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Pre-trained models for Natural Languages (NL) like BERT and GPT have been recently shown to transfer well to Programming Languages (PL) and largely benefit a broad set of code-related tasks. Despite their success, most current methods…

Computation and Language · Computer Science 2021-09-03 Yue Wang , Weishi Wang , Shafiq Joty , Steven C. H. Hoi

Decoding sequences that stem from multiple transmissions of a codeword over an insertion, deletion, and substitution channel is a critical component of efficient deoxyribonucleic acid (DNA) data storage systems. In this paper, we consider a…

Information Theory · Computer Science 2020-10-30 Andreas Lenz , Issam Maarouf , Lorenz Welter , Antonia Wachter-Zeh , Eirik Rosnes , Alexandre Graell i Amat

Nowadays polar codes are becoming one of the most favorable capacity achieving error correction codes for their low encoding and decoding complexity. However, due to the large code length required by practical applications, the few existing…

Hardware Architecture · Computer Science 2011-11-04 Chuan Zhang , Bo Yuan , Keshab K. Parhi

The past few years have witnessed a growing interest in LLM-based recommender systems (RSs), although their industrial deployment remains in a preliminary stage. Most existing deployments leverage LLMs offline as feature enhancers,…

Information Retrieval · Computer Science 2025-04-30 Yunjia Xi , Hangyu Wang , Bo Chen , Jianghao Lin , Menghui Zhu , Weiwen Liu , Ruiming Tang , Zhewei Wei , Weinan Zhang , Yong Yu

Decoding strategies play a central role in shaping the reasoning ability of large language models (LLMs). Traditional methods such as greedy decoding and beam search often suffer from error propagation, while sampling-based approaches…

We propose a decoder for Trellis-Constrained Codes, a super-class of Turbo- and LDPC codes. Inspired by amplitude amplification from quantum computing, we attempt to amplify the relative likelihood of the most likely codeword until it…

Information Theory · Computer Science 2019-10-29 Christian Franck

Identifying the unknown convolutional code corresponding to the given intercepted data is an important problem in military surveillance and in wireless communication. While a variety of code identification algorithms are available in the…

Information Theory · Computer Science 2025-07-01 Harshvardhan Pandey , Pragya Khanna , Arti Yardi

We consider error decoding of locally repairable codes (LRC) and partial MDS (PMDS) codes through interleaved decoding. For a specific class of LRCs we investigate the success probability of interleaved decoding. For PMDS codes we show that…

Information Theory · Computer Science 2019-07-09 Lukas Holzbaur , Sven Puchinger , Antonia Wachter-Zeh

We present the first known efficient decoding algorithm for correcting multiple insertion-deletion errors in Helberg codes and their non-binary generalizations, extending a known algorithm for correcting multiple deletion errors.

Information Theory · Computer Science 2025-08-27 Anthony Segrest , Hieu D. Nguyen

We consider a distributed source coding system in which several observations are communicated to the decoder using limited transmission rate. The observations must be separately coded. We introduce a robust distributed coding scheme which…

Information Theory · Computer Science 2007-07-13 Jun Chen , Toby Berger

Scaling inference compute enhances reasoning in large language models (LLMs), with long chains-of-thought (CoTs) enabling strategies like backtracking and error correction. Reinforcement learning (RL) has emerged as a crucial method for…

Computation and Language · Computer Science 2025-02-06 Edward Yeo , Yuxuan Tong , Morry Niu , Graham Neubig , Xiang Yue

This paper reviews the potential channel decoding techniques for ultra-reliable low-latency communications (URLLC). URLLC is renowned for its stringent requirements including ultra-reliability, low end-to-end transmission latency, and…

Information Theory · Computer Science 2022-12-26 Chentao Yue , Vera Miloslavskaya , Mahyar Shirvanimoghaddam , Branka Vucetic , Yonghui Li

Practical random network coding based schemes for multicast include a header in each packet that records the transformation between the sources and the terminal. The header introduces an overhead that can be significant in certain…

Information Theory · Computer Science 2010-06-03 Shizheng Li , Aditya Ramamoorthy

We consider the problem of learned transform compression where we learn both, the transform as well as the probability distribution over the discrete codes. We utilize a soft relaxation of the quantization operation to allow for…

Machine Learning · Computer Science 2021-05-05 Magda Gregorová , Marc Desaules , Alexandros Kalousis

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in chart understanding tasks. However, interpreting charts with textual descriptions often leads to information loss, as it fails to fully capture the dense…

Artificial Intelligence · Computer Science 2025-07-03 Xuanle Zhao , Xianzhen Luo , Qi Shi , Chi Chen , Shuo Wang , Zhiyuan Liu , Maosong Sun

In this paper will be presented methodology of encoding information in valuations of discrete lattice with some translational invariant constrains in asymptotically optimal way. The method is based on finding statistical description of such…

Information Theory · Computer Science 2008-11-02 Jarek Duda

Data analysis and performance evaluation of simulation deduction plays a pivotal role in modern warfare, which enables military personnel to gain invaluable insights into the potential effectiveness of different strategies, tactics, and…

Computation and Language · Computer Science 2025-11-17 Shansi Zhang , Min Li

The rapid advancement of large language models (LLMs) has revolutionized code generation tasks across various programming languages. However, the unique characteristics of programming languages, particularly those like Verilog with specific…

Machine Learning · Computer Science 2025-03-19 Changran Xu , Yi Liu , Yunhao Zhou , Shan Huang , Ningyi Xu , Qiang Xu

A new approach for estimating the Decoding Error-Probability (DEP) of LT codes with dense rows is derived by using the conditional Kovalenko's rank distribution. The estimate by the proposed approach is very close to the DEP approximated by…

Information Theory · Computer Science 2009-01-19 Ki-Moon Lee , Hayder Radha , Beom-Jin Kim

We improve the method in \cite{Seidl:10} for increasing the finite-lengh performance of polar codes by protecting specific, less reliable symbols with simple outer repetition codes. Decoding of the scheme integrates easily in the known…

Information Theory · Computer Science 2013-12-11 Mathis Seidl , Johannes B. Huber