1 citations · 2 across the 4 of their papers we have counts for
4 papers
Was it Slander? Towards Exact Inversion of Generative Language Models
Adrians Skapars, Edoardo Manino, Youcheng Sun +1
Training large language models (LLMs) requires a substantial investment of time and money. To get a good return on investment, the developers spend considerable effort ensuring tha…
ESBMC-Python: A Bounded Model Checker for Python Programs
Bruno Farias, Rafael Menezes, Eddie B. de Lima Filho +2
This paper introduces a tool for verifying Python programs, which, using type annotation and front-end processing, can harness the capabilities of a bounded model-checking (BMC) pi…
An Overview of Structural Coverage Metrics for Testing Neural Networks
Muhammad Usman, Youcheng Sun, Divya Gopinath +3
Deep neural network (DNN) models, including those used in safety-critical domains, need to be thoroughly tested to ensure that they can reliably perform well in different scenarios…
Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models
Jialuo Chen, Jingyi Wang, Tinglan Peng +6
Deep learning (DL) models, especially those large-scale and high-performance ones, can be very costly to train, demanding a great amount of data and computational resources. Unauth…