163 citations · 274 across the 45 of their papers we have counts for
5 papers · 1 filter
ACECode: A Reinforcement Learning Framework for Aligning Code Efficiency and Correctness in Code Language Models
Chengran Yang, Hong Jin Kang, Jieke Shi +1
CodeLLMs have demonstrated remarkable advancements in software engineering tasks. However, while these models can generate functionally correct code, they often produce code that i…
Synthesizing Efficient and Permissive Programmatic Runtime Shields for Neural Policies
Jieke Shi, Junda He, Zhou Yang +2
With the increasing use of neural policies in control systems, ensuring their safety and reliability has become a critical software engineering task. One prevalent approach to ensu…
Finding Safety Violations of AI-Enabled Control Systems through the Lens of Synthesized Proxy Programs
Jieke Shi, Zhou Yang, Junda He +4
Given the increasing adoption of modern AI-enabled control systems, ensuring their safety and reliability has become a critical task in software testing. One prevalent approach to…
Ecosystem of Large Language Models for Code
Zhou Yang, Jieke Shi, Premkumar Devanbu +1
The availability of vast amounts of publicly accessible data of source code and the advances in modern language models, coupled with increasing computational resources, have led to…
Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
Jieke Shi, Zhou Yang, David Lo
Large Language Models (LLMs) have recently shown remarkable capabilities in various software engineering tasks, spurring the rapid growth of the Large Language Models for Software…