4 papers
When Machine Learning Meets Importance Sampling: A More Efficient Rare Event Estimation Approach
Ruoning Zhao, Xinyun Chen
Driven by applications in telecommunication networks, we explore the simulation task of estimating rare event probabilities for tandem queues in their steady state. Existing litera…
Vulnerability Detection with Code Language Models: How Far Are We?
Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim +6
In the context of the rising interest in code language models (code LMs) and vulnerability detection, we study the effectiveness of code LMs for detecting vulnerabilities. Our anal…
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
Chengshu Li, Jacky Liang, Andy Zeng +7
Code provides a general syntactic structure to build complex programs and perform precise computations when paired with a code interpreter - we hypothesize that language models (LM…
Steady-State Analysis and Online Learning for Queues with Hawkes Arrivals
Xinyun Chen, Guiyu Hong
We investigate the long-run behavior of single-server queues with Hawkes arrivals and general service distributions and related optimization problems. In detail, utilizing novel co…