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Logiciels


logiciels

L-Framework

2022

Carlos Olarte, Elaine Pimentel, Camilo Rocha

Description

The L-Framework uses rewrite-based reasoning for proving crucial properties of sequent systems such as admissibility of structural rules, invertibility of rules and cut-elimination. Such procedures have been fully mechanized in Maude, achieving a great degree of automation when used on several sequent systems including intuitionistic and classical logics, linear logic, and normal modal logics.

QKVAE

2022

A model for Unsupervised Disentanglement of Syntax and Semantics (code)

Ghazi Felhi, Joseph Le Roux, Djamé Seddah

Description

This repo contains the code for our paper Exploiting Inductive Bias in Transformers for Unsupervised Disentanglement of Syntax and Semantics with VAEs

MBartCopyGenerator

2022

Jose Angel Gonzalez, Davide Buscaldi, Lluis Hurtado, Emilio Sanchis

Description

MBart-based model for the indexing of scientific documents. Presented to NLDB 2022. "Transformer-based models for the Automatic Indexing of Scientific Documents in French" José Angel Gonzalez, Davide Buscaldi, Lluis Hurtado and Emilio Sanchis

Global Span Selection for Named Entity Recognition (code)

2022

Urchade Zaratiana, Niama Elkhbir, Pierre Holat, Nadi Tomeh, Thierry Charnois

Description

Named Entity Recognition (NER) is an important task in Natural Language Processing with applications in many domains. We present a named entity recognition system in which we output a set of spans (i.e., segmentations) by maximizing a global score. During training, we optimize our model by maximizing the probability of the gold segmentation. During inference, we use dynamic programming to select the best segmentation under a linear time complexity.

GNNer

2022

Reducing Overlapping in Span-based NER Using Graph Neural Networks (code)

Urchade Zaratiana, Nadi Tomeh, Pierre Holat, Thierry Charnois

Description

Code for Reducing Overlapping in Span-based NER Using Graph Neural Networks

DyREx

2022

Dynamic Query Representation for Extractive Question Answering (code)

Urchade Zaratiana, Niama Elkhbir, Dennis Hernando Nunez Fernandez, Pierre Holat, Nadi Tomeh, Thierry Charnois

Description

Extractive question answering (ExQA) is an essential task for Natural Language Processing. To address this task, we propose DyREx, a generalization of the vanilla approach where we dynamically compute query vectors given the input, using an attention mechanism through transformer layers.

CS-KG

2022

A Large-Scale Knowledge Graph of Research Entities and Claims in Computer Science

Davide Buscaldi, Danilo Dessì, Diego Reforgiato Recupero, Francesco Osborne, Enrico Motta

coq-num-analysis opam package (Numerical Analysis in Coq)

2022

Sylvie Boldo, François Clément, Martin Vincent, Micaela Mayero, Florian Faissole, Houda Mouhcine, Louise Leclerc, Stephane Aubry

Description

Formal developments and proofs in Coq of numerical analysis problems. This archive includes several Coq developments: - Lebesgue directory is about the Lebesgue Integration of Nonnegative Functions (see paper, paper, and report); - Lebesgue/bochner_integral directory is about the Bochner integral (see report); - LM directory is about the Lax–Milgram theorem (see paper, paper, and report); - Opam package coq-num-analysis: version 1.0 provides Lebesgue, and LM. - Lebesgue and LM are compiling in Coq 8.12 to 8.16.

UnifiedAR

2022

A Modular Platform for Activity Recognition from Sensor Data

Seyed Mohammad Reza Modaresi, Aomar Osmani, Mohammadreza Razzazi, Abdelghani Chibani

Description

UnifiedAR is a modular platform designed to recognize activities based on sensor data. With the proliferation of sensors in various devices and environments, there is a growing need to extract meaningful insights from the data they generate. Existing activity recognition systems often lack flexibility and interoperability, making it challenging to deploy across different domains and sensor types.

