Zobrazeno 1 - 10
of 3 474
pro vyhledávání: '"Geraud, A."'
Autor:
Benabdesselam, Mourad, Bahout, J., Mady, Franck, Blanc, Wilfried, Hamzaoui, Hicham El, Cassez, Andy, Delplace-Baudelle, Karen, Habert, Remi, Bouwmans, Geraud, Bouazaoui, Mohamed, Capoen, Bruno
Publikováno v:
IEEE Sensors Journal, 2021, 21 (24), pp.1-8
Two rods made from sol-gel silica have been doped with Ce ions or co-doped with Ce and Tb ions respectively. First, a thermoluminescence (TL) characterization of the trapping and luminescence parameters is carried out to understand the physical mecha
Externí odkaz:
http://arxiv.org/abs/2407.12364
Autor:
Faye, Géraud, Casanova, Morgane, Icard, Benjamin, Chanson, Julien, Gadek, Guillaume, Gravier, Guillaume, Égré, Paul
This paper summarizes the experiments and results of the HYBRINFOX team for the CheckThat! 2024 - Task 1 competition. We propose an approach enriching Language Models such as RoBERTa with embeddings produced by triples (subject ; predicate ; object)
Externí odkaz:
http://arxiv.org/abs/2407.03850
Autor:
Casanova, Morgane, Chanson, Julien, Icard, Benjamin, Faye, Géraud, Gadek, Guillaume, Gravier, Guillaume, Égré, Paul
This paper presents the HYBRINFOX method used to solve Task 2 of Subjectivity detection of the CLEF 2024 CheckThat! competition. The specificity of the method is to use a hybrid system, combining a RoBERTa model, fine-tuned for subjectivity detection
Externí odkaz:
http://arxiv.org/abs/2407.03770
Reinforcement learning (RL) has progressed substantially over the past decade, with much of this progress being driven by benchmarks. Many benchmarks are focused on video or board games, and a large number of robotics benchmarks lack diversity and re
Externí odkaz:
http://arxiv.org/abs/2407.14516
Autor:
Golkar, Siavash, Bietti, Alberto, Pettee, Mariel, Eickenberg, Michael, Cranmer, Miles, Hirashima, Keiya, Krawezik, Geraud, Lourie, Nicholas, McCabe, Michael, Morel, Rudy, Ohana, Ruben, Parker, Liam Holden, Blancard, Bruno Régaldo-Saint, Cho, Kyunghyun, Ho, Shirley
Transformers have revolutionized machine learning across diverse domains, yet understanding their behavior remains crucial, particularly in high-stakes applications. This paper introduces the contextual counting task, a novel toy problem aimed at enh
Externí odkaz:
http://arxiv.org/abs/2406.02585
Autor:
Allemand, Maxime, Jannin, Raphael, Dupuy, Géraud, Bureik, Jan-Philipp, Pezzè, Luca, Boiron, Denis, Clément, David
Tomography of single-particle-resolved detectors is of primary importance for characterizing particle correlations with applications in quantum metrology, quantum simulation and quantum computing. However, it is a non-trivial task in practice due to
Externí odkaz:
http://arxiv.org/abs/2405.01211
We propose a method to remotely verify the authenticity of Optically Variable Devices (OVDs), often referred to as ``holograms'', in identity documents. Our method processes video clips captured with smartphones under common lighting conditions, and
Externí odkaz:
http://arxiv.org/abs/2404.17253
Autor:
Icard, Benjamin, Maine, François, Casanova, Morgane, Faye, Géraud, Chanson, Julien, Gadek, Guillaume, Atemezing, Ghislain, Bancilhon, François, Égré, Paul
We present a corpus of 100 documents, OBSINFOX, selected from 17 sources of French press considered unreliable by expert agencies, annotated using 11 labels by 8 annotators. By collecting more labels than usual, by more annotators than is typically d
Externí odkaz:
http://arxiv.org/abs/2403.16099
Autor:
Faye, Géraud, Icard, Benjamin, Casanova, Morgane, Chanson, Julien, Maine, François, Bancilhon, François, Gadek, Guillaume, Gravier, Guillaume, Égré, Paul
This paper investigates the language of propaganda and its stylistic features. It presents the PPN dataset, standing for Propagandist Pseudo-News, a multisource, multilingual, multimodal dataset composed of news articles extracted from websites ident
Externí odkaz:
http://arxiv.org/abs/2402.03780
We present counting reward automata-a finite state machine variant capable of modelling any reward function expressible as a formal language. Unlike previous approaches, which are limited to the expression of tasks as regular languages, our framework
Externí odkaz:
http://arxiv.org/abs/2312.11364