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Chain-of-Thought (CoT) prompting has significantly enhanced the reasoning abilities of large language models. However, recent studies have shown that models can still perform complex reasoning tasks even when the CoT is replaced with…

Computation and Language · Computer Science 2024-12-09 Aryasomayajula Ram Bharadwaj

The source coding problem with action-dependent side information at the decoder has recently been introduced to model data acquisition in resource-constrained systems. In this paper, an efficient algorithm for numerical computation of the…

Information Theory · Computer Science 2016-08-11 Kasper Fløe Trillingsgaard , Osvaldo Simeone , Petar Popovski , Torben Larsen

In this paper, we employ the linear systems representation of a convolutional code to develop a decoding algorithm for convolutional codes over the erasure channel. We study the decoding problem using the state space description and this…

Information Theory · Computer Science 2020-08-21 Julia Lieb , Joachim Rosenthal

In this article we extend the idea of Turbo codes onto the Real Field. The channel is taken to result in block erasures and the only noise as being that due to quantization. The decoding in this case is reduced to reconstruction of the lost…

Combinatorics · Mathematics 2007-05-23 Animesh Datta

For efficient application of protons and light ions in radiotherapy, detailed knowledge and realistic models of the corresponding radiobiological mechanism are necessary. Basic characteristics of this mechanism have been represented within…

Biological Physics · Physics 2007-05-23 Pavel Kundrat , Hana Hromcikova , Milos Lokajicek

In this paper, we introduce a new way of constructing and decoding multipermutation codes. Multipermutations are permutations of a multiset that generally consist of duplicate entries. We first introduce a class of binary matrices called…

Information Theory · Computer Science 2015-07-29 Xishuo Liu , Stark C. Draper

Tools for rewriting, refactoring and optimizing code should be fast and correct. Large language models (LLMs), by their nature, possess neither of these qualities. Yet, there remains tremendous opportunity in using LLMs to improve code. We…

Machine Learning · Computer Science 2024-10-14 Chris Cummins , Volker Seeker , Jordi Armengol-Estapé , Aram H. Markosyan , Gabriel Synnaeve , Hugh Leather

Consider two remote nodes (encoder and decoder), each with a binary sequence. The encoder's sequence $X$ differs from the decoder's sequence $Y$ by a small number of edits (deletions and insertions). The goal is to construct a message $M$,…

Information Theory · Computer Science 2020-10-28 Mahed Abroshan , Ramji Venkataramanan , Albert Guillen i Fabregas

This paper considers the multiple-access relay channel in a setting where two source nodes transmit packets to a destination node, both directly and via a relay node, over packet erasure channels. Intra-session network coding is used at the…

Information Theory · Computer Science 2022-03-08 Amjad Saeed Khan , Ioannis Chatzigeorgiou

Interior-point algorithms constitute a very interesting class of algorithms for solving linear-programming problems. In this paper we study efficient implementations of such algorithms for solving the linear program that appears in the…

Information Theory · Computer Science 2008-02-12 Pascal O. Vontobel

Cellular signal transduction usually involves activation cascades, the sequential activation of a series of proteins following the reception of an input signal. Here we study the classic model of weakly activated cascades and obtain…

Molecular Networks · Quantitative Biology 2016-09-15 Mariano Beguerisse-Diaz , Radhika Desikan , Mauricio Barahona

This paper delves into the intricacies of code summarization using advanced transformer-based language models. Through empirical studies, we evaluate the efficacy of code summarization by altering function and variable names to explore…

Machine Learning · Computer Science 2023-10-30 Debanjan Mondal , Abhilasha Lodha , Ankita Sahoo , Beena Kumari

In this work, we develop a reduced complexity maximum likelihood (ML) decoder for quantum low-density parity-check (QLDPC) codes over erasures. Our decoder combines classical inactivation decoding, which integrates peeling with symbolic…

Information Theory · Computer Science 2026-01-21 Giulio Pech , Mert Gökduman , Hanwen Yao , Henry D. Pfister

Undetected errors are important for linear codes, which are the only type of errors after hard decision and automatic-repeat-request (ARQ), but do not receive much attention on their correction. In concatenated channel coding, suboptimal…

Information Theory · Computer Science 2019-01-09 Jingzhao Wang , Yuan Luo

We explore the possibility of improving probabilistic models in structured prediction. Specifically, we combine the models with constrained decoding approaches in the context of token classification for information extraction. The decoding…

Computation and Language · Computer Science 2023-12-07 Arthur Hemmer , Mickaël Coustaty , Nicola Bartolo , Jérôme Brachat , Jean-Marc Ogier

Recently, techniques such as explicit structured reasoning have demonstrated strong test-time scaling behavior by enforcing a separation between the model's internal "thinking" process and the final response. A key factor influencing answer…

Machine Learning · Computer Science 2025-06-10 Roy Eisenstadt , Itamar Zimerman , Lior Wolf

This technical report describes the design and training of novel speculative decoding draft models, for accelerating the inference speeds of large language models in a production environment. By conditioning draft predictions on both…

Computation and Language · Computer Science 2024-06-10 Davis Wertheimer , Joshua Rosenkranz , Thomas Parnell , Sahil Suneja , Pavithra Ranganathan , Raghu Ganti , Mudhakar Srivatsa

In this paper, our aim is to propose a model for code abstraction, based on abstract interpretation, allowing us to improve the precision of a recently proposed static analysis by abstract interpretation of dynamic languages. The problem we…

Software Engineering · Computer Science 2021-09-08 Isabella Mastroeni , Vincenzo Arceri

Multiple heads decoding accelerates the inference of Large Language Models (LLMs) by predicting next several tokens simultaneously. It generates and verifies multiple candidate sequences in parallel via tree attention with a fixed…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Zhendong Zhang

Despite strong performance on a variety of tasks, neural sequence models trained with maximum likelihood have been shown to exhibit issues such as length bias and degenerate repetition. We study the related issue of receiving…

Machine Learning · Computer Science 2020-10-06 Sean Welleck , Ilia Kulikov , Jaedeok Kim , Richard Yuanzhe Pang , Kyunghyun Cho