EvalSeg

2022

Multi Modal Evaluation For Medical Image Segmentation

Seyed Mohammad Reza Modaresi, Aomar Osmani, Mohammadreza Razzazi, Abdelghani Chibani

Description

The selection of an optimal image segmentation technique relies heavily on the evaluation function utilized. However, recent investigations have revealed shortcomings in the performance evaluation of image segmentation models, particularly in the context of medical image segmentation where inter-voxel dependencies exist. Existing evaluation methods often suffer from a lack of robustness and exhibit statistical biases. Unlike conventional systems that classify predictions as either correct or incorrect, medical image segmentation predictions can exhibit both partial correctness and partial incorrectness simultaneously. This software addresses this inherent expressiveness and proposes a novel multi-modal evaluation (MME) method that aims to assess the effectiveness of various segmentation techniques in a comprehensive manner. The proposed MME method introduces a formal definition that incorporates interpretable criteria, including boundary alignment, detection, total volume, relative volume, and uniformity. By considering these salient properties of segmentation systems, the MME method provides a refined approach to segmentation assessment. By leveraging the MME method, researchers and practitioners can gain deeper insights into the efficiency of diverse segmentation techniques, particularly in the context of medical image analysis. The incorporation of interpretable criteria enhances the interpretability and applicability of segmentation evaluation, fostering advancements in the field of medical imaging and improving the overall quality of segmentation results.

Strength in numbers

2021

averaging and clustering effects in mixture of experts for graph-based dependency parsing (code)

Xudong Zhang, Joseph Le Roux, Thierry Charnois

Description

Mixture of Experts, training for mixture with clustering. Un VAE texte-vers-texte pour la génération contrôlée.

RENFO / DiasporasRL (code)

2021

Jessica Lopez Espejel, Pegah Alizadeh, Jorge Garcia Flores

Description

La recherche d'experts parmi les migrations hautement qualifiées est un enjeu crucial pour les pays en développement. Cet système implémente une méthode d'apprentissage par renforcement profond pour répondre à cette problématique à partir de résultats des moteurs de recherche sur le web. Les résultats obtenus pourront être utilisés par des sociologues de la migration pour mieux comprendre les diasporas des savoirs, ainsi que par le pays en développement pour localiser ses experts formés à l'étranger. Notre système effectue des requêtes envers des moteurs de recherche pour y extraire les informations concernant l'institution et l'année d'affiliation de chaque expert. L'objectif de ce travail est de définir un navigateur intelligent capable d'assister cette recherche en générant et en observant le moins possible de requêtes automatiques. Nous utilisons comme navigateur un Deep-Q Network avec deux architectures basées sur des réseaux de neurones pour approximer la valeur de la Q-value fonction.

GeSERA

2021

General-domain Summary Evaluation by Relevance Analysis (code)

Jessica Lopez Espejel, Gaël De Chalendar, Jorge Garcia Flores, Thierry Charnois, Ivan Vladimir Meza Ruiz

Description

We present GeSERA, an open-source improved version of SERA for evaluating automatic extractive and abstractive summaries from the general domain. SERA is based on a search engine that compares candidate and reference summaries (called queries) against an information retrieval document base (called index). SERA was originally designed for the biomedical domain only, where it showed a better correlation with manual methods than the widely used lexical-based ROUGE method. In this paper, we take out SERA from the biomedical domain to the general one by adapting its content-based method to successfully evaluate summaries from the general domain. First, we improve the query reformulation strategy with POS Tags analysis of general-domain corpora. Second, we replace the biomedical index used in SERA with two article collections from AQUAINT-2 and Wikipedia.

ChêneTAL

2021

plate-forme d'intégration d'outils de traitement automatique des langues

Aude Grezka, Jorge Garcia Flores, Thierry Charnois

Description

La plateforme ChêneTAL a été conçue pour permettre la mise en place de chaînes hétérogènes de Traitement Automatique des Langues (TAL) en intégrant des logiciels existants en gestion et manipulation de corpus avec des modèles plus récents d’Intelligence Artificielle (IA) et en proposant une interface simple et intuitive pour les chercheur·euse·s de la communauté en Traitement Automatique des Langues (TAL) et pour ceux en Linguistique/Sciences Humaines et Sociales non spécialistes en informatique. Code: https://depot.lipn.univ-paris13.fr/garciaflores/ch-netal

JCV2

2021

Enabling Compatibility of OpenCV UI Components with Jupyter Notebooks

Seyed Mohammad Reza Modaresi, Aomar Osmani, Mohammadreza Razzazi, Abdelghani Chibani

Description

The "OpenCV Jupyter UI" project addresses the compatibility issue between OpenCV's user interface components and Jupyter Notebooks. In remote Jupyter environments such as Jupyter Notebook or Google Colab, the traditional method of using `cv2.imshow` for displaying images is not supported. This project introduces an alternative solution by providing the `jcv2.imshow` function, which is compatible with Jupyter environments. By replacing `cv2.imshow` with `jcv2.imshow`, users can seamlessly display images within Jupyter Notebooks without encountering compatibility errors. The `jcv2.imshow` function leverages Jupyter's capabilities to render images and ensures a smooth integration between OpenCV and Jupyter. Additionally, the project addresses the need for user interaction and replaces the usage of `cv2.waitKey` with `jcv2.waitKey`. For instance, `jcv2.waitKey(1000)` waits for a button press for one second. By bridging the gap between OpenCV and Jupyter, the "OpenCV Jupyter UI" project enhances the usability and convenience of using OpenCV's user interface components within Jupyter Notebooks. Users can seamlessly leverage OpenCV functionalities for image processing and visualization, empowering them to work efficiently in Jupyter environments.

