1 citations · 1 across the 3 of their papers we have counts for
5 papers
Do Machines Struggle Where Humans Do? LLM and Human Comprehension of Obfuscated Code
Jack Le, Anh H. N. Nguyen, Tien N. Nguyen
While code obfuscation impairs human code comprehension, it remains unclear if large language models share these failure modes. Building directly on a recent human study of program…
The Effect of Code Obfuscation on Human Program Comprehension
Anh H. N. Nguyen, Jack Le, Ilse Lahnstein Coronado +1
We investigate how code obfuscation influences human understanding of programs through an output-prediction task. To study this effect, we construct multiple levels of obfuscation,…
LEANCODE: Understanding Models Better for Code Simplification of Pre-trained Large Language Models
Yan Wang, Ling Ding, Tien N Nguyen +2
Large Language Models for code often entail significant computational complexity, which grows significantly with the length of the input code sequence. We propose LeanCode for code…
Rectifier: Code Translation with Corrector via LLMs
Xin Yin, Chao Ni, Tien N. Nguyen +2
Software migration is garnering increasing attention with the evolution of software and society. Early studies mainly relied on handcrafted translation rules to translate between t…
Natural Is The Best: Model-Agnostic Code Simplification for Pre-trained Large Language Models
Yan Wang, Xiaoning Li, Tien Nguyen +3
Pre-trained Large Language Models (LLM) have achieved remarkable successes in several domains. However, code-oriented LLMs are heavy in computational complexity, and quadratically…