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A new class of distances appropriate for measuring similarity relations between sequences, say one type of similarity per distance, is studied. We propose a new ``normalized information distance'', based on the noncomputable notion of…

Computational Complexity · Computer Science 2011-11-09 Ming Li , Xin Chen , Xin Li , Bin Ma , Paul Vitanyi

We define a metric on $\mathbb{F}_q^n$ using the linear complexity of finite sequences. We will then develop a coding theory for this metric. We will give a Singleton-like bound and we will give constructions of subspaces of…

Information Theory · Computer Science 2018-03-19 Tovohery Randrianarisoa

Given a set X of finite strings, one interesting question to ask is whether there exists a member of X which is simple conditional to all other members of X. Conditional simplicity is measured by low conditional Kolmogorov complexity. We…

Computational Complexity · Computer Science 2021-02-09 Samuel Epstein

In this paper we study the computational complexity of the (extended) minimum cost homomorphism problem (Min-Cost-Hom) as a function of a constraint language, i.e. a set of constraint relations and cost functions that are allowed to appear…

Computational Complexity · Computer Science 2013-10-01 Hannes Uppman

Described are two algorithms to find long approximate palindromes in a string, for example a DNA sequence. A simple algorithm requires O(n)-space and almost always runs in $O(k.n)$-time where n is the length of the string and k is the…

Data Structures and Algorithms · Computer Science 2007-05-23 L. Allison

Many reasoning, planning, and problem-solving tasks share an intrinsic algorithmic nature: correctly simulating each step is a sufficient condition to solve them correctly. This work studies to what extent Large Language Models (LLMs) can…

Methods from statistical physics, such as those involving complex networks, have been increasingly used in quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification…

Physics and Society · Physics 2013-02-20 Diego R. Amancio , Sandra M. Aluisio , Osvaldo N. Oliveira , Luciano da F. Costa

Data complexity is an important concept in the natural sciences and related areas, but lacks a rigorous and computable definition. In this paper, we focus on a particular sense of complexity that is high if the data is structured in a way…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Louis Mahon

The classical coding theorem in Kolmogorov complexity states that if an $n$-bit string $x$ is sampled with probability $\delta$ by an algorithm with prefix-free domain then K$(x) \leq \log(1/\delta) + O(1)$. In a recent work, Lu and…

Computational Complexity · Computer Science 2022-04-19 Zhenjian Lu , Igor C. Oliveira , Marius Zimand

This paper uses the Minimum Description Length paradigm to model the complexity of CxGs (operationalized as the encoding size of a grammar) alongside their descriptive adequacy (operationalized as the encoding size of a corpus given a…

Computation and Language · Computer Science 2019-04-12 Jonathan Dunn

Cognitive complexity measures quantify human difficulty in understanding the source code based on cognitive informatics foundation. The discipline derives cognitive complexity on a basis of fundamental software factors i.e, inputs, outputs,…

Software Engineering · Computer Science 2013-04-02 Yong-Hwa Choe , Chol-Yong Jong , Song Han

We give a trichotomy theorem for the complexity of approximately counting the number of satisfying assignments of a Boolean CSP instance. Such problems are parameterised by a constraint language specifying the relations that may be used in…

Computational Complexity · Computer Science 2009-07-23 Martin Dyer , Leslie Ann Goldberg , Mark Jerrum

Muchnik's theorem about simple conditional descriptions states that for all strings $a$ and $b$ there exists a short program $p$ transforming $a$ to $b$ that has the least possible length and is simple conditional on $b$. In this paper we…

Computational Complexity · Computer Science 2011-03-21 Daniil Musatov , Andrei Romashchenko , Alexander Shen

Text simplification reduces the language complexity of professional content for accessibility purposes. End-to-end neural network models have been widely adopted to directly generate the simplified version of input text, usually functioning…

Computation and Language · Computer Science 2021-07-08 Cristina Garbacea , Mengtian Guo , Samuel Carton , Qiaozhu Mei

The LZ-End parsing [Kreft & Navarro, 2011] of an input string yields compression competitive with the popular Lempel-Ziv 77 scheme, but also allows for efficient random access. Kempa and Kosolobov showed that the parsing can be computed in…

Data Structures and Algorithms · Computer Science 2024-09-18 Patrick Dinklage

The following problem is considered. A Turing machine $M$, that accepts a string of fixed length $t$ as input, runs for a time not exceeding a fixed value $n$ and is guaranteed to produce a binary output, is given. It's required to find a…

Computational Complexity · Computer Science 2020-12-04 Marsel Matdinov

The goal of this work is to build a classifier that can identify text complexity within the context of teaching reading to English as a Second Language (ESL) learners. To present language learners with texts that are suitable to their level…

Computation and Language · Computer Science 2023-06-22 M. Zakaria Kurdi

The classic supervised classification algorithms are efficient, but time-consuming, complicated and not interpretable, which makes it difficult to analyze their results that limits the possibility to improve them based on real observations.…

Computation and Language · Computer Science 2018-03-05 Hussam Hamdan

In this paper with two equivalent representations of the information contained by a SAT formula, the reason why string generated by succinct SAT formula can be greatly compressed is firstly presented based on Kolmogorov complexity theory.…

Computational Complexity · Computer Science 2015-10-06 Feng Pan

Large language models display remarkable capabilities in logical and mathematical reasoning, allowing them to solve complex tasks. Interestingly, these abilities emerge in networks trained on the simple task of next-token prediction. In…

Machine Learning · Computer Science 2024-07-31 Eran Malach