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Publications associées (82)

Silent Bugs Matter: A Study of Compiler-Introduced Security Bugs

Compilers assure that any produced optimized code is semantically equivalent to the original code. However, even "correct" compilers may introduce security bugs as security properties go beyond translation correctness. Security bugs introduced by such corr ...

Berkeley2023

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In real-world scenarios, achieving domain generalization (DG) presents significant challenges as models are required to generalize to unknown target distributions. Generalizing to unseen multi-modal distributions poses even greater difficulties due to the ...

2023

Understanding Revision Behavior in Adaptive Writing Support Systems for Education

Paola Mejia Domenzain, Luca Mouchel, Thiemo Wambsganss

Revision behavior in adaptive writing support systems is an important and relatively new area of research that can improve the design and effectiveness of these tools, and promote students' self-regulated learning (SRL). Understanding how these tools are u ...

Zenodo2023

We present an approach for using formal methods in embedded systems and its evaluation on a case study. In our approach, the developers describe the system in a restricted subset of the high-level programming language Scala. We then use 1) a verification s ...

2022

The Dependent Object Type (DOT) calculus was designed to put Scala on a sound basis, but while DOT relies on structural subtyping, Scala is a fundamentally class-based language. This impedance mismatch means that a proof of DOT soundness by itself is not e ...

2022

Formally verifying the correctness of software network functions (NFs) is necessary for network reliability, yet existing techniques require full source code and mandate the use of specific data structures. We describe an automated technique to verify NF b ...

USENIX Association2022

RayTran: 3D Pose Estimation and Shape Reconstruction of Multiple Objects from Videos with Ray-Traced Transformers

Michal Jan Tyszkiewicz, Vittorio Ferrari, Kevis-Kokitsi Maninis

We propose a transformer-based neural network architecture for multi-object 3D reconstruction from RGB videos. It relies on two alternative ways to represent its knowledge: as a global 3D grid of features and an array of view-specific 2D grids. We progress ...

Springer2022

Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions

Mathieu Salzmann, Vincent Lepetit, Yinlin Hu, Van Nguyen Nguyen, Yang Xiao

We present a method that can recognize new objects and estimate their 3D pose in RGB images even under partial occlusions. Our method requires neither a training phase on these objects nor real images depicting them, only their CAD models. It relies on a s ...

IEEE COMPUTER SOC2022

U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search

Pascal Frossard, Nikolaos Dimitriadis, Ahmet Caner Yüzügüler

Optimizing resource utilization in target platforms is key to achieving high performance during DNN inference. While optimizations have been proposed for inference latency, memory footprint, and energy consumption, prior hardware-aware neural architecture ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

A Study on More Realistic Room Simulation for Far-Field Keyword Spotting

Eric Bezzam, Robin Scheibler

We investigate the impact of more realistic room simulation for training far-field keyword spotting systems without fine-tuning on in-domain data. To this end, we study the impact of incorporating the following factors in the room impulse response (RIR) ge ...

IEEE2020

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