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Compressed indexing is a powerful technique that enables efficient querying over data stored in compressed form, significantly reducing memory usage and often accelerating computation. While extensive progress has been made for…

Data Structures and Algorithms · Computer Science 2025-10-23 Rajat De , Dominik Kempa

Efficient and consistent string processing is critical in the exponentially growing genomic data era. Locally Consistent Parsing (LCP) addresses this need by partitioning an input genome string into short, exactly matching substrings (e.g.,…

In this study, we propose a simple and effective preprocessing method for subword segmentation based on a data compression algorithm. Compression-based subword segmentation has recently attracted significant attention as a preprocessing…

Computation and Language · Computer Science 2023-03-02 Keita Nonaka , Kazutaka Yamanouchi , Tomohiro I , Tsuyoshi Okita , Kazutaka Shimada , Hiroshi Sakamoto

The most fundamental problem considered in algorithms for text processing is pattern matching: given a pattern $p$ of length $m$ and a text $t$ of length $n$, does $p$ occur in $t$? Multiple versions of this basic question have been…

Data Structures and Algorithms · Computer Science 2021-11-10 Moses Ganardi , Paweł Gawrychowski

This letter presents a recursive technique to synthesize the array factor (AF) of a concentric ring array. In this method, first, the problem is modeled using the traditional least square method (LSM). In the second step, a recursive…

Signal Processing · Electrical Eng. & Systems 2023-06-13 Atefe Akbari-Bardaskan

Relative compression, where a set of similar strings are compressed with respect to a reference string, is a very effective method of compressing DNA datasets containing multiple similar sequences. Relative compression is fast to perform…

Quantitative Methods · Quantitative Biology 2011-06-21 Shanika Kuruppu , Simon Puglisi , Justin Zobel

Despite strong performance in many sequence-to-sequence tasks, autoregressive models trained with maximum likelihood estimation suffer from exposure bias, i.e. the discrepancy between the ground-truth prefixes used during training and the…

Computation and Language · Computer Science 2023-01-11 Michalis Korakakis , Andreas Vlachos

Highly-concurrent system models with vast state spaces like Chemical Reaction Networks (CRNs) that model biological and chemical systems pose a formidable challenge to cutting-edge formal analysis tools. Although many symbolic approaches…

Data Structures and Algorithms · Computer Science 2025-12-22 Landon Taylor , Joshua Jeppson , Ahmed Irfan , Lukas Buecherl , Chris Myers , Zhen Zhang

Large Language Models (LLMs) have achieved remarkable performance across a wide range of Natural Language Processing (NLP) tasks. However, in long-context scenarios, they face two challenges: high computational cost and information…

Computation and Language · Computer Science 2026-02-10 Jiwei Tang , Zhicheng Zhang , Shunlong Wu , Jingheng Ye , Lichen Bai , Zitai Wang , Tingwei Lu , Lin Hai , Yiming Zhao , Hai-Tao Zheng , Hong-Gee Kim

In recent years, RDF has gained popularity as a format for the standardized publication and exchange of information in the Web of Data. In this paper we introduce RDFCSA, a data structure that is able to self-index an RDF dataset in small…

Data Structures and Algorithms · Computer Science 2024-10-30 Nieves R. Brisaboa , Ana Cerdeira-Pena , Guillermo de Bernardo , Antonio Fariña , Gonzalo Navarro

In this paper we provide an extended formulation for the class of constraint satisfaction problems and prove that its size is polynomial for instances whose constraint graph has bounded treewidth. This implies new upper bounds on extension…

Computational Complexity · Computer Science 2015-04-29 Petr Kolman , Martin Koutecký

In the minimum common string partition (MCSP) problem two related input strings are given. "Related" refers to the property that both strings consist of the same set of letters appearing the same number of times in each of the two strings.…

Data Structures and Algorithms · Computer Science 2017-02-02 Christian Blum , Günther R. Raidl

Relational queries, and in particular join queries, often generate large output results when executed over a huge dataset. In such cases, it is often infeasible to store the whole materialized output if we plan to reuse it further down a…

Databases · Computer Science 2018-03-28 Shaleen Deep , Paraschos Koutris

Large Language Models (LLMs) have demonstrated remarkable proficiency in language comprehension and generation; however, their widespread adoption is constrained by substantial bandwidth and computational demands. While pruning and low-rank…

Computation and Language · Computer Science 2025-10-31 Zeliang Zong , Kai Zhang , Zheyang Li , Wenming Tan , Ye Ren , Yiyan Zhai , Jilin Hu

Recently, a plethora of works have proposed inference-time algorithms (e.g. best-of-n), which incorporate verifiers to assist the generation process. Their quality-efficiency trade-offs have been empirically benchmarked on a variety of…

Computation and Language · Computer Science 2025-06-09 Edoardo Botta , Yuchen Li , Aashay Mehta , Jordan T. Ash , Cyril Zhang , Andrej Risteski

Let $\Sigma$ and $\Pi$ be disjoint alphabets, respectively called the static alphabet and the parameterized alphabet. Two strings $x$ and $y$ over $\Sigma \cup \Pi$ of equal length are said to parameterized match (p-match) if there exists a…

Data Structures and Algorithms · Computer Science 2021-02-05 Noriki Fujisato , Yuto Nakashima , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

Various grammar compression algorithms have been proposed in the last decade. A grammar compression is a restricted CFG deriving the string deterministically. An efficient grammar compression develops a smaller CFG by finding duplicated…

Data Structures and Algorithms · Computer Science 2016-09-01 Shouhei Fukunaga , Yoshimasa Takabatake , I Tomohiro , Hiroshi Sakamoto

Constrained decoding enables Language Models (LMs) to produce samples that provably satisfy hard constraints. However, existing constrained-decoding approaches often distort the underlying model distribution, a limitation that is especially…

Artificial Intelligence · Computer Science 2025-06-09 Emmanuel Anaya Gonzalez , Sairam Vaidya , Kanghee Park , Ruyi Ji , Taylor Berg-Kirkpatrick , Loris D'Antoni

We introduce a new symbolic representation based on an original generalization of counter abstraction. Unlike classical counter abstraction (used in the analysis of parameterized systems with unordered or unstructured topologies) the new…

Logic in Computer Science · Computer Science 2015-03-20 Ahmed Rezine

For many kinds of prefix-free codes there are efficient and compact alternatives to the traditional tree-based representation. Since these put the codes into canonical form, however, they can only be used when we can choose the order in…

Data Structures and Algorithms · Computer Science 2021-04-02 Antonio Fariña , Travis Gagie , Szymon Grabowski , Giovanni Manzini , Gonzalo Navarro , Alberto Ordóñez
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