phase. The concept of Hotplug Placement Delivery Arrays (HpPDAs) for hotplug coded caching systems has been introduced in the literature, and two classes of HpPDAs are known. In this paper, we consider a secrecy constraint in hotplug coded caching setup, where users should not learn anything about any file from their cache content, and active users should no…

Crypto custody company BitGo confidentially files for a US IPO; it raised $100M at a $1.75B valuation in August 2023 (CoinDesk)
https://www.coindesk.com/business/2025/07/21/bitgo-files-to-go-public-as-crypto-market-surges-past-…

RiNNAL : a Riemannian ALM Solver for SDP-RLT Relaxations of Mixed-Binary Quadratic Programs
Di Hou, Tianyun Tang, Kim-Chuan Toh
https://arxiv.org/abs/2507.13776

RiNNAL+: a Riemannian ALM Solver for SDP-RLT Relaxations of Mixed-Binary Quadratic Programs
Doubly nonnegative (DNN) relaxation usually provides a tight lower bound for a mixed-binary quadratic program (MBQP). However, solving DNN problems is challenging because: (1) the problem size is $Ω((n+l)^2)$ for an MBQP with $n$ variables and $l$ inequality constraints, and (2) the rank of optimal solutions cannot be estimated a priori due to the absence of theoretical bounds. In this work, we propose RiNNAL+, a Riemannian augmented Lagrangian method (ALM) for solving DNN problems. We prove t…

Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
Alessandro B. Melchiorre, Elena V. Epure, Shahed Masoudian, Gustavo Escobedo, Anna Hausberger, Manuel Moussallam, Markus Schedl
https://arxiv.org/abs/2507.15826

Just Ask for Music (JAM): Multimodal and Personalized Natural Language Music Recommendation
Natural language interfaces offer a compelling approach for music recommendation, enabling users to express complex preferences conversationally. While Large Language Models (LLMs) show promise in this direction, their scalability in recommender systems is limited by high costs and latency. Retrieval-based approaches using smaller language models mitigate these issues but often rely on single-modal item representations, overlook long-term user preferences, and require full model retraining, pos…

Asymptotically Optimal Codes Correcting One Substring Edit
Yuting Li, Yuanyuan Tang, Hao Lou, Ryan Gabrys, Farzad Farnoud
https://arxiv.org/abs/2507.13808 …

Asymptotically Optimal Codes Correcting One Substring Edit
The substring edit error is the operation of replacing a substring $u$ of $x$ with another string $v$, where the lengths of $u$ and $v$ are bounded by a given constant $k$. It encompasses localized insertions, deletions, and substitutions within a window. Codes correcting one substring edit have redundancy at least $\log n+k$. In this paper, we construct codes correcting one substring edit with redundancy $\log n+O(\log \log n)$, which is asymptotically optimal.

Crosslisted article(s) found for math-ph. https://arxiv.org/list/math-ph/new
[1/1]:
- Average weighted ratio of consecutive level spacings for infinite-dimensional orthogonal random m...
Wouter Buijsman

A look at the data center cluster in the Chinese city of Wuhu, where 15 companies, including Huawei, have built data centers with a total investment of $37B (Financial Times)

SPAR: Scholar Paper Retrieval with LLM-based Agents for Enhanced Academic Search
Xiaofeng Shi, Yuduo Li, Qian Kou, Longbin Yu, Jinxin Xie, Hua Zhou
https://arxiv.org/abs/2507.15245

SPAR: Scholar Paper Retrieval with LLM-based Agents for Enhanced Academic Search
Recent advances in large language models (LLMs) have opened new opportunities for academic literature retrieval. However, existing systems often rely on rigid pipelines and exhibit limited reasoning capabilities. We introduce SPAR, a multi-agent framework that incorporates RefChain-based query decomposition and query evolution to enable more flexible and effective search. To facilitate systematic evaluation, we also construct SPARBench, a challenging benchmark with expert-annotated relevance la…

Round-Preserving Asymptotic Compression of Prior-Free Interactive Protocols
Gurleen Padda, Dave Touchette
https://arxiv.org/abs/2507.13464 https://

Round-Preserving Asymptotic Compression of Prior-Free Interactive Protocols
There is a close relationship between the communication complexity and information complexity of communication problems, as demonstrated by results such as Shannon's noiseless source coding theorem, and the Slepian-Wolf theorem. Here, we study this relationship in the prior-free and interactive setting, where we provide an alternate proof for the result of Braverman [SIAM Review, vol. 59, no. 4, 2017], that the amortized communication complexity of simulating a prior-free interactive communicat…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- Stochastic Primal-Dual Q-Learning
Narim Jeong, Donghwan Lee, Niao He

Tropicalized quantum field theory and global tropical sampling
Michael Borinsky
https://arxiv.org/abs/2508.14263 https://arxiv.org/pdf/2508.14263

Tropicalized quantum field theory and global tropical sampling
We explain how to tropicalize scalar quantum field theory and show that tropicalized massive scalar quantum field theory is exactly solvable. This exact solution manifests as a non-linear recursion equation fulfilled by the expansion coefficients of the quantum effective action. Geometrically, this recursion computes specific volumes of moduli spaces of metric graphs and is thereby analogous to Mirzakhani's volume recursions on the moduli space of curves. Building on this exact solution, we con…

FullRecall: A Semantic Search-Based Ranking Approach for Maximizing Recall in Patent Retrieval
Amna Ali, Liyanage C. De Silva, Pg Emeroylariffion Abas
https://arxiv.org/abs/2507.14946

