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Given a string $S$ of $n$ integers in $[0,\sigma)$, a range minimum query RMQ$(i, j)$ asks for the index of the smallest integer in $S[i \dots j]$. It is well known that the problem can be solved with a succinct data structure of size $2n +…

Data Structures and Algorithms · Computer Science 2019-05-30 Paweł Gawrychowski , Seungbum Jo , Shay Mozes , Oren Weimann

The Shortest Common Superstring (SCS) problem asks for the shortest string that contains each of a given set of strings as a substring. Its reverse-complement variant, the Shortest Common Superstring problem with Reverse Complements…

Data Structures and Algorithms · Computer Science 2026-01-23 Ryosuke Yamano , Tetsuo Shibuya

Grammar compression represents a string as a context free grammar. Achieving compression requires encoding such grammar as a binary string; there are a few commonly used encodings. We bound the size of practically used encodings for several…

Data Structures and Algorithms · Computer Science 2020-05-21 Michał Gańczorz

Tensor network contraction is a powerful computational tool in quantum many-body physics, quantum information and quantum chemistry. The complexity of contracting a tensor network is thought to mainly depend on its entanglement properties,…

Quantum Physics · Physics 2025-12-11 Jiaqing Jiang , Jielun Chen , Norbert Schuch , Dominik Hangleiter

In "Compress or Route?" (Johnson, 2026), we found that code generation tolerates aggressive prompt compression (r >= 0.6) while chain-of-thought reasoning degrades gradually. That study was limited to HumanEval (164 problems), left the…

Computation and Language · Computer Science 2026-02-19 Warren Johnson

The Shortest Common Superstring (SCS) problem is a fundamental task in sequence analysis. In genome assembly, however, the double-stranded nature of DNA implies that each fragment may occur either in its original orientation or as its…

Data Structures and Algorithms · Computer Science 2026-03-30 Ryosuke Yamano , Tetsuo Shibuya

Data subsampling is one of the most natural methods to approximate a massively large data set by a small representative proxy. In particular, sensitivity sampling received a lot of attention, which samples points proportional to an…

Data Structures and Algorithms · Computer Science 2024-06-04 Alexander Munteanu , Simon Omlor

The increasing prevalence of large language models (LLMs) such as GPT-4 in various applications has led to a surge in the size of prompts required for optimal performance, leading to challenges in computational efficiency. Prompt…

Computation and Language · Computer Science 2024-12-19 Shivam Shandilya , Menglin Xia , Supriyo Ghosh , Huiqiang Jiang , Jue Zhang , Qianhui Wu , Victor Rühle

A well-known but rarely used approach to text categorization uses conditional entropy estimates computed using data compression tools. Text affinity scores derived from compressed sizes can be used for classification and ranking tasks, but…

Machine Learning · Computer Science 2021-12-08 Nitya Kasturi , Igor L. Markov

The Longest Common Subsequence (LCS) is a fundamental string similarity measure, and computing the LCS of two strings is a classic algorithms question. A textbook dynamic programming algorithm gives an exact algorithm in quadratic time, and…

Data Structures and Algorithms · Computer Science 2023-02-13 Xiaoyu He , Ray Li

The practice of compressed sensing suffers importantly in terms of the efficiency/accuracy trade-off when acquiring noisy signals prior to measurement. It is rather common to find results treating the noise affecting the measurements,…

Numerical Analysis · Mathematics 2014-11-25 Marco Artina , Massimo Fornasier , Steffen Peter

Compressive sensing (CS) is a new methodology to capture signals at lower rate than the Nyquist sampling rate when the signals are sparse or sparse in some domain. The performance of CS estimators is analyzed in this paper using tools from…

Information Theory · Computer Science 2014-09-09 Solomon A. Tesfamicael , Bruhtesfa E. Godana , Faraz Barzideh

We study the approximation hardness of the Shortest Superstring, the Maximal Compression and the Maximum Asymmetric Traveling Salesperson (MAX-ATSP) problem. We introduce a new reduction method that produces strongly restricted instances of…

Computational Complexity · Computer Science 2012-08-28 Marek Karpinski , Richard Schmied

In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse and compressible signals. Many recovery algorithms are known to…

Information Theory · Computer Science 2014-04-29 Holger Rauhut , Justin Romberg , Joel A. Tropp

Large language models (LLMs) exhibit degraded performance under prompt compression, but the mechanisms remain poorly understood. We introduce the Compression-Decay Comprehension Test (CDCT), a benchmark that independently measures…

Computation and Language · Computer Science 2025-12-23 Rahul Baxi

We extend Ziv and Lempel's model of finite-state encoders to the realm of lossy compression of individual sequences. In particular, the model of the encoder includes a finite-state reconstruction codebook followed by an information lossless…

Information Theory · Computer Science 2024-01-04 Neri Merhav

In this paper we compare the difference in performance of two of the Prediction by Partial Matching (PPM) family of compressors (PPM$^*$ and the original Bounded PPM algorithm) and the Lempel-Ziv 78 (LZ) algorithm. We construct an infinite…

Data Structures and Algorithms · Computer Science 2021-01-21 Liam Jordon , Philippe Moser

The normalized substring complexity $\delta$ of a string is defined as $\max_k \{c[k]/k\}$, where $c[k]$ is the number of \textit{distinct} substrings of length $k$. This simply defined measure has recently attracted attention due to its…

Data Structures and Algorithms · Computer Science 2026-02-17 Gregory Kucherov , Yakov Nekrich

We investigate two closely related LZ78-based compression schemes: LZMW (an old scheme by Miller and Wegman) and LZD (a recent variant by Goto et al.). Both LZD and LZMW naturally produce a grammar for a string of length $n$; we show that…

Data Structures and Algorithms · Computer Science 2017-07-26 Golnaz Badkobeh , Travis Gagie , Shunsuke Inenaga , Tomasz Kociumaka , Dmitry Kosolobov , Simon J. Puglisi

The complexity of computing the Lempel-Ziv factorization and the set of all runs (= maximal repetitions) is studied in the decision tree model of computation over ordered alphabet. It is known that both these problems can be solved by RAM…

Data Structures and Algorithms · Computer Science 2014-09-22 Dmitry Kosolobov
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