ConfJournalRank

2021

Integrated Multi SourcesConference and Journal Information"

Seyed Mohammad Reza Modaresi, Aomar Osmani, Mohammadreza Razzazi, Abdelghani Chibani

Description

ConfJournalRank isintegrates conference and journal information from multiple authoritative sources. The system collects data from various reputable platforms, including Scopus, Scimago, Web of Science, WikiCFP, Core Ranking, Qualis, ERA, research.com, and Open Research, and consolidates this information into a unified platform. By gathering data from diverse sources, ConfJournalRank provides users with a centralized location to access and explore conference and journal details. Users no longer need to visit multiple websites or platforms to obtain relevant information. Instead, they can conveniently access a wide range of conference and journal data through a single interface. The system offers a comprehensive view of conferences and journals, incorporating various metrics, rankings, and categorizations from each source. This enables users to compare and assess the significance, impact, and quality of conferences and journals based on multiple criteria. ConfJournalRank aims to streamline the process of gathering conference and journal information, making it more efficient and accessible for researchers, scholars, and other users in the academic community. By providing a consolidated platform, the system facilitates informed decision-making and enhances the overall research experience for users seeking up-to-date and reliable conference and journal information.

Auto Profiler

2021

Automatic Interactive Tree-based Profiling of Python Scripts in Jupyter Notebook

Seyed Mohammad Reza Modaresi, Aomar Osmani, Mohammadreza Razzazi, Abdelghani Chibani

Description

This library presents a real-time timer designed for profiling Python functions or code snippets within the Jupyter environment. The timer integrates seamlessly with Jupyter widgets, providing an interactive and extendable tree-based visualization of profiling results. Key features of the proposed timer include the ability to filter out external library profiling, allowing users to focus solely on their own code. Additionally, the timer incorporates a threshold-based filter to exclude functions with very short execution times, enabling users to concentrate on more significant performance concerns. Furthermore, the timer supports variable depth analysis, facilitating the identification of time-consuming functions within nested call hierarchies. It also handles loop or multiple function calls, providing comprehensive profiling capabilities for iterative or repetitive code structures. Moreover, recursive function calls are appropriately handled, ensuring accurate and insightful profiling results. To optimize efficiency, users have the option to globally disable the timer by setting Profiler.GlobalDisable to True, thereby saving valuable execution time when profiling is not required. Overall, this real-time timer with interactive Jupyter widgets and an extendable tree-based interface empowers users to effectively profile Python functions or code snippets, filter results based on specific criteria, and gain deeper insights into their code's performance characteristics.

Mariotel, gestionnaire de salles de TP virtuelles sous GNU/Linux

2020

Jean-Vincent Loddo

Description

Mariotel est un logiciel libre (GNU GPL) de gestion de salles de TP virtuelles pour l'enseignement à distance, conçu et réalisé à partir de mars 2020 suite à la crise sanitaire du Covid-19. Avec ce système, n'importe quel enseignant d'une université hébergeant un serveur Mariotel peut, à tout moment, réserver une salle de TP composée de plusieurs ordinateurs virtuels. Chaque ordinateur virtuel, appelé "station de travail", sera affecté à un étudiant de la classe en début de séance et sera rendue accessible par un simple navigateur web (firefox, chrome, safari, etc). De son côté, l'enseignant aura, lui aussi, accès à distance à *tous* les postes des étudiants en simultanée. Il pourra prendre le contrôle de la station de travail, si nécessaire, avec sa souri et son clavier, en même temps que l'étudiant affecté au poste, en cliquant sur le poste de l'étudiant depuis une page web de contrôle de la salle. Il pourra ainsi assister l'ensemble des étudiants dans la réalisation de la séance de TP (on s’appuiera sur un logiciel de visioconférence, comme BBB, Meet, Teams ou Zoom, pour communiquer de vive voix avec la classe ou, à minima, sur un logiciel de messagerie instantanée). Le nom du projet, Mariotel, s'explique par l'idée originale de rendre le logiciel Marionnet utilisable à distance, dans une fenêtre de navigateur. À présent, le projet dépasse largement cet objectif initial et couvre l'ensemble des besoins en TP informatique réalisables sous le système d'exploitation GNU/Linux, ce qui reste (et restera) l'unique contrainte. La plateforme peut aussi être exploitée pour allouer des salles en libre service en dehors des heures de cours (certains enseignants réservent des salles en libre service pour des petits groupes, parfois le soir, voire la nuit). Dans les premiers mois de service (de septembre 2020 à mai 2021, incluant les confinements de fin 2020 et début 2021), Mariotel a été utilisé par plus de 40 enseignants différents (de l'IUT et de l'IG de l'USPN), pour plus de 4500 sessions étudiant (réellement connectés), c'est-à-dire 18000 heures étudiant au total.