FullRecall: A Semantic Search-Based Ranking Approach for Maximizing Recall in Patent Retrieval
Patent examiners and inventors face significant pressure to verify the originality and non-obviousness of inventions, and the intricate nature of patent data intensifies the challenges of patent retrieval. Therefore, there is a pressing need to devise cutting-edge retrieval strategies that can reliably achieve the desired recall. This study introduces FullRecall, a novel patent retrieval approach that effectively manages the complexity of patent data while maintaining the reliability of relevan…

Bakkt shares jump 40% after naming Mike Alfred, the crypto veteran who co-founded Digital Assets Data, to its board (RT Watson/The Block)
https://www.theblock.co/post/371733/bakkt-stock-jumps-over-40-after-naming-crypto-vet-mike-alf…

Error Correcting Codes for Segmented Burst-Deletion Channels
Yajuan Liu, Tolga M. Duman
https://arxiv.org/abs/2507.14070 https://arxi…

Error Correcting Codes for Segmented Burst-Deletion Channels
We study segmented burst-deletion channels motivated by the observation that synchronization errors commonly occur in a bursty manner in real-world settings. In this channel model, transmitted sequences are implicitly divided into non-overlapping segments, each of which may experience at most one burst of deletions. In this paper, we develop error correction codes for segmented burst-deletion channels over arbitrary alphabets under the assumption that each segment may contain only one burst of …

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining
Van-Hoang Le, Duc-Vu Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
https://arxiv.org/abs/2507.14619

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining
Large Language Models (LLMs) face significant challenges in specialized domains like law, where precision and domain-specific knowledge are critical. This paper presents a streamlined two-stage framework consisting of Retrieval and Re-ranking to enhance legal document retrieval efficiency and accuracy. Our approach employs a fine-tuned Bi-Encoder for rapid candidate retrieval, followed by a Cross-Encoder for precise re-ranking, both optimized through strategic negative example mining. Key innov…

cuPDLP : A Further Enhanced GPU-Based First-Order Solver for Linear Programming
Haihao Lu, Zedong Peng, Jinwen Yang
https://arxiv.org/abs/2507.14051 https:…

cuPDLP+: A Further Enhanced GPU-Based First-Order Solver for Linear Programming
We introduce cuPDLP+, a further enhanced GPU-based first-order solver for linear programming. Building on the predecessor cuPDLP, cuPDLP+ incorporates recent algorithmic advances, including the restarted Halpern PDHG method with reflection, a novel restart criterion, and a PID-controlled primal weight update. These innovations are carefully tailored for GPU architectures and deliver substantial empirical gains. On a comprehensive benchmark of MIPLIB LP relaxations, cuPDLP+ achieves 2x - 4x spee…

[2025-08-21 Thu (UTC), 1 new article found for math-ph Mathematical Physics]
toXiv_bot_toot

Bounds and Constructions of High-Memory Spatially-Coupled Codes
Lei Huang
https://arxiv.org/abs/2507.14064 https://arxiv.org/pdf/2507…

Bounds and Constructions of High-Memory Spatially-Coupled Codes
In this paper, we apply the Clique Lovász Local Lemma to provide sufficient conditions on memory and lifting degree for removing certain harmful combinatorial structures in spatially-coupled (SC) codes that negatively impact decoding performance. Additionally, we present, for the first time, a constructive algorithm based on the Moser-Tardos algorithm that ensures predictable performance. Furthermore, leveraging the properties of LLL-distribution and M-T-distribution, we establish the dependen…

RaMen: Multi-Strategy Multi-Modal Learning for Bundle Construction
Huy-Son Nguyen, Quang-Huy Nguyen, Duc-Hoang Pham, Duc-Trong Le, Hoang-Quynh Le, Padipat Sitkrongwong, Atsuhiro Takasu, Masoud Mansoury
https://arxiv.org/abs/2507.14361

RaMen: Multi-Strategy Multi-Modal Learning for Bundle Construction
Existing studies on bundle construction have relied merely on user feedback via bipartite graphs or enhanced item representations using semantic information. These approaches fail to capture elaborate relations hidden in real-world bundle structures, resulting in suboptimal bundle representations. To overcome this limitation, we propose RaMen, a novel method that provides a holistic multi-strategy approach for bundle construction. RaMen utilizes both intrinsic (characteristics) and extrinsic (c…

A Multi-Objective Optimization framework for Decentralized Learning with coordination constraints
Roberto Morales, Umberto Biccari
https://arxiv.org/abs/2507.13983

A Multi-Objective Optimization framework for Decentralized Learning with coordination constraints
This article introduces a generalized framework for Decentralized Learning formulated as a Multi-Objective Optimization problem, in which both distributed agents and a central coordinator contribute independent, potentially conflicting objectives over a shared model parameter space. Unlike traditional approaches that merge local losses under a common goal, our formulation explicitly incorporates coordinator-side criteria, enabling more flexible and structured training dynamics. To navigate the …

Replaced article(s) found for math-ph. https://arxiv.org/list/math-ph/new
[1/1]:
- Tautological Tuning of the Kostant-Souriau Quantization Map with Differential Geometric Structures
Tom McClain

Density Evolution Analysis of Sparse-Block IDMA
Jean-Francois Chamberland, Gianluigi Liva, Krishna Narayanan
https://arxiv.org/abs/2507.13689 https://

Density Evolution Analysis of Sparse-Block IDMA
Sparse block interleaver division multiple access (SB-IDMA) is a recently introduced unsourced multiple access protocol that aims to improve the performance of the grant-free two-step random access transmission protocol of the 3GPP 5G New Radio standard. We introduced a density evolution analysis of the successive interference cancellation receiver of SB-IDMA, providing a theoretical characterization of its performance.

