Towards generalizable neural program understanding and synthesis
The recent rapid advancement of deep learning, especially the development of the large language models (LLMs) has revolutionized the community of software engineering. Thanks to the great amount of open-sourced code-related data readily available for training, the neural network solutions manage to...
Saved in:
Main Author: | Li, Zhiming |
---|---|
Other Authors: | Liu Yang |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/181413 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Uncertainty guided ranking loss for enhanced domain generalizable stereo-matching
by: Nallapati, Nikhil
Published: (2024) -
Towards omni-generalizable neural methods for vehicle routing problems
by: ZHOU, Jianan, et al.
Published: (2023) -
On the generalizability of Neural Program Models with respect to semantic-preserving program transformations
by: RABIN, Md Rafiqul Islam, et al.
Published: (2021) -
Building generalizable deep learning solutions for mobile sensing
by: Xu, Huatao
Published: (2024) -
Assessing generalizability of CodeBERT
by: ZHOU, Xin, et al.
Published: (2021)