Publications associées à Analyse syntaxique

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

Angelos Katharopoulos, Andreas Geiger, Despoina Paschalidou

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 ...

2020

Zippy LL(1) Parsing with Derivatives

Viktor Kuncak, Jad Hamza, Romain Edelmann

In this paper, we present an efficient, functional, and formally verified parsing algorithm for LL(1) context-free expressions based on the concept of derivatives of formal languages. Parsing with derivatives is an elegant parsing technique, which, in the ...

ASSOC COMPUTING MACHINERY2020

Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony

Martin Alois Rohrmeier, Daniel Harasim

Music is hierarchically structured, both in how it is perceived by listeners and how it is composed. Such structure can be elegantly captured using probabilistic grammatical models similar to those used to study natural language. They address the complexit ...

ISMIR2019

Annotated References in the Historiography on Venice: 19th–21st centuries

Matteo Romanello, Giovanni Colavizza

We publish a dataset containing more than 40’000 manually annotated references from a broad corpus of books and journal articles on the history of Venice. References were considered from both reference lists and footnotes, include primary and secondary sou ...

2017

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

A pilot study on eliciting human operations decision in purchasing and measuring their impact on supply chain efficiency

Rémy Glardon, Souleïman Naciri, Min-Jung Yoo, Yvonne Badulescu

This paper presents a methodology for eliciting the behavioural model of purchasers' decision-making in a supply chain environment. The objective of the work is to explicitly describe the relationship between a human user's behaviour and the resulting perf ...

Pergamon-Elsevier Science Ltd2017

The SUMMA Platform Prototype

Hervé Bourlard, Philip Neil Garner, Andrei Popescu-Belis, Nikolaos Pappas, Sibo Tong, Yang Wang, Ahmed Ali, Steve Renals, Lesly Sadiht Miculicich Werlen, Marco Damonte, Hassan Sajjad

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

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Analyse syntaxique

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

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

Zippy LL(1) Parsing with Derivatives

Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony

Implicit discourse relation classification with syntax-aware contextualized word representations

Annotated References in the Historiography on Venice: 19th–21st centuries

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

A pilot study on eliciting human operations decision in purchasing and measuring their impact on supply chain efficiency

The SUMMA Platform Prototype

Specialising Parsers for Queries

Graph Chatbot

Chattez avec Graph Search

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

Zippy LL(1) Parsing with Derivatives

Specialising Parsers for Queries

Implicit discourse relation classification with syntax-aware contextualized word representations

A pilot study on eliciting human operations decision in purchasing and measuring their impact on supply chain efficiency

Harmonic Syntax in Time: Rhythm Improves Grammatical Models of Harmony

The SUMMA Platform Prototype

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

Annotated References in the Historiography on Venice: 19th–21st centuries

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