Gradient descent avoids strict saddles with a simple line-search method too
Andreea-Alexandra Mu\c{s}at, Nicolas Boumal
https://arxiv.org/abs/2507.13804 ht…

Gradient descent avoids strict saddles with a simple line-search method too
It is known that gradient descent (GD) on a $C^2$ cost function generically avoids strict saddle points when using a small, constant step size. However, no such guarantee existed for GD with a line-search method. We provide one for a modified version of the standard Armijo backtracking method with generic, arbitrarily large initial step size. In contrast to previous works, our analysis does not require a globally Lipschitz gradient. We extend this to the Riemannian setting (RGD), assuming the…

Crosslisted article(s) found for math-ph. https://arxiv.org/list/math-ph/new
[1/1]:
- On the Fermi-Dirac-type Fisher information
Yuzhe Zhu
https://

Efficient Decoding of Double-circulant and Wozencraft Codes from Square-root Errors
Oren Dubin, Noam Oz, Noga Ron-Zewi
https://arxiv.org/abs/2507.13548 htt…

Efficient Decoding of Double-circulant and Wozencraft Codes from Square-root Errors
We present efficient decoding algorithms from square-root errors for two known families of double-circulant codes: A construction based on Sidon sets (Bhargava, Taveres, and Shiva, \emph{IEEE IT 74}; Calderbank, \emph{IEEE IT 83}; Guruswami and Li, \emph{IEEE IT 2025}), and a construction based on cyclic codes (Chen, Peterson, and Weldon, \emph{Information and Control 1969}). We further observe that the work of Guruswami and Li implicitly gives a transformation from double-circulant codes of ce…

Replaced article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review
Alexander Michael Rombach, Peter Fettke

Conformal Contraction for Robust Nonlinear Control with Distribution-Free Uncertainty Quantification
Sihang Wei, Melkior Ornik, Hiroyasu Tsukamoto
https://arxiv.org/abs/2507.13613

Conformal Contraction for Robust Nonlinear Control with Distribution-Free Uncertainty Quantification
We present a novel robust control framework for continuous-time, perturbed nonlinear dynamical systems with uncertainty that depends nonlinearly on both the state and control inputs. Unlike conventional approaches that impose structural assumptions on the uncertainty, our framework enhances contraction-based robust control with data-driven uncertainty prediction, remaining agnostic to the models of the uncertainty and predictor. We statistically quantify how reliably the contraction conditions …

Cluster Expansion and Decay of Correlations for Multidimensional Long-Range Ising Models
Lucas Affonso, Rodrigo Bissacot, Jo\~ao Maia, Jo\~ao F. Rodrigues, Kelvyn Welsch
https://arxiv.org/abs/2508.15666

Cluster Expansion and Decay of Correlations for Multidimensional Long-Range Ising Models
We develop the cluster expansion for the multidimensional multiscaled contours defined by three of us. These contours are suitable for long-range Ising models with interaction $J_{xy}=J(|x-y|)= J/|x-y|^α$, $J>0$, and $α>d$. As an application of the convergence of the cluster expansion at low temperatures, we study the decay of the truncated two-point correlation functions, showing that the decay is algebraic with coefficient $α$.

Loss-Complexity Landscape and Model Structure Functions
Alexander Kolpakov
https://arxiv.org/abs/2507.13543 https://arxiv.org/pdf/250…

Loss-Complexity Landscape and Model Structure Functions
We develop a framework for dualizing the Kolmogorov structure function $h_x(α)$, which then allows using computable complexity proxies. We establish a mathematical analogy between information-theoretic constructs and statistical mechanics, introducing a suitable partition function and free energy functional. We explicitly prove the Legendre-Fenchel duality between the structure function and free energy, showing detailed balance of the Metropolis kernel, and interpret acceptance probabilities a…

[2025-07-21 Mon (UTC), 8 new articles found for cs.IT Information Theory]
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DUALRec: A Hybrid Sequential and Language Model Framework for Context-Aware Movie Recommendation
Yitong Li, Raoul Grasman
https://arxiv.org/abs/2507.13957 …

DUALRec: A Hybrid Sequential and Language Model Framework for Context-Aware Movie Recommendation
The modern recommender systems are facing an increasing challenge of modelling and predicting the dynamic and context-rich user preferences. Traditional collaborative filtering and content-based methods often struggle to capture the temporal patternings and evolving user intentions. While Large Language Models (LLMs) have gained gradual attention in recent years, by their strong semantic understanding and reasoning abilities, they are not inherently designed to model chronologically evolving us…

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

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

Uncertainty Relation for the Wigner-Yanase Skew Information and Quantum Sobolev Inequalities
Laurent Lafleche
https://arxiv.org/abs/2508.15554 https://arxi…

Uncertainty Relation for the Wigner-Yanase Skew Information and Quantum Sobolev Inequalities
This note explores uncertainty inequalities for quantum analogues of the Fisher information including the Wigner-Yanase skew information, and their connection to the quantum Sobolev inequalities proved by the author in [Journal of Functional Analysis, 286 (10) 2024]. Some additional inequalities concerning commutators are derived and others are left as open problems.

