23 citations · 38 across the 8 of their papers we have counts for
9 papers
Raw-Routed Mixture of Adapters: A Causal Intervention for Routing Collapse in Time Series Foundation Models
Hung Phan, Thuy T. Nguyen, Minh Ngoc Dinh +1
Time series foundation models (TSFMs) commonly adapt to new data by attaching a single trainable head to a frozen backbone, a one-size-fits-all setup that underfits heterogeneous r…
Enhancing Small Language Models for Power Outage Report Generation via Minimum Risk Training
Hung Phan, Waqwoya Abebe, Youssef Hussein +3
Minimum Risk Training (MRT) enables neural machine translation models to directly optimize sequence-level evaluation metrics instead of relying only on token- level maximum-likelih…
The Landscape and Challenges of HPC Research and LLMs
Le Chen, Nesreen K. Ahmed, Akash Dutta +14
Recently, language models (LMs), especially large language models (LLMs), have revolutionized the field of deep learning. Both encoder-decoder models and prompt-based techniques ha…
AutoParLLM: GNN-guided Context Generation for Zero-Shot Code Parallelization using LLMs
Quazi Ishtiaque Mahmud, Ali TehraniJamsaz, Hung Phan +5
In-Context Learning (ICL) has been shown to be a powerful technique to augment the capabilities of LLMs for a diverse range of tasks. This work proposes \ourtool, a novel way to ge…
Evaluating and Optimizing the Effectiveness of Neural Machine Translation in Supporting Code Retrieval Models: A Study on the CAT Benchmark
Hung Phan, Ali Jannesari
Neural Machine Translation (NMT) is widely applied in software engineering tasks. The effectiveness of NMT for code retrieval relies on the ability to learn from the sequence of to…
Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation
Le Chen, Quazi Ishtiaque Mahmud, Hung Phan +2
Detecting parallelizable code regions is a challenging task, even for experienced developers. Numerous recent studies have explored the use of machine learning for code analysis an…
Heterogeneous Graph Neural Networks for Software Effort Estimation
Hung Phan, Ali Jannesari
Software effort can be measured by story point [35]. Current approaches for automatically estimating story points focus on applying pre-trained embedding models and deep learning f…
Story Point Effort Estimation by Text Level Graph Neural Network
Hung Phan, Ali Jannesari
Estimating the software projects' efforts developed by agile methods is important for project managers or technical leads. It provides a summary as a first view of how many hours a…
Self Learning from Large Scale Code Corpus to Infer Structure of Method Invocations
Hung Phan
Automatically generating code from a textual description of method invocation confronts challenges. There were two current research directions for this problem. One direction focus…