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Concept

Parser combinator

Related publications (19)

Hearing structure in music: An empirical inquiry into listening as representation and processing

Gabriele Cecchetti

As a universal expression of human creativity, music is capable of conveying great subtlety and complexity. Crucially, this complexity is not encoded in the score or in the sounds, but is rather construed in the mind of the listener in the form of nuanced ...

EPFL2024

Interpreting Rhythm as Parsing: Syntactic-Processing Operations Predict the Migration of Visual Flashes as Perceived During Listening to Musical Rhythms

Martin Alois Rohrmeier, Steffen Alexander Herff, Gabriele Cecchetti

Music can be interpreted by attributing syntactic relationships to sequential musical events, and, computationally, such musical interpretation represents an analogous combinatorial task to syntactic processing in language. While this perspective has been ...

Wiley2023

Musical Garden Paths: Evidence for Syntactic Revision Beyond the Linguistic Domain

Martin Alois Rohrmeier, Steffen Alexander Herff, Gabriele Cecchetti

While theoretical and empirical insights suggest that the capacity to represent and process complex syntax is crucial in language as well as other domains, it is still unclear whether specific parsing mechanisms are also shared across domains. Focusing on ...

Wiley2022

Uniform parsing for hyperedge replacement grammars

Petter Harald Ericson

It is well known that hyperedge-replacement grammars can generate NP-complete graph languages even under seemingly harsh restrictions. This means that the parsing problem is difficult even in the non-uniform setting, in which the grammar is considered to b ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2021

Efficient Parsing with Derivatives and Zippers

Romain Edelmann

Parsing is the process that enables a computer system to make sense of raw data. Parsing is common to almost all computer systems: It is involved every time sequential data is read and elaborated into structured data. The theory of parsing usually focuses ...

EPFL2021

Gramatron: Effective Grammar-Aware Fuzzing

Mathias Josef Payer

Fuzzers aware of the input grammar can explore deeper program states using grammar-aware mutations. Existing grammar-aware fuzzers are ineffective at synthesizing complex bug triggers due to: (i) grammars introducing a sampling bias during input generation ...

ASSOC COMPUTING MACHINERY2021

Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networks

Angelos Katharopoulos

Impressive progress in 3D shape extraction led to representations that can capture object geometries with high fidelity. In parallel, primitive-based methods seek to represent objects as semantically consistent part arrangements. However, due to the simpli ...

IEEE COMPUTER SOC2021

Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement

James Henderson, Alireza Mohammadshahi

We propose the Recursive Non-autoregressive Graph-to-graph Transformer architecture (RNG-Tr) for the iterative refinement of arbitrary graphs through the recursive application of a non-autoregressive Graph-to-Graph Transformer and apply it to syntactic dep ...

2021

LMS-Verify: Abstraction without Regret for Verified Systems Programming’

Tiark Rompf, Nada Amin

Performance critical software is almost always developed in C, as programmers do not trust high-level languages to deliver the same reliable performance. This is bad because low-level code in unsafe languages attracts security vulnerabilities and because d ...

Assoc Computing Machinery2017

The SUMMA Platform Prototype

Philip Neil Garner, Hervé Bourlard, Andrei Popescu-Belis, Nikolaos Pappas, Sibo Tong, Yang Wang, Lesly Sadiht Miculicich Werlen

We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadca ...

Association for Computational Linguistics2017

Specialising Parsers for Queries

Manohar Jonnalagedda

Many software systems consist of data processing components that analyse large datasets to gather information and learn from these. Often, only part of the data is relevant for analysis. Data processing systems contain an initial preprocessing step that fi ...

EPFL2016

Word Sequence Modeling using Deep Learning : an End-to-end Approach and its Applications

Joël Yvon Roland Legrand

For a long time, natural language processing (NLP) has relied on generative models with task specific and manually engineered features. Recently, there has been a resurgence of interest for neural networks in the machine learning community, obtaining state ...

EPFL2016

Automating Grammar Comparison

Viktor Kuncak, Mikaël Mayer, Ravichandhran Kandhadai Madhavan

We consider from a practical perspective the problem of checking equivalence of context-free grammars. We present techniques for proving equivalence, as well as techniques for finding counter-examples that establish non-equivalence. Among the key building ...

2015

Staged parser combinators for efficient data processing

Martin Odersky, Tiark Rompf, Sandro Stucki, Manohar Jonnalagedda, Thierry Coppey

Parsers are ubiquitous in computing, and many applications depend on their performance for decoding data efficiently. Parser combinators are an intuitive tool for writing parsers: tight integration with the host language enables grammar specifications to b ...

ACM Press2014

Staged Parser Combinators for Efficient Data Processing

Martin Odersky, Tiark Rompf, Sandro Stucki, Manohar Jonnalagedda, Thierry Coppey

Assoc Computing Machinery2014

Accelerating parser combinators with macros

Manohar Jonnalagedda, Eric Beguet

Parser combinators provide an elegant way of writing parsers: parser implementations closely follow the structure of the underlying grammar, while accommodating interleaved host language code for data processing. However, the host language features used fo ...

ACM Press2014

Comparing machines and humans on a visual categorization test

François Fleuret, Charles Dubout

Automated scene interpretation has benefited from advances in machine learning, and restricted tasks, such as face detection, have been solved with sufficient accuracy for restricted settings. However, the performance of machines in providing rich semantic ...

National Academy of Sciences2011

Stationary Features and Cat Detection

François Fleuret

Most discriminative techniques for detecting instances from object categories in still images consist of looping over a partition of a pose space with dedicated binary classifiers. The efficiency of this strategy for a complex pose, i.e., for fine-grained ...

2008

Model Driven Analysis and Synthesis of Concrete Syntax

Frédéric Fondement

Metamodeling is raising more and more interest in the field of language engineering. While this approach is now well understood for defining abstract syntaxes, formally defining concrete syntaxes with metamodels is still a challenge. Concrete syntaxes are ...

2006