A DPI-PAC-Bayesian Framework for Generalization Bounds
Muhan Guan, Farhad Farokhi, Jingge Zhu
https://arxiv.org/abs/2507.14795 https://

A DPI-PAC-Bayesian Framework for Generalization Bounds
We develop a unified Data Processing Inequality PAC-Bayesian framework -- abbreviated DPI-PAC-Bayesian -- for deriving generalization error bounds in the supervised learning setting. By embedding the Data Processing Inequality (DPI) into the change-of-measure technique, we obtain explicit bounds on the binary Kullback-Leibler generalization gap for both Rényi divergence and any $f$-divergence measured between a data-independent prior distribution and an algorithm-dependent posterior distributi…

PARK: Personalized academic retrieval with knowledge-graphs
Pranav Kasela, Gabriella Pasi, Raffaele Perego
https://arxiv.org/abs/2507.13910 https://…

PARK: Personalized academic retrieval with knowledge-graphs
Academic Search is a search task aimed to manage and retrieve scientific documents like journal articles and conference papers. Personalization in this context meets individual researchers' needs by leveraging, through user profiles, the user related information (e.g. documents authored by a researcher), to improve search effectiveness and to reduce the information overload. While citation graphs are a valuable means to support the outcome of recommender systems, their use in personalized acade…

Single spin exact gradients for the optimization of complex pulses and pulse sequences
Stella Slad, Burkhard Luy
https://arxiv.org/abs/2507.13557 https://

Single spin exact gradients for the optimization of complex pulses and pulse sequences
The efficient computer optimization of magnetic resonance pulses and pulse sequences involves the calculation of a problem-adapted cost function as well as its gradients with respect to all controls applied. The gradients generally can be calculated as a finite difference approximation, as a GRAPE approximation, or as an exact function, e.g. by the use of the augmented matrix exponentiation, where the exact gradient should lead to best optimization convergence. However, calculation of exact gra…

GW/DT invariants and 5D BPS indices for strips from topological recursion
Sibasish Banerjee, Alexander Hock, Olivier Marchal
https://arxiv.org/abs/2508.15459 https://

GW/DT invariants and 5D BPS indices for strips from topological recursion
Topological string theory partition function gives rise to Gromov-Witten invariants, Donaldson-Thomas invariants and 5D BPS indices. Via the remodeling conjecture connecting Topological Recursion and topological string theory for toric Calabi-Yau 3-folds, a more direct connection is studied for the subclass of strip geometries. In doing so, new developments in the theory of topological recursion are applied as its extension to Logarithmic Topological Recursion (Log-TR) and the universal $x$--$y…

Study of Delay-Calibrated Joint User Activity Detection, Channel Estimation and Data Detection for Asynchronous mMTC Systems
Z. Shao, X. Yuan, R. de Lamare
https://arxiv.org/abs/2507.14733

Study of Delay-Calibrated Joint User Activity Detection, Channel Estimation and Data Detection for Asynchronous mMTC Systems
This work considers uplink asynchronous massive machine-type communications, where a large number of low-power and low-cost devices asynchronously transmit short packets to an access point equipped with multiple receive antennas. If orthogonal preambles are employed, massive collisions will occur due to the limited number of orthogonal preambles given the preamble sequence length. To address this problem, we propose a delay-calibrated joint user activity detection, channel estimation, and data …

SPARQL Query Generation with LLMs: Measuring the Impact of Training Data Memorization and Knowledge Injection
Aleksandr Gashkov, Aleksandr Perevalov, Maria Eltsova, Andreas Both
https://arxiv.org/abs/2507.13859

SPARQL Query Generation with LLMs: Measuring the Impact of Training Data Memorization and Knowledge Injection
Nowadays, the importance of software with natural-language user interfaces cannot be underestimated. In particular, in Question Answering (QA) systems, generating a SPARQL query for a given natural-language question (often named Query Building) from the information retrieved from the same question is the central task of QA systems working over Knowledge Graphs (KGQA). Due to the rise of Large Language Models (LLMs), they are considered a well-suited method to increase the quality of the questio…

A Specialized Simplex Algorithm for Budget-Constrained Total Variation-Regularized Problems
Dominic Yang
https://arxiv.org/abs/2507.13493 https://

A Specialized Simplex Algorithm for Budget-Constrained Total Variation-Regularized Problems
We consider a class of linear programs on graphs with total variation regularization and a budgetary constraint. For these programs, we give a characterization of basic solutions in terms of rooted spanning forests with orientation on the underlying graph. This leads to an interpretation of the simplex method in terms of simple graph operations on these underlying forests. We exploit this structure to produce an accelerated simplex method and empirically show that such improvements can lead to …

Equivalence of mutually unbiased bases via orbits: general theory and a $d=4$ case study
Amit Te'eni, Eliahu Cohen
https://arxiv.org/abs/2508.15412 https://

Equivalence of mutually unbiased bases via orbits: general theory and a $d=4$ case study
In quantum mechanics, mutually unbiased bases (MUBs) represent orthonormal bases that are as "far apart" as possible, and their classification reveals rich underlying geometric structure. Given a complex inner product space, we construct the space of its orthonormal bases as a discrete quotient of the complete flag manifold. We introduce a metric on this space, which corresponds to the "MUBness" distance. This allows us to describe equivalence between sets of mutually unbiased bases in terms of…

RAG-based Architectures for Drug Side Effect Retrieval in LLMs
Shad Nygren, Pinar Avci, Andre Daniels, Reza Rassol, Afshin Beheshti, Diego Galeano
https://arxiv.org/abs/2507.13822