YuCorrectMaya

2019

validation app of comparable corpus for the Maya Yucatec language (code)

Heba Kaddouh, Maroi Labiodh, Nouha Ghourabi, Jorge Garcia Flores, Alik Hafsa, Cylia Ourtirane

Description

The objective of this project is to develop resources for the automatic translation of the Maya Yucatec language.

Pamparios

2019

Traducteur espagnol - Wixárika (langue amérindienne) (démo)

Jorge Garcia Flores, Hugo Ferreira, Aziz Okotan, Fernando Mantilla, Fayaz Abdoulvahide

Description

Traducteur espagnol - Wixárika (langue amérindienne).

Neoveille, plateforme de repérage et de suivi des néologismes en corpus dynamique (outil en ligne)

2019

Emmanuel Cartier

Description

La plateforme Néoveille a pour objectif d'offrir un outil de détection et de suivi des néologismes dans la presse en ligne et plus généralement l'ensemble des données disponibles sur le web. Le projet a été financé pour trois ans (juin 2015 - juin 2018) par la COMUE Sorbonne Paris Cité (regroupant plusieurs laboratoires de Sorbonne-Paris-Cité (LIPN, LDI, CLILLAC-ARP, ERTIM), les acteurs du groupe EMPNEO et l'Université de São Paulo (USP)), puis financé par la Direction Générale à la Langue Française et aux Langues de France (DGLF-LF). Le projet propose : Une interface de gestion de sources de presse en ligne (format RSS) : les sources sont ensuite récupérées une fois par jour et les néologismes automatiquement détectés ; Une interface de validation/invalidation des néologismes détectés automatiquement dans la phase précédente ; Une interface de suivi des néologismes validés, avec une visualisation des contextes et un suivi par différents indicateurs métalinguistiques (pays, journal, domaine);

Boltzmann-Brain

2019

A standalone application for random generation of combinatorial structures.

Maciej Bendkowski, Olivier Bodini, Sergey Dovgal

Kilroy

2018

tag prediction and semantic indexing system (code)

Ivan Garrido Marquez, Jorge Garcia Flores, François Lévy, Adeline Nazarenko

Description

Document classification is often meant to serve as semantic indexing to help readers finding documents related to a given topic. However, the quality of indexing typically deteriorates with time: some categories are misused or forgotten by indexers, others become obsolete or too general to be useful. We implemented a semantic indexing system as an algorithm that guides indexers in restructuring their indexes. Focus is put on the reader’s rather than on the annotator’s point of view.

QPLIB

2018

A Library of Quadratic Programming Instances

Fabio Furini, Emiliano Traversi, Pietro Belotti, Antonio Frangioni, Ambros Gleixner, Nick Gould, Leo Liberti, Andrea Lodi, Ruth Misener, Hans Mittelmann, Nikolaos Sahinidis, Stefan Vigerske, Angelika Wiegele

MathProgComplex

2018

A Tool for for polynomial optimization problems with complex variables

Julie Sliwak, Miguel Anjos, Lucas Ltocart, Emiliano Traversi, Manuel Ruiz

Description

The MathProgComplex module is a tool for polynomial optimization problems with complex variables. These problems consist in optimizing a generic complex multivariate polynomial function, subject to some complex polynomial equality and inequality constraints. The MathProgComplex module enables: the manipulation of multivariate polynomials with complex numbers to construct polynomial optimization problems with complex variables (POP-C). the evaluation of polynomials, for example the objective and the constraints of a (POP-C) from points the resolution of a (POP-C) via a JuMP model the export of a (POP-C) to be solved using another language

min-hashing

2017

Topic mining data processing and visualization (mostly on wikipedia)

