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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

We consider string matching with variable length gaps. Given a string $T$ and a pattern $P$ consisting of strings separated by variable length gaps (arbitrary strings of length in a specified range), the problem is to find all ending…

Data Structures and Algorithms · Computer Science 2011-10-14 Philip Bille , Inge Li Goertz , Hjalte Wedel Vildhøj , David Kofoed Wind

One of the long-standing goals in optimisation and constraint programming is to describe a problem in natural language and automatically obtain an executable, efficient model. Large language models appear to bring this vision closer,…

Artificial Intelligence · Computer Science 2025-11-20 Alessio Pellegrino , Jacopo Mauro

We analyze how symmetries can be used to compress structures (also known as interpretations) onto a smaller domain without loss of information. This analysis suggests the possibility to solve satisfiability problems in the compressed domain…

Logic in Computer Science · Computer Science 2023-12-15 Pierre Carbonnelle , Gottfried Schenner , Maurice Bruynooghe , Bart Bogaerts , Marc Denecker

An LZ-like factorization of a string divides it into factors, each being either a single character or a copy of a preceding substring. While grammar-based compression schemes support efficient random access with space linear in the…

Data Structures and Algorithms · Computer Science 2026-01-22 Hiroki Shibata , Yuto Nakashima , Yutaro Yamaguchi , Shunsuke Inenaga

We present a new on-line algorithm for computing the Lempel-Ziv factorization of a string that runs in $O(N\log N)$ time and uses only $O(N\log\sigma)$ bits of working space, where $N$ is the length of the string and $\sigma$ is the size of…

Data Structures and Algorithms · Computer Science 2013-05-28 Jun'ichi Yamamoto , Tomohiro I , Hideo Bannai , Shunsuke Inenaga , Masayuki Takeda

Suffix trees are key and efficient data structure for solving string problems. A suffix tree is a compressed trie containing all the suffixes of a given text of length $n$ with a linear construction cost. In this work, we introduce an…

Data Structures and Algorithms · Computer Science 2024-06-04 Anas Al-okaily

Suffix tree (and the closely related suffix array) are fundamental structures capturing all substrings of a given text essentially by storing all its suffixes in the lexicographical order. In some applications, we work with a subset of $b$…

Data Structures and Algorithms · Computer Science 2016-08-03 Paweł Gawrychowski , Tomasz Kociumaka

A border of a string is a non-empty proper prefix of the string that is also a suffix. A string is unbordered if it has no border. The longest unbordered factor is a fundamental notion in stringology, closely related to string periodicity.…

Data Structures and Algorithms · Computer Science 2025-07-23 Shoma Sekizaki , Takuya Mieno

Let $S$ be a string of length $n$ over an alphabet $\Sigma$ and let $Q$ be a subset of $\Sigma$ of size $q \geq 2$. The 'co-occurrence problem' is to construct a compact data structure that supports the following query: given an integer $w$…

Data Structures and Algorithms · Computer Science 2022-11-11 Philip Bille , Inge Li Gørtz , Tord Stordalen

As large language models (LLMs) continue to be deployed and utilized across domains, the volume of LLM-generated data is growing rapidly. This trend highlights the increasing importance of effective and lossless compression for such data in…

Machine Learning · Computer Science 2025-05-13 Yu Mao , Holger Pirk , Chun Jason Xue

Long prompt leads to huge hardware costs when using transformer-based Large Language Models (LLMs). Unfortunately, many tasks, such as summarization, inevitably introduce long documents, and the wide application of in-context learning…

Computation and Language · Computer Science 2024-09-04 Jun Gao , Ziqiang Cao , Wenjie Li

We address the problem of efficiently gathering correlated data from a wired or a wireless sensor network, with the aim of designing algorithms with provable optimality guarantees, and understanding how close we can get to the known…

Networking and Internet Architecture · Computer Science 2009-08-03 Jian Li , Amol Deshpande , Samir Khuller

Text compression for large language model (LLM) systems is usually framed as token deletion, retrieval, summarization, or exact reconstruction. We study a more aggressive but explicitly lossy setting: compress text into compact codes that…

Machine Learning · Computer Science 2026-05-26 Natalia Trukhina , Vadim Vashkelis

Recent work has shown that scaling large language models (LLMs) improves their alignment with human brain activity, yet it remains unclear what drives these gains and which representational properties are responsible. Although larger models…

Natural language generation (NLG) spans a broad range of tasks, each of which serves for specific objectives and desires different properties of generated text. The complexity makes automatic evaluation of NLG particularly challenging.…

Computation and Language · Computer Science 2022-01-25 Mingkai Deng , Bowen Tan , Zhengzhong Liu , Eric P. Xing , Zhiting Hu

Compression refers to encoding data using bits, so that the representation uses as few bits as possible. Compression could be lossless: i.e. encoded data can be recovered exactly from its representation) or lossy where the data is…

Information Theory · Computer Science 2012-10-19 Narayana Santhanam , Dharmendra Modha

The longest common subsequence (LCS) is a fundamental problem in string processing which has numerous algorithmic studies, extensions, and applications. A sequence $u_1, \ldots, u_f$ of $f$ strings s said to be an ($f$-)segmentation of a…

Data Structures and Algorithms · Computer Science 2025-02-27 Yuki Yonemoto , Takuya Mieno , Shunsuke Inenaga , Ryo Yoshinaka , Ayumi Shinohara

The rapid growth of large language models (LLMs) presents significant deployment challenges due to their massive computational and memory demands. While model compression, such as network pruning, offers potential solutions, most existing…

Machine Learning · Computer Science 2026-04-07 Ziwei Li , Yuang Ma , Yi Kang

We consider the problem of computing the q-gram profile of a string \str of size $N$ compressed by a context-free grammar with $n$ production rules. We present an algorithm that runs in $O(N-\alpha)$ expected time and uses $O(n+q+\kq)$…

Data Structures and Algorithms · Computer Science 2014-06-09 Philip Bille , Patrick Hagge Cording , Inge Li Gørtz
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