Tootfinder

They are opening a new Irish pub, sorry "Irish" pub near work, and they've given it an extremely traditional Celtic name of ... *checks notes* ... the Salmon of Knowledge.
Blimey, apparently the Salmon of Knowledge is a thing in Celtic mythology. Every day's a school day! Thank you to @…

Decoding Algorithms for Twisted GRS Codes
Guanghui Zhang, Liren Lin, Bocong Chen
https://arxiv.org/abs/2508.03552 https://arxiv.org/pdf/2508.03552

Decoding Algorithms for Twisted GRS Codes
Twisted generalized Reed-Solomon (TGRS) codes were introduced to extend the algebraic capabilities of classical generalized Reed-Solomon (GRS) codes. This extension holds the potential for constructing new non-GRS maximum distance separable (MDS) codes and enhancing cryptographic security. It is known that TGRS codes with $1$ twist can either be MDS or near-MDS. In this paper, we employ the Gaussian elimination method to propose new decoding algorithms for MDS TGRS codes with parameters $[n,k,n…

Non-Reed-Solomon Type MDS Codes from Elliptic Curves
Puyin Wang, Wei Liu, Jinquan Luo, Dengxin Zhai
https://arxiv.org/abs/2509.04247 https://arxiv.org/pdf/…

Non-Reed-Solomon Type MDS Codes from Elliptic Curves
In this paper, we present a new family of MDS codes derived from elliptic curves. These codes attain lengths close to the theoretical maximum and are provably inequivalent to Reed-Solomon (RS) codes. Unlike many previous constructions that rely on the point at infinity, our approach allows for more general choices: we consider divisors supported on affine points and divisors consisting of multiple distinct points. This broader framework enables the construction of codes with length approximatel…

Are LLMs ready to help non-expert users to make charts of official statistics data?
Gadir Suleymanli, Alexander Rogiers, Lucas Lageweg, Jefrey Lijffijt
https://arxiv.org/abs/2510.01197

Are LLMs ready to help non-expert users to make charts of official statistics data?
In this time when biased information, deep fakes, and propaganda proliferate, the accessibility of reliable data sources is more important than ever. National statistical institutes provide curated data that contain quantitative information on a wide range of topics. However, that information is typically spread across many tables and the plain numbers may be arduous to process. Hence, this open data may be practically inaccessible. We ask the question "Are current Generative AI models capable …

High-Resolution Sensing in Communication-Centric ISAC: Deep Learning and Parametric Methods
Salmane Naoumi, Ahmad Bazzi, Roberto Bomfin, Marwa Chafii
https://arxiv.org/abs/2509.02137

High-Resolution Sensing in Communication-Centric ISAC: Deep Learning and Parametric Methods
This paper introduces two novel algorithms designed to address the challenge of super-resolution sensing parameter estimation in bistatic configurations within communication-centric integrated sensing and communication (ISAC) systems. Our approach leverages the estimated channel state information derived from reference symbols originally intended for communication to achieve super-resolution sensing parameter estimation. The first algorithm, IFFT-C2VNN, employs complex-valued convolutional neur…

A view toward smooth geometry of Sklyanin algebras
Karol Herrera, Sebasti\'an Higuera, Andr\'es Rubiano
https://arxiv.org/abs/2507.19719 https://ar…

A view toward smooth geometry of Sklyanin algebras
We study the differential smoothness of Sklyanin algebras in three and four variables. We show that all non-degenerate three-dimensional cases are differentially smooth, while none of the four-dimensional Sklyanin algebras admit a connected integrable differential calculus of suitable dimension.

Evaluating the effect of different non-informative prior specifications on the Bayesian proportional odds model in randomised controlled trials: a simulation study
Chris J. Selman, Katherine J. Lee, Michael Dymock, Ian C. Marschner, Steven Y. C. Tong, Mark Jones, Robert K. Mahar
https://arxiv.org/abs/2507.21491

Evaluating the effect of different non-informative prior specifications on the Bayesian proportional odds model in randomised controlled trials: a simulation study
Background: Ordinal outcomes combine multiple distinct ordered patient states into a single endpoint and are commonly analysed using proportional odds (PO) models in clinical trials. When using a Bayesian approach, it is not obvious what the influence of a 'non-informative' prior is in the analysis of a fixed design or on early stopping decisions in adaptive designs. Methods: This study compares different non-informative prior specifications for the Bayesian PO model in the context of both a …

Properties and Decoding of Twisted GRS Codes and Their Extensions
Yang Li, Martianus Frederic Ezerman, Huimin Lao, San Ling
https://arxiv.org/abs/2508.02382 https://

Properties and Decoding of Twisted GRS Codes and Their Extensions
Maximum distance separable (MDS) codes that are not equivalent to generalized Reed-Solomon (GRS) codes are called non-GRS MDS codes. Alongside near MDS (NMDS) codes, they are applicable in communication, cryptography, and storage systems. From theoretical perspective, it is particularly intriguing to investigate families of linear codes in which each element can be determined to be either a non-GRS MDS or an NMDS code. Two promising candidates for such families emerge from what is known as twis…

Construction of non-generalized Reed-Solomon MDS codes based on systematic generator matrix
Shengwei Liu, Hongwei Liu, Bocong Chen
https://arxiv.org/abs/2507.20559 https://

Construction of non-generalized Reed-Solomon MDS codes based on systematic generator matrix
Maximum distance separable (MDS) codes are considered optimal because the minimum distance cannot be improved for a given length and code size. The most prominent MDS codes are likely the generalized Reed-Solomon (GRS) codes. In 1989, Roth and Lempel constructed a type of MDS code that is not a GRS code (referred to as non-GRS). In 2017, Beelen et al. introduced twisted Reed-Solomon (TRS) codes and demonstrated that many MDS TRS codes are indeed non-GRS. Following this, the definition of TRS co…

Learning to Ask: Decision Transformers for Adaptive Quantitative Group Testing
Mahdi Soleymani, Tara Javidi
https://arxiv.org/abs/2509.01723 https://arxiv.…

Learning to Ask: Decision Transformers for Adaptive Quantitative Group Testing
We consider the problem of quantitative group testing (QGT), where the goal is to recover a sparse binary vector from aggregate subset-sum queries: each query selects a subset of indices and returns the sum of those entries. Information-theoretic results suggest that adaptivity could yield up to a twofold reduction in the total number of required queries, yet no algorithm has surpassed the non-adaptive bound, leaving its practical benefit an open question. In this paper, we reduce the QGT probl…