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Minimum Bayes Risk (MBR) decoding optimizes output selection by maximizing the expected utility value of an underlying human distribution. While prior work has shown the effectiveness of MBR decoding through empirical evaluation, few…

Computation and Language · Computer Science 2025-06-23 Yuki Ichihara , Yuu Jinnai , Kaito Ariu , Tetsuro Morimura , Eiji Uchibe

An index code for broadcast channel with receiver side information is locally decodable if each receiver can decode its demand by observing only a subset of the transmitted codeword symbols instead of the entire codeword. Local decodability…

Information Theory · Computer Science 2020-07-31 Lakshmi Natarajan , Prasad Krishnan , V. Lalitha , Hoang Dau

Codes based on sparse matrices have good performance and can be efficiently decoded by belief-propagation (BP). Decoding binary stabilizer codes needs a quaternary BP for (additive) codes over GF(4), which has a higher check-node complexity…

Quantum Physics · Physics 2021-03-10 Kao-Yueh Kuo , Ching-Yi Lai

This work develops a rate-distortion-based approach to stochastic Chase decoding of algebraic codes over binary memoryless symmetric (BMS) channels, replacing the heuristics traditionally used to determine flip probabilities with…

Information Theory · Computer Science 2026-05-20 Amit Berman , Ariel Doubchak , Uri Erez , Tal Philosof , Ilya Shapir

Locally repairable codes (LRCs) were originally introduced to enable efficient recovery from erasures in distributed storage systems by accessing only a small number of other symbols. While their structural properties-such as bounds and…

Information Theory · Computer Science 2026-02-23 Hoang Ly , Emina Soljanin , Philip Whiting

Large language models (LLMs) have shown remarkable ability to generate code, yet their outputs often violate syntactic or semantic constraints when guided only through natural language prompts. We introduce TreeCoder, the most general and…

Machine Learning · Computer Science 2026-04-27 Henrijs Princis , Arindam Sharma , Cristina David

The security of code-based cryptography relies primarily on the hardness of decoding generic linear codes. Until very recently, all the best algorithms for solving the decoding problem were information set decoders (ISD). However, recently…

Cryptography and Security · Computer Science 2023-12-04 Kévin Carrier , Thomas Debris-Alazard , Charles Meyer-Hilfiger , Jean-Pierre Tillich

We introduce a new family of concatenated codes with an outer low-density parity-check (LDPC) code and an inner low-density generator matrix (LDGM) code, and prove that these codes can achieve capacity under any memoryless binary-input…

Information Theory · Computer Science 2016-08-31 Chun-Hao Hsu , Achilleas Anastasopoulos

In this paper, we construct protograph-based spatially coupled low-density parity-check (SC-LDPC) codes by coupling together a series of L disjoint, or uncoupled, LDPC code Tanner graphs into a single coupled chain. By varying L, we obtain…

Information Theory · Computer Science 2016-11-17 David G. M. Mitchell , Michael Lentmaier , Daniel J. Costello

Polar codes are a family of capacity-achieving codes that have explicit and low-complexity construction, encoding, and decoding algorithms. Decoding of polar codes is based on the successive-cancellation decoder, which decodes in a bit-…

Information Theory · Computer Science 2018-03-06 Boaz Shuval , Ido Tal

Reed-Muller (RM) codes exhibit good performance under maximum-likelihood (ML) decoding due to their highly-symmetric structure. In this paper, we explore the question of whether the code symmetry of RM codes can also be exploited to achieve…

Information Theory · Computer Science 2018-04-30 Elia Santi , Christian Häger , Henry D. Pfister

Kitaev's toric code is one of the most prominent models for fault-tolerant quantum computation, currently regarded as the leading solution for connectivity constrained quantum technologies. Significant effort has been recently devoted to…

Quantum Physics · Physics 2026-03-26 Julien du Crest , Mehdi Mhalla , Valentin Savin

We introduce Decision Tree Decoders (DTDs), which rely only on the sparsity of the binary check matrix, making them broadly applicable for decoding any quantum low-density parity-check (qLDPC) code and fault-tolerant quantum circuits. DTDs…

Quantum Physics · Physics 2025-02-25 Kai R. Ott , Bence Hetényi , Michael E. Beverland

In this paper, we propose a linear complexity encoding method for arbitrary LDPC codes. We start from a simple graph-based encoding method ``label-and-decide.'' We prove that the ``label-and-decide'' method is applicable to Tanner graphs…

Information Theory · Computer Science 2016-11-18 Jin Lu , José M. F. Moura

Efficient text embedding is crucial for large-scale natural language processing (NLP) applications, where storage and computational efficiency are key concerns. In this paper, we explore how using binary representations (barcodes) instead…

Computation and Language · Computer Science 2025-07-24 Soumen Sinha , Shahryar Rahnamayan , Azam Asilian Bidgoli

The Consultative Committee for Space Data Systems (CCSDS) 141.11-O-1 Line Product Code (LPC) provides a rare opportunity to compare maximum-likelihood decoding and message passing. The LPC considered in this paper is intended to serve as…

Information Theory · Computer Science 2021-11-16 Jonathan Nguyen , Linfang Wang , Chester Hulse , Sahil Dani , Amaael Antonini , Todd Chauvin , Divsalar Dariush , Richard Wesel

A low-complexity tree search approach is presented that achieves the maximum-likelihood (ML) decoding performance of Reed-Muller (RM) codes. The proposed approach generates a bit-flipping tree that is traversed to find the ML decoding…

Information Theory · Computer Science 2021-07-20 Seyyed Ali Hashemi , Nghia Doan , Warren J. Gross , John Cioffi , Andrea Goldsmith

The min-sum (MS) algorithm is arguably the second most fundamental algorithm in the realm of message passing due to its optimality (for a tree code) with respect to the {\em block error} probability \cite{Wiberg}. There also seems to be a…

Information Theory · Computer Science 2007-07-13 Kapil Bhattad , Vishwambhar Rathi , Ruediger Urbanke

We present a general framework for derandomizing random linear codes with respect to a broad class of properties, known as local properties, which encompass several standard notions such as distance, list-decoding, list-recovery, and…

Information Theory · Computer Science 2025-11-21 Fernando Granha Jeronimo , Nikhil Shagrithaya

In this paper, we study codes with sparse generator matrices. More specifically, low-density generator matrix (LDGM) codes with a certain constraint on the weight of the columns in the generator matrix are considered. In this paper, it is…

Information Theory · Computer Science 2022-06-28 James Chin-Jen Pang , Hessam Mahdavifar , S. Sandeep Pradhan