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Both syntactic and semantic structures are key linguistic contextual clues, in which parsing the latter has been well shown beneficial from parsing the former. However, few works ever made an attempt to let semantic parsing help syntactic…

Computation and Language · Computer Science 2020-10-08 Junru Zhou , Zuchao Li , Hai Zhao

Matrix Graph Grammars (MGG) is a novel approach to the study of graph dynamics ([15]). In the present contribution we look at MGG as a formal grammar and as a model of computation, which is a necessary step in the more ambitious program of…

Discrete Mathematics · Computer Science 2009-11-16 Pedro Pablo Perez Velasco

Researchers have relegated natural language processing tasks to Transformer-type models, particularly generative models, because these models exhibit high versatility when performing generation and classification tasks. As the size of these…

Computation and Language · Computer Science 2025-04-04 Fabio Yáñez-Romero , Andrés Montoyo , Armando Suárez , Yoan Gutiérrez , Ruslan Mitkov

Sentence matching is a fundamental task of natural language processing with various applications. Most recent approaches adopt attention-based neural models to build word- or phrase-level alignment between two sentences. However, these…

Computation and Language · Computer Science 2021-10-22 Peng Cui , Le Hu , Yuanchao Liu

In this paper, we describe a so-called screening approach for learning robust processing of spontaneously spoken language. A screening approach is a flat analysis which uses shallow sequences of category representations for analyzing an…

cmp-lg · Computer Science 2016-08-31 Stefan Wermter , Volker Weber

We introduce Transformer Grammars (TGs), a novel class of Transformer language models that combine (i) the expressive power, scalability, and strong performance of Transformers and (ii) recursive syntactic compositions, which here are…

Computation and Language · Computer Science 2022-12-07 Laurent Sartran , Samuel Barrett , Adhiguna Kuncoro , Miloš Stanojević , Phil Blunsom , Chris Dyer

While deep convolutional architectures have achieved remarkable results in a gamut of supervised applications dealing with images and speech, recent works show that deep untrained non-convolutional architectures can also outperform…

Signal Processing · Electrical Eng. & Systems 2020-03-13 Samuel Rey , Antonio G. Marques , Santiago Segarra

Neural network architectures have been augmented with differentiable stacks in order to introduce a bias toward learning hierarchy-sensitive regularities. It has, however, proven difficult to assess the degree to which such a bias is…

Computation and Language · Computer Science 2019-06-05 William Merrill , Lenny Khazan , Noah Amsel , Yiding Hao , Simon Mendelsohn , Robert Frank

We present a novel work-in-progress approach to the parsing of hypergraphs generated by context-free hyperedge replacement grammars. This method is based on a new LR parsing technique for positional grammars, which is also under active…

Formal Languages and Automata Theory · Computer Science 2026-01-08 Gennaro Costagliola , Federico Vastarini

Rewriting is a formalism widely used in computer science and mathematical logic. The classical formalism has been extended, in the context of functional languages, with an order over the rules and, in the context of rewrite based languages,…

Logic in Computer Science · Computer Science 2019-06-12 Horatiu Cirstea , Pierre-Etienne Moreau

Growing interest in modelling complex systems from brains to societies to cities using networks has led to increased efforts to describe generative processes that explain those networks. Recent successes in machine learning have prompted…

Neural and Evolutionary Computing · Computer Science 2024-01-12 Govind Gandhi

Engelfriet and Vereijken have shown that linear graph grammars based on hyperedge replacement generate graph languages that can be considered as interpretations of regular string languages over typed symbols. In this paper we show that…

Formal Languages and Automata Theory · Computer Science 2025-03-27 Frank Drewes , Berthold Hoffmann , Mark Minas

Formal languages let us define the textual representation of data with precision. Formal grammars, typically in the form of BNF-like productions, describe the language syntax, which is then annotated for syntax-directed translation and…

Software Engineering · Computer Science 2015-03-19 Luis Quesada , Fernando Berzal , Juan-Carlos Cubero

GP (for Graph Programs) is a rule-based, nondeterministic programming language for solving graph problems at a high level of abstraction, freeing programmers from handling low-level data structures. The core of GP consists of four…

Logic in Computer Science · Computer Science 2010-04-08 Detlef Plump , Sandra Steinert

Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as…

Information Theory · Computer Science 2007-07-16 Russell K. Standish

Persistence diagrams (PDs), often characterized as sets of death and birth of homology class, have been known for providing a topological representation of a graph structure, which is often useful in machine learning tasks. Prior works rely…

Machine Learning · Computer Science 2022-09-29 Chau Pham , Trung Dang , Peter Chin

Diagrams are common tools for representing complex concepts, relationships and events, often when it would be difficult to portray the same information with natural images. Understanding natural images has been extensively studied in…

Computer Vision and Pattern Recognition · Computer Science 2016-03-25 Aniruddha Kembhavi , Mike Salvato , Eric Kolve , Minjoon Seo , Hannaneh Hajishirzi , Ali Farhadi

String diagrams are a powerful tool for reasoning about physical processes, logic circuits, tensor networks, and many other compositional structures. Dixon, Duncan and Kissinger introduced string graphs, which are a combinatoric…

Category Theory · Mathematics 2014-04-02 Aleks Kissinger , Alex Merry , Matvey Soloviev

Graphs can represent relational information among entities and graph structures are widely used in many intelligent tasks such as search, recommendation, and question answering. However, most of the graph-structured data in practice suffers…

Information Retrieval · Computer Science 2021-12-30 Hanxiong Chen , Yunqi Li , Shaoyun Shi , Shuchang Liu , He Zhu , Yongfeng Zhang

In this paper we provide for parsing with respect to grammars expressed in a general TFS-based formalism, a restriction of ALE. Our motivation being the design of an abstract (WAM-like) machine for the formalism, we consider parsing as a…

cmp-lg · Computer Science 2016-08-31 Shuly Wintner , Nissim Francez