no code implementations • 26 Feb 2024 • Isabelle Mohr, Markus Krimmel, Saba Sturua, Mohammad Kalim Akram, Andreas Koukounas, Michael Günther, Georgios Mastrapas, Vinit Ravishankar, Joan Fontanals Martínez, Feng Wang, Qi Liu, Ziniu Yu, Jie Fu, Saahil Ognawala, Susana Guzman, Bo wang, Maximilian Werk, Nan Wang, Han Xiao
We introduce a novel suite of state-of-the-art bilingual text embedding models that are designed to support English and another target language.
no code implementations • 7 Mar 2019 • Saahil Ognawala, Fabian Kilger, Alexander Pretschner
Guided fuzzing has, in recent years, been able to uncover many new vulnerabilities in real-world software due to its fast input mutation strategies guided by path-coverage.
Software Engineering
no code implementations • 24 Jul 2018 • Saahil Ognawala, Ricardo Nales Amato, Alexander Pretschner, Pooja Kulkarni
Compositional analysis, based on symbolic execution, is an automated testing method to find vulnerabilities in medium- to large-scale programs consisting of many interacting components.
Software Engineering
no code implementations • 26 Nov 2017 • Saahil Ognawala, Thomas Hutzelmann, Eirini Psallida, Alexander Pretschner
Fuzzing and symbolic execution are popular techniques for finding vulnerabilities and generating test-cases for programs.
Software Engineering
no code implementations • 21 Jun 2016 • Maximilian Karl, Artur Lohrer, Dhananjay Shah, Frederik Diehl, Max Fiedler, Saahil Ognawala, Justin Bayer, Patrick van der Smagt
We study the responses of two tactile sensors, the fingertip sensor from the iCub and the BioTac under different external stimuli.
no code implementations • 21 Oct 2014 • Saahil Ognawala, Justin Bayer
Advancements in parallel processing have lead to a surge in multilayer perceptrons' (MLP) applications and deep learning in the past decades.