RAG-based Architectures for Drug Side Effect Retrieval in LLMs
Drug side effects are a major global health concern, necessitating advanced methods for their accurate detection and analysis. While Large Language Models (LLMs) offer promising conversational interfaces, their inherent limitations, including reliance on black-box training data, susceptibility to hallucinations, and lack of domain-specific knowledge, hinder their reliability in specialized fields like pharmacovigilance. To address this gap, we propose two architectures: Retrieval-Augmented Gene…

Expansive Natural Neural Gradient Flows for Energy Minimization
Wolfgang Dahmen, Wuchen Li, Yuankai Teng, Zhu Wang
https://arxiv.org/abs/2507.13475 https:/…

Expansive Natural Neural Gradient Flows for Energy Minimization
This paper develops expansive gradient dynamics in deep neural network-induced mapping spaces. Specifically, we generate tools and concepts for minimizing a class of energy functionals in an abstract Hilbert space setting covering a wide scope of applications such as PDEs-based inverse problems and supervised learning. The approach hinges on a Hilbert space metric in the full diffeomorphism mapping space, which could be viewed as a generalized Wasserstein-2 metric. We then study a projection gr…

[2025-08-22 Fri (UTC), 4 new articles found for math-ph Mathematical Physics]
toXiv_bot_toot

Point of Interest Recommendation: Pitfalls and Viable Solutions
Alejandro Bellog\'in, Linus W. Dietz, Francesco Ricci, Pablo S\'anchez
https://arxiv.org/abs/2507.13725

Point of Interest Recommendation: Pitfalls and Viable Solutions
Point of interest (POI) recommendation can play a pivotal role in enriching tourists' experiences by suggesting context-dependent and preference-matching locations and activities, such as restaurants, landmarks, itineraries, and cultural attractions. Unlike some more common recommendation domains (e.g., music and video), POI recommendation is inherently high-stakes: users invest significant time, money, and effort to search, choose, and consume these suggested POIs. Despite the numerous researc…

[2025-07-21 Mon (UTC), 10 new articles found for math.OC Optimization and Control]
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Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
Genki Kusano, Kosuke Akimoto, Kunihiro Takeoka
https://arxiv.org/abs/2507.13525

Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
Large language models (LLMs) can perform recommendation tasks by taking prompts written in natural language as input. Compared to traditional methods such as collaborative filtering, LLM-based recommendation offers advantages in handling cold-start, cross-domain, and zero-shot scenarios, as well as supporting flexible input formats and generating explanations of user behavior. In this paper, we focus on a single-user setting, where no information from other users is used. This setting is practi…

Replaced article(s) found for cs.IT. https://arxiv.org/list/cs.IT/new
[1/1]:
- TREET: TRansfer Entropy Estimation via Transformers
Omer Luxembourg, Dor Tsur, Haim Permuter

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning
Qingyun Sun, Jiaqi Yuan, Shan He, Xiao Guan, Haonan Yuan, Xingcheng Fu, Jianxin Li, Philip S. Yu
https://arxiv.org/abs/2507.13396

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning
Graph Retrieval-Augmented Generation has emerged as a powerful paradigm for grounding large language models with external structured knowledge. However, existing Graph RAG methods struggle with temporal reasoning, due to their inability to model the evolving structure and order of real-world events. In this work, we introduce DyG-RAG, a novel event-centric dynamic graph retrieval-augmented generation framework designed to capture and reason over temporal knowledge embedded in unstructured text.…

The Capacity of Semantic Private Information Retrieval with Colluding Servers
Mohamed Nomeir, Alptug Aytekin, Sennur Ulukus
https://arxiv.org/abs/2507.15818

The Capacity of Semantic Private Information Retrieval with Colluding Servers
We study the problem of semantic private information retrieval (Sem-PIR) with $T$ colluding servers (Sem-TPIR), i.e., servers that collectively share user queries. In Sem-TPIR, the message sizes are different, and message retrieval probabilities by any user are not uniform. This is a generalization of the classical PIR problem where the message sizes are equal and message retrieval probabilities are identical. The earlier work on Sem-PIR considered the case of no collusions, i.e., the collusion…

[2025-07-21 Mon (UTC), 8 new articles found for cs.IR Information Retrieval]
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Remote Channel Synthesis
Yassine Hamdi, Deniz G\"und\"uz
https://arxiv.org/abs/2507.15757 https://arxiv.org/pdf/2507.15757

Remote Channel Synthesis
We consider the problem of synthesizing a memoryless channel between an unobserved source and a remote terminal. An encoder has access to a partial or noisy version $Z^n = (Z_1, \ldots, Z_n)$ of a remote source sequence $X^n = (X_1, \ldots, X_n),$ with $(X_i,Z_i)$ independent and identically distributed with joint distribution $q_{X,Z}.$ The encoder communicates through a noiseless link to a decoder which aims to produce an output $Y^n$ coordinated with the remote source; that is, the total var…

Estimating Rate-Distortion Functions Using the Energy-Based Model
Shitong Wu, Sicheng Xu, Lingyi Chen, Huihui Wu, Wenyi Zhang
https://arxiv.org/abs/2507.15700

Estimating Rate-Distortion Functions Using the Energy-Based Model
The rate-distortion (RD) theory is one of the key concepts in information theory, providing theoretical limits for compression performance and guiding the source coding design, with both theoretical and practical significance. The Blahut-Arimoto (BA) algorithm, as a classical algorithm to compute RD functions, encounters computational challenges when applied to high-dimensional scenarios. In recent years, many neural methods have attempted to compute high-dimensional RD problems from the perspe…