Ivan Vladimir Meza Ruiz, Gibran Fuentes-Pineda, Jorge Garcia Flores, Mohamed Chabouni, Zakaria Khezane

Description

Topic mining data processing and visualization (mostly on wikipedia)

Golfred

2017

Robot Experience Stories Generator (code)

Jorge Garcia Flores, Ivan Vladimir Meza Ruiz, Luis Alberto Pineda Cortes

Description

The aim of this system is to provide service robots with natural language capabilities to produce a Robot Experience Story for its human interlocutors. Golfred stories are narratives composed of the robot's holistic perception of a recently performed task: navigation, visual perceptions and action descriptions. We implemented with a narrate dialog model specifying the composition of situations necessary for a service robot to transform its task history record into a narrative knowledge representation. We provide SitLog algorithms allowing to analyze the robot's situation and behaviors sequence in order to generate a Golfred story of the task. Both the dialogue model and the algorithms can be embedded as compositional behaviors in any other SitLog task structure. We instantiated our model into the Golem service robot framework.

Logiciel Terminae - Version 2012

2012

Sylvie Szulman

Description

plateforme d'aide à la construction de ressources termino-ontologiques à partir de ressources textuelles. (http://lipn.fr/terminae/index.php/Main_Page)

Marionnet

2012

Jean-Vincent Loddo, Luca Saiu

Description

Logiciel pédagogique de simulation de réseaux d'ordinateurs, sous licence libre GNU GPL. Utilisé par plusieurs universités en France et à l'étranger. Financé par l'IUT de Villetaneuse et l'Institut Galilée

Reduction of VISION GRAPHS. Patent No. FR2955408 (A1)

2010

Nicolas Lerm, Franois Malgouyres, Lucas Ltocart

COlumn Generation In Transportation Optimization (COGITO). IDDN No. FR.001.050008.000.S.P.2009.000.30805

2009

Alfandari Laurent, Jrme Bier, Nathan Godard, Olivier Laval, Ltocart Lucas, Anass Nagih, Agns Plateau, Alexandre Quivet, Sadki Fenzar Jalila, Touati Nora, Toulouse Sophie

Logiciel (Universit Paris 13, Universit Paul Verlaine de Metz, ESSEC, CNAM), Agence pour la Protection des Programmes (APP)

METHODS FOR UPDATING AND TRAINING A SELF-ORGANISING MAP (WO/2009/081005 - PCT/FR2008/052288)

2009

Younès Bennani

CoSyVerif

2008

Complex Systems Verification

A Hamez, L Hillah, K Klai, F Kordon, L Petrucci, D Poitrenaud, Y Thierry-Mieg

Description

Tool presentation at PetriNets'08

Density-based Simultaneous 2-Level - Self-Organizing Map (DS2L-SOM)

2008

Guénaël Cabanes, Younès Bennani

Description

Enregistrement numéro IDDN.FR.001.490019.000S.P.2008.000.20000 auprès de l'agence de protection logiciel

Marionnet/Iutoppix

2007

un environnement pédagogique pour la simulation de réseaux locaux

Jean-Vincent Loddo, Thierry Hamon

Description

Démonstration à la conférence EIAH 2007 (Environnements Informatiques pour l'Apprentissage Humain) Projet E-Learning Université Paris 13

Synopsys

2006

Jean-Vincent Loddo

Description

Utilitaire permettant d'automatiser l'analyse lexicale, syntaxique et en partie sémantique des paramètres d'appel d'un script bash. Code source OCaml, licence GPL.

IUTOPPIX

2006

Jean-Vincent Loddo

Description

Cdrom amorçable, auto-configurable, dérivé de Knoppix 5.0.1, francisé et spécialisé pour les enseignements aux dép. R&T et INFO de l'IUT Villetaneuse. Licence GPL.

FAST

2005

Fast Acceleration of Symbolic Transition systems

S Bardin, A Finkel, J Leroux, L Petrucci

Description

Tool presentation at ACSD'05

Netxkiss

2005

Jean-Vincent Loddo

Description

Application (en mode texte) de simulation d'un réseaux d'ordinateurs qui exploite la technologie UML (User Mode Linux) et repose sur un DVD amorçable, auto-configurable, dérivé de Knoppix 3.8. Code source OCaml, licence GPL.

Knoppix4GTR

2004

Jean-Vincent Loddo

Description

Cdrom amorçable, auto-configurable, dérivé de Knoppix 3.8, francisé et spécialisé pour les enseignements au dép. GTR de l'IUT Villetaneuse. Licence GPL.