1 citations · 1 across the 5 of their papers we have counts for
5 papers
LLM-based Hardware Development with Hierarchical IRs and End-to-End Multi-Agent Workflow
Chenyang Yin, Agasthi Haputhanthri, Aditya Anirudh Jonnalagadda +7
Large language models (LLMs) are increasingly used in software development, but their use in complex hardware design remains limited. This gap stems from both the scarcity of publi…
Verifying the Generalization of Deep Learning to Out-of-Distribution Domains
Guy Amir, Osher Maayan, Tom Zelazny +2
Deep neural networks (DNNs) play a crucial role in the field of machine learning, demonstrating state-of-the-art performance across various application domains. However, despite th…
Verifying Generalization in Deep Learning
Guy Amir, Osher Maayan, Tom Zelazny +2
Deep neural networks (DNNs) are the workhorses of deep learning, which constitutes the state of the art in numerous application domains. However, DNN-based decision rules are notor…
On Optimizing Back-Substitution Methods for Neural Network Verification
Tom Zelazny, Haoze Wu, Clark Barrett +1
With the increasing application of deep learning in mission-critical systems, there is a growing need to obtain formal guarantees about the behaviors of neural networks. Indeed, ma…
Verification-Aided Deep Ensemble Selection
Guy Amir, Tom Zelazny, Guy Katz +1
Deep neural networks (DNNs) have become the technology of choice for realizing a variety of complex tasks. However, as highlighted by many recent studies, even an imperceptible per…