Replaced article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- Hierarchical Reinforcement Learning for Temporal Abstraction of Listwise Recommendation
Luo Ji, Gao Liu, Mingyang Yin, Hongxia Yang, Jingren Zhou

Galois equiangular tight frames from Galois self-dual codes
Junmin An, Jon-Lark Kim
https://arxiv.org/abs/2507.15448 https://arxiv.or…

Galois equiangular tight frames from Galois self-dual codes
Greaves et al. (2022) extended frames over real or complex numbers to frames over finite fields. In this paper, we study the theory of frames over finite fields by incorporating the Galois inner products introduced by Fan and Zhang (2017), which generalize the Euclidean and Hermitian inner products. We define a class of frames, called Galois frames over finite fields, along with related notions such as Galois Gram matrices, Galois frame operators, and Galois equiangular tight frames (Galois ETF…

RankMixer: Scaling Up Ranking Models in Industrial Recommenders
Jie Zhu, Zhifang Fan, Xiaoxie Zhu, Yuchen Jiang, Hangyu Wang, Xintian Han, Haoran Ding, Xinmin Wang, Wenlin Zhao, Zhen Gong, Huizhi Yang, Zheng Chai, Zhe Chen, Yuchao Zheng, Qiwei Chen, Feng Zhang, Xun Zhou, Peng Xu, Xiao Yang, Di Wu, Zuotao Liu
https://arxiv.org/ab…

RankMixer: Scaling Up Ranking Models in Industrial Recommenders
Recent progress on large language models (LLMs) has spurred interest in scaling up recommendation systems, yet two practical obstacles remain. First, training and serving cost on industrial Recommenders must respect strict latency bounds and high QPS demands. Second, most human-designed feature-crossing modules in ranking models were inherited from the CPU era and fail to exploit modern GPUs, resulting in low Model Flops Utilization (MFU) and poor scalability. We introduce RankMixer, a hardware…

Cross Mutual Information
Chetan Gohil, Oliver M Cliff, James M. Shine, Ben D. Fulcher, Joseph T. Lizier
https://arxiv.org/abs/2507.15372 https://

Cross Mutual Information
Mutual information (MI) is a useful information-theoretic measure to quantify the statistical dependence between two random variables: $X$ and $Y$. Often, we are interested in understanding how the dependence between $X$ and $Y$ in one set of samples compares to another. Although the dependence between $X$ and $Y$ in each set of samples can be measured separately using MI, these estimates cannot be compared directly if they are based on samples from a non-stationary distribution. Here, we propo…

Hierarchical Graph Information Bottleneck for Multi-Behavior Recommendation
Hengyu Zhang, Chunxu Shen, Xiangguo Sun, Jie Tan, Yanchao Tan, Yu Rong, Hong Cheng, Lingling Yi
https://arxiv.org/abs/2507.15395

Hierarchical Graph Information Bottleneck for Multi-Behavior Recommendation
In real-world recommendation scenarios, users typically engage with platforms through multiple types of behavioral interactions. Multi-behavior recommendation algorithms aim to leverage various auxiliary user behaviors to enhance prediction for target behaviors of primary interest (e.g., buy), thereby overcoming performance limitations caused by data sparsity in target behavior records. Current state-of-the-art approaches typically employ hierarchical design following either cascading (e.g., vi…

A Novel Two-Dimensional Smoothing Algorithm
Xufeng Chen, Liang Yan, Xiaoshan Gao
https://arxiv.org/abs/2507.15301 https://arxiv.org/p…

A Novel Two-Dimensional Smoothing Algorithm
Smoothing and filtering two-dimensional sequences are fundamental tasks in fields such as computer vision. Conventional filtering algorithms often rely on the selection of the filtering window, limiting their applicability in certain scenarios. To this end, we propose a novel Two-Dimensional Smoothing (TDS) algorithm for the smoothing and filtering problem of two-dimensional sequences. Typically, the TDS algorithm does not require assumptions about the type of noise distribution. It is simple a…

GREAT: Guiding Query Generation with a Trie for Recommending Related Search about Video at Kuaishou
Ninglu Shao, Jinshan Wang, Chenxu Wang, Qingbiao Li, Xiaoxue Zang, Han Li
https://arxiv.org/abs/2507.15267

GREAT: Guiding Query Generation with a Trie for Recommending Related Search about Video at Kuaishou
Currently, short video platforms have become the primary place for individuals to share experiences and obtain information. To better meet users' needs for acquiring information while browsing short videos, some apps have introduced a search entry at the bottom of videos, accompanied with recommended relevant queries. This scenario is known as query recommendation in video-related search, where core task is item-to-query (I2Q) recommendation. As this scenario has only emerged in recent years, t…

The Exact Parameters of A Family of BCH Codes
Zhonghua Sun
https://arxiv.org/abs/2507.15247 https://arxiv.org/pdf/2507.15247

The Exact Parameters of A Family of BCH Codes
Despite the theoretical and practical significance of BCH codes, the exact minimum distance and dimension remain unknown for many families. This paper establishes the precise minimum distance and dimension of narrow-sense BCH codes $\C_{(q, m, λ, \ell_0, \ell_1)}$ over $\gf(q)$ of length $\frac{q^m-1}λ$ and designed distance $\frac{(q-λ\ell_0)q^{m-1-\ell_1}-1}λ$, where $λ\mid (q-1)$, $0\leq \ell_0< \frac{q-1}λ$, and $0\leq \ell_1\leq m-1$. These results conclusively resolve the three open…

