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Speculative Decoding (SD) accelerates inference in large language models by using a smaller draft model to propose tokens, which are then verified by a larger target model. However, the throughput gains of SD are fundamentally limited by a…

Computation and Language · Computer Science 2025-10-16 Sanghyun Byun , Mohanad Odema , Jung Ick Guack , Baisub Lee , Jacob Song , Woo Seong Chung

We introduce a novel soft-aided hard-decision decoder for product codes adopting bit marking via updated reliabilities at each decoding iteration. Gains up to 0.8 dB vs. standard iterative bounded distance decoding and up to 0.3 dB vs. our…

Information Theory · Computer Science 2019-06-25 Gabriele Liga , Alireza Sheikh , Alex Alvarado

New soft- and hard decision decoding algorithms are presented for general Reed-Muller codes $\left\{\genfrac{}{}{0pt}{}{m}{r}\right\} $ of length $2^{m}$ and distance $2^{m-r}$. We use Plotkin $(u,u+v)$ construction and decompose code…

Information Theory · Computer Science 2017-03-17 Ilya Dumer

Automatic speech recognition (ASR) systems often encounter difficulties in accurately recognizing rare words, leading to errors that can have a negative impact on downstream tasks such as keyword spotting, intent detection, and text…

Artificial Intelligence · Computer Science 2023-10-10 Jiajun He , Zekun Yang , Tomoki Toda

Neural-network decoders can achieve a lower logical error rate compared to conventional decoders, like minimum-weight perfect matching, when decoding the surface code. Furthermore, these decoders require no prior information about the…

Quantum Physics · Physics 2025-07-30 Boris M. Varbanov , Marc Serra-Peralta , David Byfield , Barbara M. Terhal

Folded Reed-Solomon codes, introduced by Guruswami and Rudra in 2007, have been shown to achieve the information-theoretically best possible trade-off between the rate of a code and the error-correction radius. In 2024, Bergamaschi,…

Information Theory · Computer Science 2026-05-12 Gretchen L. Matthews , Julia Shapiro

In this work, lossy distributed compression of pairs of correlated sources is considered. Conventionally, Shannon's random coding arguments -- using randomly generated unstructured codebooks whose blocklength is taken to be asymptotically…

Information Theory · Computer Science 2020-10-21 Farhad Shirani , S. Sandeep Pradhan

This paper proposes a novel maximum-likelihood (ML) soft-decision decoding framework for linear block codes, termed error-building decoding (EBD). The complete decoding process can be performed using only the parity-check matrix, without…

Information Theory · Computer Science 2026-01-06 Guoda Qiu , Ling Liu , Yuejun Wei , Liping Li

The classical family of $[n,k]_q$ Reed-Solomon codes over a field $\F_q$ consist of the evaluations of polynomials $f \in \F_q[X]$ of degree $< k$ at $n$ distinct field elements. In this work, we consider a closely related family of codes,…

Information Theory · Computer Science 2015-03-19 Venkatesan Guruswami , Carol Wang

We provide a rigorous mathematical analysis of two communication strategies: soft decode-and-forward (soft-DF) for relay channels, and soft partial interference-cancelation (soft-IC) for interference channels. Both strategies involve soft…

Information Theory · Computer Science 2016-11-18 Amir Bennatan , Shlomo Shamai , A. Robert Calderbank

Maximum-likelihood decoding is one of the central algorithmic problems in coding theory. It has been known for over 25 years that maximum-likelihood decoding of general linear codes is NP-hard. Nevertheless, it was so far unknown whether…

Computational Complexity · Computer Science 2007-07-16 Venkatesan Guruswami , Alexander Vardy

We introduce a novel universal soft-decision decoding algorithm for binary block codes called ordered reliability direct error pattern testing (ORDEPT). Our results, obtained for a variety of popular short high-rate codes, demonstrate that…

Information Theory · Computer Science 2023-10-19 Reza Hadavian , Xiaoting Huang , Dmitri Truhachev , Kamal El-Sankary , Hamid Ebrahimzad , Hossein Najafi

Modern applications are driving demand for ultra-reliable low-latency communications, rekindling interest in the performance of short, high-rate error correcting codes. To that end, here we introduce a soft-detection variant of Guessing…

Information Theory · Computer Science 2021-06-16 Ken R. Duffy

Auditory attention decoding (AAD) aims to extract from brain activity the attended speaker amidst candidate speakers, offering promising applications for neuro-steered hearing devices and brain-computer interfacing. This pilot study makes a…

Neurons and Cognition · Quantitative Biology 2024-10-15 H. A. Scheppink , S. Ahmadi , P. Desain , M. Tangermann , J. Thielen

Guessing random additive noise decoding (GRAND) is a noise-centric decoding method, which is suitable for ultra-reliable low-latency communications, as it supports high-rate error correction codes that generate short-length codewords. GRAND…

Information Theory · Computer Science 2022-12-12 Ioannis Chatzigeorgiou , Francisco A. Monteiro

Recursive decoding techniques are considered for Reed-Muller (RM) codes of growing length $n$ and fixed order $r.$ An algorithm is designed that has complexity of order $n\log n$ and corrects most error patterns of weight up to…

Information Theory · Computer Science 2017-03-17 Ilya Dumer

A construction using the E8 lattice and Reed-Solomon codes for error-correction in flash memory is given. Since E8 lattice decoding errors are bursty, a Reed-Solomon code over GF($2^8$) is well suited. This is a type of coded modulation,…

Information Theory · Computer Science 2011-02-17 Brian M. Kurkoski

The repair bandwidth of a code is the minimum amount of data required to repair one or several failed nodes (erasures). For MDS codes, the repair bandwidth is bounded below by the so-called cut-set bound, and codes that meet this bound with…

Information Theory · Computer Science 2017-10-20 Min Ye , Alexander Barg

This paper studies the parameters for which Reed-Muller (RM) codes over $GF(2)$ can correct random erasures and random errors with high probability, and in particular when can they achieve capacity for these two classical channels.…

Information Theory · Computer Science 2014-11-18 Emmanuel Abbe , Amir Shpilka , Avi Wigderson

We construct an explicit family of linear rank-metric codes over any field ${\mathbb F}_h$ that enables efficient list decoding up to a fraction $\rho$ of errors in the rank metric with a rate of $1-\rho-\epsilon$, for any desired $\rho \in…

Information Theory · Computer Science 2013-12-03 Venkatesan Guruswami , Carol Wang
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