203 citations · 414 across the 35 of their papers we have counts for
10 papers · 1 filter
Benchmarking Large Language Models for Automated Verilog RTL Code Generation
Shailja Thakur, Baleegh Ahmad, Zhenxing Fan +5
Automating hardware design could obviate a significant amount of human error from the engineering process and lead to fewer errors. Verilog is a popular hardware description langua…
Privacy-Preserving Collaborative Learning through Feature Extraction
Alireza Sarmadi, Hao Fu, Prashanth Krishnamurthy +2
We propose a framework in which multiple entities collaborate to build a machine learning model while preserving privacy of their data. The approach utilizes feature embeddings fro…
An Upper Bound for the Distribution Overlap Index and Its Applications
Hao Fu, Prashanth Krishnamurthy, Siddharth Garg +1
This paper proposes an easy-to-compute upper bound for the overlap index between two probability distributions without requiring any knowledge of the distribution models. The compu…
Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants
Gustavo Sandoval, Hammond Pearce, Teo Nys +3
Large Language Models (LLMs) such as OpenAI Codex are increasingly being used as AI-based coding assistants. Understanding the impact of these tools on developers' code is paramoun…
Characterizing and Optimizing End-to-End Systems for Private Inference
Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha +2
In two-party machine learning prediction services, the client's goal is to query a remote server's trained machine learning model to perform neural network inference in some applic…
Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale
Akshaj Kumar Veldanda, Ivan Brugere, Jiahao Chen +3
The success of DNNs is driven by the counter-intuitive ability of over-parameterized networks to generalize, even when they perfectly fit the training data. In practice, test error…