Click A, Buy B: Rethinking Conversion Attribution in E- Commerce Recommendations
Xiangyu Zeng, Amit Jaspal, Bin Liu, Goutham Panneeru, Kevin Huang, Nicolas Bievre, Mohit Jaggi, Prathap Maniraju, Ankur Jain
https://arxiv.org/abs/2507.15113

Click A, Buy B: Rethinking Conversion Attribution in E- Commerce Recommendations
User journeys in e-commerce routinely violate the one-to-one assumption that a clicked item on an advertising platform is the same item later purchased on the merchant's website/app. For a significant number of converting sessions on our platform, users click product A but buy product B -- the Click A, Buy B (CABB) phenomenon. Training recommendation models on raw click-conversion pairs therefore rewards items that merely correlate with purchases, leading to biased learning and sub-optimal conv…

Noise Quantification and Control in Circuits via Strong Data-Processing Inequalities
Chenyang Sun
https://arxiv.org/abs/2507.15108 https://

Noise Quantification and Control in Circuits via Strong Data-Processing Inequalities
This essay explores strong data-processing inequalities (SPDI's) as they appear in the work of Evans and Schulman \cite{ES} and von Neumann \cite{vN} on computing with noisy circuits. We first develop the framework in \cite{ES}, which leads to lower bounds on depth and upper bounds on noise that permit reliable computation. We then introduce the $3$-majority gate, introduced by \cite{vN} for the purpose of controlling noise, and obtain an upper bound on noise necessary for its function. We end …

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…

Reconfigurable Antenna Arrays With Tunable Loads: Expanding Solution Space via Coupling Control
Elio Faddoul, Konstantinos Ntougias, Ioannis Krikidis
https://arxiv.org/abs/2507.15074

Reconfigurable Antenna Arrays With Tunable Loads: Expanding Solution Space via Coupling Control
The emerging reconfigurable antenna (RA) array technology promises capacity enhancement through dynamic antenna positioning. Traditional approaches enforce half-wavelength or greater spacing among RA elements to avoid mutual coupling, limiting the solution space. Additionally, achieving sufficient spatial channel sampling requires numerous discrete RA positions (ports), while high-frequency scenarios with hybrid processing demand many physical RAs to maintain array gains. This leads to exponent…

U-MARVEL: Unveiling Key Factors for Universal Multimodal Retrieval via Embedding Learning with MLLMs
Xiaojie Li, Chu Li, Shi-Zhe Chen, Xi Chen
https://arxiv.org/abs/2507.14902

U-MARVEL: Unveiling Key Factors for Universal Multimodal Retrieval via Embedding Learning with MLLMs
Universal multimodal retrieval (UMR), which aims to address complex retrieval tasks where both queries and candidates span diverse modalities, has been significantly advanced by the emergence of MLLMs. While state-of-the-art MLLM-based methods in the literature predominantly adopt contrastive learning principles, they often differ in their specific training recipes. Despite their success, the mechanisms underlying their retrieval capabilities remain largely unexplored, potentially resulting in …

Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
Rivka Gitik, Alejandro Cohen
https://arxiv.org/abs/2507.14852 https://

Variable Min-Cut Max-Flow Bounds and Algorithms in Finite Regime
The maximum achievable capacity from source to destination in a network is limited by the min-cut max-flow bound; this serves as a converse limit. In practice, link capacities often fluctuate due to dynamic network conditions. In this work, we introduce a novel analytical framework that leverages tools from computational geometry to analyze throughput in heterogeneous networks with variable link capacities in a finite regime. Within this model, we derive new performance bounds and demonstrate t…

Enhancing POI Recommendation through Global Graph Disentanglement with POI Weighted Module
Pei-Xuan Li, Wei-Yun Liang, Fandel Lin, Hsun-Ping Hsieh
https://arxiv.org/abs/2507.14612

Enhancing POI Recommendation through Global Graph Disentanglement with POI Weighted Module
Next point of interest (POI) recommendation primarily predicts future activities based on users' past check-in data and current status, providing significant value to users and service providers. We observed that the popular check-in times for different POI categories vary. For example, coffee shops are crowded in the afternoon because people like to have coffee to refresh after meals, while bars are busy late at night. However, existing methods rarely explore the relationship between POI categ…

Rate-Distortion-Perception Trade-off with Strong Realism Constraints: Role of Side Information and Common Randomness
Yassine Hamdi, Aaron B. Wagner, Deniz G\"und\"uz
https://arxiv.org/abs/2507.14825

Rate-Distortion-Perception Trade-off with Strong Realism Constraints: Role of Side Information and Common Randomness
In image compression, with recent advances in generative modeling, existence of a trade-off between the rate and perceptual quality has been brought to light, where the perceptual quality is measured by the closeness of the output and source distributions. We consider the compression of a memoryless source sequence $X^n=(X_1, \ldots, X_n)$ in the presence of memoryless side information $Z^n=(Z_1, \ldots, Z_n),$ originally studied by Wyner and Ziv, but elucidate the impact of a strong perfect re…

Understanding Matching Mechanisms in Cross-Encoders
Mathias Vast, Basile Van Cooten, Laure Soulier, Benjamin Piwowarski
https://arxiv.org/abs/2507.14604 ht…

