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The theory of limits of discrete combinatorial objects has been thriving for the last decade or so. The syntactic, algebraic approach to the subject is popularly known as "flag algebras", while the semantic, geometric one is often…

Combinatorics · Mathematics 2020-12-02 Leonardo N. Coregliano , Alexander A. Razborov

Large Language Models (LLMs) have shown remarkable capabilities in processing various data structures, including graphs. While previous research has focused on developing textual encoding methods for graph representation, the emergence of…

Machine Learning · Computer Science 2024-09-16 Zhiqiang Zhong , Davide Mottin

The lambda calculus since more than half a century is a model and foundation of functional programming languages. However, lambda expressions can be evaluated with different reduction strategies and thus, there is no fixed cost model nor…

Programming Languages · Computer Science 2024-05-22 Tomasz Drab

Large language models (LLMs) have achieved impressive performance on many natural language processing tasks. However, their capabilities on graph-structured data remain relatively unexplored. In this paper, we conduct a series of…

Machine Learning · Computer Science 2023-10-10 Yuntong Hu , Zheng Zhang , Liang Zhao

This work aims to make it easier for a specialist in one field to find and explore ideas from another field which may be useful in solving a new problem arising in his practice. It presents a methodology which serves to represent the…

Computers and Society · Computer Science 2007-05-23 Sebastien Paquet

Graph transformations definable in logic can be described using the notion of transductions. By understanding transductions as a basic embedding mechanism, which captures the possibility of encoding one graph in another graph by means of…

Combinatorics · Mathematics 2025-01-09 Michał Pilipczuk

Transformers have become the foundational architecture for a broad spectrum of sequence modeling applications, underpinning state-of-the-art systems in natural language processing, vision, and beyond. However, their theoretical limitations…

Computation and Language · Computer Science 2026-02-13 Michelle Yuan , Weiyi Sun , Amir H. Rezaeian , Jyotika Singh , Sandip Ghoshal , Yao-Ting Wang , Miguel Ballesteros , Yassine Benajiba

The emergence of a variety of graph-based meaning representations (MRs) has sparked an important conversation about how to adequately represent semantic structure. These MRs exhibit structural differences that reflect different theoretical…

Computation and Language · Computer Science 2020-05-01 Lucia Donatelli , Jonas Groschwitz , Alexander Koller , Matthias Lindemann , Pia Weißenhorn

Graph neural networks (GNNs) are powerful tools on graph data. However, their predictions are mis-calibrated and lack interpretability, limiting their adoption in critical applications. To address this issue, we propose a new…

Machine Learning · Computer Science 2025-08-26 Lingkai Kong , Haotian Sun , Yuchen Zhuang , Haorui Wang , Wenhao Mu , Chao Zhang

Scott's graph model is a lambda-algebra based on the observation that continuous endofunctions on the lattice of sets of natural numbers can be represented via their graphs. A graph is a relation mapping finite sets of input values to…

Logic in Computer Science · Computer Science 2015-07-01 Guy McCusker

While graphs and abstract data structures can be large and complex, practical instances are often regular or highly structured. If the instance has sufficient structure, we might hope to compress the object into a more succinct…

Computational Complexity · Computer Science 2024-12-02 Shreya Gupta , Boyang Huang , Russell Impagliazzo , Stanley Woo , Christopher Ye

This article proposes a convenient tool for decoding the output of neural networks trained by Connectionist Temporal Classification (CTC) for handwritten text recognition. We use regular expressions to describe the complex structures…

Neural and Evolutionary Computing · Computer Science 2016-03-31 Tobias Strauß , Gundram Leifert , Tobias Grüning , Roger Labahn

Symbolic sentence meaning representations, such as AMR (Abstract Meaning Representation) provide expressive and structured semantic graphs that act as intermediates that simplify downstream NLP tasks. However, the instruction-following…

Computation and Language · Computer Science 2024-07-08 Peiran Yao , Kostyantyn Guzhva , Denilson Barbosa

Many different systems with explicit substitutions have been proposed to implement a large class of higher-order languages. Motivations and challenges that guided the development of such calculi in functional frameworks are surveyed in the…

Programming Languages · Computer Science 2015-07-01 Delia Kesner

Large language models (LLMs) are being increasingly explored for graph tasks. Despite their remarkable success in text-based tasks, LLMs' capabilities in understanding explicit graph structures remain limited, particularly with large…

Machine Learning · Computer Science 2024-10-31 Sambhav Khurana , Xiner Li , Shurui Gui , Shuiwang Ji

We present a method to simplify expressions in the context of an equational theory. The basic ideas and concepts of the method have been presented previously elsewhere but here we tackle the difficult task of making it efficient in…

Logic in Computer Science · Computer Science 2020-03-16 Baudouin Le Charlier

We introduce a category-theoreticabstraction of a syntax with auxiliary functions, called an admissiblemonad morphism. Relying on an abstract form of structural recursion,we then design generic tools to construct admissible monad…

Logic in Computer Science · Computer Science 2022-04-11 Tom Hirschowitz , Ambroise Lafont

These are lecture notes on the algebraic approach to regular languages. The classical algebraic approach is for finite words; it uses semigroups instead of automata. However, the algebraic approach can be extended to structures beyond…

Formal Languages and Automata Theory · Computer Science 2020-08-27 Mikołaj Bojańczyk

Real-world applications often combine learning and optimization problems on graphs. For instance, our objective may be to cluster the graph in order to detect meaningful communities (or solve other common graph optimization problems such as…

Machine Learning · Computer Science 2020-01-09 Bryan Wilder , Eric Ewing , Bistra Dilkina , Milind Tambe

The lambda-calculus is a peculiar computational model whose definition does not come with a notion of machine. Unsurprisingly, implementations of the lambda-calculus have been studied for decades. Abstract machines are implementations…

Programming Languages · Computer Science 2017-01-04 Beniamino Accattoli
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