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Found 6 papers, 0 papers with code
Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings
We introduce a novel suite of state-of-the-art bilingual text embedding models that are designed to support English and another target language.
Compositional Fuzzing Aided by Targeted Symbolic Execution
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
Automatically Assessing Vulnerabilities Discovered by Compositional Analysis
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
Improving Function Coverage with Munch: A Hybrid Fuzzing and Directed Symbolic Execution Approach
Fuzzing and symbolic execution are popular techniques for finding vulnerabilities and generating test-cases for programs.
Software Engineering
ML-based tactile sensor calibration: A universal approach
We study the responses of two tactile sensors, the fingertip sensor from the iCub and the BioTac under different external stimuli.
Regularizing Recurrent Networks - On Injected Noise and Norm-based Methods
Advancements in parallel processing have lead to a surge in multilayer perceptrons' (MLP) applications and deep learning in the past decades.