Understanding Matching Mechanisms in Cross-Encoders
Neural IR architectures, particularly cross-encoders, are highly effective models whose internal mechanisms are mostly unknown. Most works trying to explain their behavior focused on high-level processes (e.g., what in the input influences the prediction, does the model adhere to known IR axioms) but fall short of describing the matching process. Instead of Mechanistic Interpretability approaches which specifically aim at explaining the hidden mechanisms of neural models, we demonstrate that mo…

Enhancing Communications and Sensing Simultaneously by Zero-Order Optimization of MTS
Wenhai Lai, Kaiming Shen, Zhi-Quan Luo
https://arxiv.org/abs/2507.14794

Enhancing Communications and Sensing Simultaneously by Zero-Order Optimization of MTS
Metasurface (MTS) comprises an array of metaatoms, each reflecting and inducing a phase shift into the incident wireless signal. We seek the optimal combination of phase shifts across all the meta-atoms to maximize the channel strength from transmitter to receiver. Unlike many existing works that heavily rely on channel state information (CSI), this paper proposes a statistical approach to the phase shift optimization in the absence of CSI, namely blind configuration or zero-order optimization.…

A Reproducibility Study of Product-side Fairness in Bundle Recommendation
Huy-Son Nguyen, Yuanna Liu, Masoud Mansoury, Mohammad Alian Nejadi, Alan Hanjalic, Maarten de Rijke
https://arxiv.org/abs/2507.14352

A Reproducibility Study of Product-side Fairness in Bundle Recommendation
Recommender systems are known to exhibit fairness issues, particularly on the product side, where products and their associated suppliers receive unequal exposure in recommended results. While this problem has been widely studied in traditional recommendation settings, its implications for bundle recommendation (BR) remain largely unexplored. This emerging task introduces additional complexity: recommendations are generated at the bundle level, yet user satisfaction and product (or supplier) ex…

Enhancing Resilience Against Jamming Attacks: A Cooperative Anti-Jamming Method Using Direction Estimation
Amir Mehrabian, Georges Kaddoum
https://arxiv.org/abs/2507.14775

Enhancing Resilience Against Jamming Attacks: A Cooperative Anti-Jamming Method Using Direction Estimation
The inherent vulnerability of wireless communication necessitates strategies to enhance its security, particularly in the face of jamming attacks. This paper uses the collaborations of multiple sensing nodes (SNs) in the wireless network to present a cooperative anti-jamming approach (CAJ) designed to neutralize the impact of jamming attacks. We propose an eigenvector (EV) method to estimate the direction of the channel vector from pilot symbols. Through our analysis, we demonstrate that with a…

LOVO: Efficient Complex Object Query in Large-Scale Video Datasets
Yuxin Liu, Yuezhang Peng, Hefeng Zhou, Hongze Liu, Xinyu Lu, Jiong Lou, Chentao Wu, Wei Zhao, Jie Li
https://arxiv.org/abs/2507.14301

LOVO: Efficient Complex Object Query in Large-Scale Video Datasets
The widespread deployment of cameras has led to an exponential increase in video data, creating vast opportunities for applications such as traffic management and crime surveillance. However, querying specific objects from large-scale video datasets presents challenges, including (1) processing massive and continuously growing data volumes, (2) supporting complex query requirements, and (3) ensuring low-latency execution. Existing video analysis methods struggle with either limited adaptability…

Collusion-Resilient Hierarchical Secure Aggregation with Heterogeneous Security Constraints
Zhou Li, Xiang Zhang, Jiawen Lv, Jihao Fan, Haiqiang Chen, Giuseppe Caire
https://arxiv.org/abs/2507.14768

Collusion-Resilient Hierarchical Secure Aggregation with Heterogeneous Security Constraints
Motivated by federated learning (FL), secure aggregation (SA) aims to securely compute, as efficiently as possible, the sum of a set of inputs distributed across many users. To understand the impact of network topology, hierarchical secure aggregation (HSA) investigated the communication and secret key generation efficiency in a 3-layer relay network, where clusters of users are connected to the aggregation server through an intermediate layer of relays. Due to the pre-aggregation of the messag…

[2025-07-22 Tue (UTC), 15 new articles found for cs.IR Information Retrieval]
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An Information-Theoretic Intersectional Data Valuation Theory
Eduardo C. Garrido-Merch\'an
https://arxiv.org/abs/2507.14742 https://

An Information-Theoretic Intersectional Data Valuation Theory
In contemporary digital markets, personal data often reveals not just isolated traits, but complex, intersectional identities based on combinations of race, gender, disability, and other protected characteristics. This exposure generates a privacy externality: firms benefit economically from profiling, prediction, and personalization, while users face hidden costs in the form of social risk and discrimination. We introduce a formal pricing rule that quantifies and internalizes this intersection…

Information Theoretic Analysis of a Dual-Band MIMO Cellphone Antenna with ANSYS HFSS SBR
Volodymyr Shyianov, Bamelak Tadele, Vladimir I. Okhmatovski, Amine Mezghani
https://arxiv.org/abs/2507.14704

Information Theoretic Analysis of a Dual-Band MIMO Cellphone Antenna with ANSYS HFSS SBR+
Historically, the design of antenna arrays has evolved separately from Shannon theory. Shannon theory adopts a probabilistic approach in the design of communication systems, while antenna design approaches have relied on the deterministic Maxwell theory alone. In this paper, we investigate an information-theoretic analysis approach which we apply to evaluate the design of a dual-band, dual-polarized multiple-input multiple-output (MIMO) array on a cellphone. To this end, we use ANSYS HFSS, a co…

[2025-07-22 Tue (UTC), 18 new articles found for cs.IT Information Theory]
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