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Related papers: Expressive Power of Hypergraph Lambek Grammars

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Two formalisms, both based on context-free grammars, have recently been proposed as a basis for a non-uniform random generation of combinatorial objects. The former, introduced by Denise et al, associates weights with letters, while the…

Computation and Language · Computer Science 2012-05-04 Yann Ponty

Large Language Models (LLMs) have demonstrated exceptional abilities in reasoning for task planning. However, challenges remain under-explored for parallel schedules. This paper introduces a novel paradigm, plan-over-graph, in which the…

Artificial Intelligence · Computer Science 2025-02-21 Shiqi Zhang , Xinbei Ma , Zouying Cao , Zhuosheng Zhang , Hai Zhao

Higher-Order Fixpoint Logic (HFL) is a hybrid of the simply typed \lambda-calculus and the modal \lambda-calculus. This makes it a highly expressive temporal logic that is capable of expressing various interesting correctness properties of…

Logic in Computer Science · Computer Science 2015-07-01 Roland Axelsson , Martin Lange , Rafal Somla

Every language recognized by the Lambek calculus with brackets is context-free. This is shown by combining an observation by J\"ager with an entirely straightforward adaptation of the method Pentus used for the original Lambek calculus. The…

Logic · Mathematics 2018-04-17 Makoto Kanazawa

Graph-to-text generation aims to generate fluent texts from graph-based data. In this paper, we investigate two recently proposed pretrained language models (PLMs) and analyze the impact of different task-adaptive pretraining strategies for…

Computation and Language · Computer Science 2021-09-28 Leonardo F. R. Ribeiro , Martin Schmitt , Hinrich Schütze , Iryna Gurevych

We extend the powerful Pullback-Pushout (PBPO) approach for graph rewriting with strong matching. Our approach, called \pbpostrong, exerts more control over the embedding of the pattern in the host graph, which is important for a large…

Logic in Computer Science · Computer Science 2021-06-28 Roy Overbeek , Jörg Endrullis , Aloïs Rosset

In precision medicine, quantitative multi-omic features, topological context, and textual biological knowledge play vital roles in identifying disease-critical signaling pathways and targets. Existing pipelines capture only part of…

Artificial Intelligence · Computer Science 2025-12-17 Heming Zhang , Di Huang , Wenyu Li , Michael Province , Yixin Chen , Philip Payne , Fuhai Li

We evaluate the ability of large language models (LLMs) to infer causal relations from natural language. Compared to traditional natural language processing and deep learning techniques, LLMs show competitive performance in a benchmark of…

Artificial Intelligence · Computer Science 2023-12-25 Alessandro Antonucci , Gregorio Piqué , Marco Zaffalon

This paper shows connections between command injection attacks, continuations, and the Lambek calculus: certain command injections, such as the tautology attack on SQL, are shown to be a form of control effect that can be typed using the…

Programming Languages · Computer Science 2016-06-22 Hayo Thielecke

In this paper, the deductive system for double propositional logic DL and gamma DL existential graphs are presented. It rigorously proves the consistency of the DL and that the DL theorems correspond exactly to the valid existential graphs…

Logic · Mathematics 2023-12-13 Manuel Sierra Aristizabal

We investigate the power of message-passing neural networks (MPNNs) in their capacity to transform the numerical features stored in the nodes of their input graphs. Our focus is on global expressive power, uniformly over all input graphs,…

Artificial Intelligence · Computer Science 2022-07-29 Floris Geerts , Jasper Steegmans , Jan Van den Bussche

We describe an algorithm for generating all $k$-critical $\mathcal H$-free graphs, based on a method of Ho\`{a}ng et al. Using this algorithm, we prove that there are only finitely many $4$-critical $(P_7,C_k)$-free graphs, for both $k=4$…

Combinatorics · Mathematics 2015-08-14 Jan Goedgebeur , Oliver Schaudt

This note describes a new approach to classifying graphs that leverages graph generative models (GGM). Assuming a GGM that defines a joint probability distribution over graphs and their class labels, I derive classification formulas for the…

Machine Learning · Computer Science 2023-07-25 Oliver Schulte

We refine the weighted type graph technique for proving termination of double pushout (DPO) graph transformation systems. We increase the power of the approach for graphs, we generalize the technique to other categories, and we allow for…

Logic in Computer Science · Computer Science 2026-03-11 Jörg Endrullis , Roy Overbeek

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

Equality saturation, a technique for program optimisation and reasoning, has gained attention due to the resurgence of equality graphs (e-graphs). E-graphs represent equivalence classes of terms under rewrite rules, enabling simultaneous…

Logic in Computer Science · Computer Science 2025-05-05 Aleksei Tiurin , Dan R. Ghica , Nick Hu

The rapid development of Multimodal Large Language Models (MLLMs) has enabled the integration of multiple modalities, including texts and images, within the large language model (LLM) framework. However, texts and images are usually…

Artificial Intelligence · Computer Science 2025-03-11 Yi Fang , Bowen Jin , Jiacheng Shen , Sirui Ding , Qiaoyu Tan , Jiawei Han

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language processing tasks. Recently, several LLMs-based pipelines have been developed to enhance learning on graphs with text attributes,…

Machine Learning · Computer Science 2024-07-30 Kai Guo , Zewen Liu , Zhikai Chen , Hongzhi Wen , Wei Jin , Jiliang Tang , Yi Chang

While Large Language Models (LLMs) have shown exceptional generalization capabilities, their ability to process graph data, such as molecular structures, remains limited. To bridge this gap, this paper proposes Graph2Token, an efficient…

Machine Learning · Computer Science 2025-03-11 Runze Wang , Mingqi Yang , Yanming Shen

As a supplement to my talk at the workshop, this extended abstract motivates and summarizes my work with co-authors on problems in two separate areas: first, in the lambda-calculus with letrec, a universal model of computation, and second,…

Logic in Computer Science · Computer Science 2024-10-02 Clemens Grabmayer