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Large Language Models (LLMs) excel at code generation but struggle with complex problems. Retrieval-Augmented Generation (RAG) mitigates this issue by integrating external knowledge, yet retrieval models often miss relevant context, and…

Software Engineering · Computer Science 2026-01-29 Shahd Seddik , Fahd Seddik , Iman Saberi , Fatemeh Fard , Minh Hieu Huynh , Patanamon Thongtanunam

Chase-Pyndiah decoding is widely used for decoding product codes. However, this method is suboptimal and requires scaling the soft information exchanged during the iterative processing. In this paper, we propose a framework for obtaining…

Information Theory · Computer Science 2025-08-29 Andreas Straßhofer , Diego Lentner , Gianluigi Liva , Alexandre Graell i Amat

Fast SC decoding overcomes the latency caused by the serial nature of the SC decoding by identifying new nodes in the upper levels of the SC decoding tree and implementing their fast parallel decoders. In this work, we first present a novel…

We give new constructions of two classes of algebraic code families which are efficiently list decodable with small output list size from a fraction $1-R-\epsilon$ of adversarial errors where $R$ is the rate of the code, for any desired…

Computational Complexity · Computer Science 2020-11-17 Venkatesan Guruswami , Chaoping Xing

We consider a distributed learning problem in which the computation is carried out on a system consisting of a master node and multiple worker nodes. In such systems, the existence of slow-running machines called stragglers will cause a…

Information Theory · Computer Science 2019-01-16 Shunsuke Horii , Takahiro Yoshida , Manabu Kobayashi , Toshiyasu Matsushima

Autoregressive decoding strategy is a commonly used method for text generation tasks with pre-trained language models, while early-exiting is an effective approach to speedup the inference stage. In this work, we propose a novel decoding…

Computation and Language · Computer Science 2024-03-25 Yunqi Zhu , Xuebing Yang , Yuanyuan Wu , Wensheng Zhang

Deep optical images are often crowded with overlapping objects. This is especially true in the cores of galaxy clusters, where images of dozens of galaxies may lie atop one another. Accurate measurements of cluster properties require…

Instrumentation and Methods for Astrophysics · Physics 2015-12-03 Yuanyuan Zhang , Timothy A. McKay , Emmanuel Bertin , Tesla Jeltema , Christopher J. Miller , Eli Rykoff , Jeeseon Song

We introduce Reward-Guided Speculative Decoding (RSD), a novel framework aimed at improving the efficiency of inference in large language models (LLMs). RSD synergistically combines a lightweight draft model with a more powerful target…

Computation and Language · Computer Science 2025-06-27 Baohao Liao , Yuhui Xu , Hanze Dong , Junnan Li , Christof Monz , Silvio Savarese , Doyen Sahoo , Caiming Xiong

The online programing services, such as Github,TopCoder, and EduCoder, have promoted a lot of social interactions among the service users. However, the existing social interactions is rather limited and inefficient due to the rapid…

Artificial Intelligence · Computer Science 2019-03-12 Mingming Lu , Dingwu Tan , Naixue Xiong , Zailiang Chen , Haifeng Li

We present a novel algorithm that solves the turbo code LP decoding problem in a fininte number of steps by Euclidean distance minimizations, which in turn rely on repeated shortest path computations in the trellis graph representing the…

Information Theory · Computer Science 2014-03-18 Michael Helmling , Stefan Ruzika

This paper presents a stochastic algorithm for iterative error control decoding. We show that the stochastic decoding algorithm is an approximation of the sum-product algorithm. When the code's factor graph is a tree, as with trellises, the…

Information Theory · Computer Science 2007-07-13 Chris Winstead , Anthony Rapley , Vincent C. Gaudet , Christian Schlegel

Random linear network coding (RLNC) in theory achieves the max-flow capacity of multicast networks, at the cost of high decoding complexity. To improve the performance-complexity tradeoff, we consider the design of sparse network codes. A…

Information Theory · Computer Science 2016-04-20 Ye Li , Wai-Yip Chan , Steven D. Blostein

Deep neural network (DNN)-based channel decoding is widely considered in the literature. The existing solutions are investigated for the case of hard output, i.e. when the decoder returns the estimated information word. At the same time,…

Information Theory · Computer Science 2024-10-28 Dmitry Artemasov , Kirill Andreev , Pavel Rybin , Alexey Frolov

For asynchronous transmission of short blocks, preambles for packet detection contribute a non-negligible overhead. To reduce the required preamble length, joint detection and decoding (JDD) techniques have been proposed that additionally…

Information Theory · Computer Science 2025-01-29 Simon Obermüller , Jannis Clausius , Marvin Geiselhart , Stephan ten Brink

In this paper we investigate the decoding of parallel turbo codes over the binary erasure channel suited for upper-layer error correction. The proposed algorithm performs on-the-fly decoding, i.e. it starts decoding as soon as the first…

Information Theory · Computer Science 2008-03-13 Ghassan M. Kraidy , Valentin Savin

Autoregressive decoding of large language models (LLMs) is memory bandwidth bounded, resulting in high latency and significant wastes of the parallel processing power of modern accelerators. Existing methods for accelerating LLM decoding…

Machine Learning · Computer Science 2024-02-06 Yichao Fu , Peter Bailis , Ion Stoica , Hao Zhang

Two classes of turbo codes over high-order finite fields are introduced. The codes are derived from a particular protograph sub-ensemble of the (dv=2,dc=3) low-density parity-check code ensemble. A first construction is derived as a…

Information Theory · Computer Science 2016-11-17 Gianluigi Liva , Enrico Paolini , Sandro Scalise , Marco Chiani

A telecommunication system uses carriers in order to transmit information through a cable or wirelessly. If each time only one carrier is transmitted, then the system s signal will not be immune to frequency selective fading. If frequency…

Signal Processing · Electrical Eng. & Systems 2018-07-10 Spyridon K. Chronopoulos , Vasilis Christofilakis , Giorgos Tatsis , Panos Kostarakis

Product codes (PCs) and staircase codes (SCCs) are conventionally decoded based on bounded distance decoding (BDD) of the component codes and iterating between row and column decoders. The performance of iterative BDD (iBDD) can be improved…

Information Theory · Computer Science 2021-09-08 Alireza Sheikh , Alexandre Graell i Amat , Alex Alvarado

It has recently been observed that certain extremely simple feature encoding techniques are able to achieve state of the art performance on several standard image classification benchmarks including deep belief networks, convolutional nets,…

Machine Learning · Computer Science 2013-01-08 Misha Denil , Nando de Freitas
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