5 papers · 1 filter
Exploration-Preserving Policy Optimization
Hangzhan jin, Mohammad Hamdaqa, Doina Precup
Reinforcement learning with verifiable rewards improves reasoning, while the allocation of learning signal shapes which solutions remain accessible under repeated sampling. Group-r…
The Hidden Environmental Cost of Poor Coding Practices in TensorFlow and Keras Applications: A Study on Resource Leaks and Carbon Emissions
Bashar Abdallah, Gustavo Santos, Rola Al Bataineh +2
Efficiency and sustainability are critical considerations in the development and deployment of machine learning (ML) applications. Among the factors influencing sustainability, res…
Rotation-Preserving Supervised Fine-Tuning
Hangzhan Jin, Tianwei Ni, Lu Li +3
Supervised fine-tuning (SFT) improves in-domain performance but can degrade out-of-domain (OOD) generalization. Prior work suggests that this degradation is related to changes in d…
PLMGH: What Matters in PLM-GNN Hybrids for Code Classification and Vulnerability Detection
Mohamed Taoufik Kaouthar El Idrissi, Edward Zulkoski, Mohammad Hamdaqa
Code understanding models increasingly rely on pretrained language models (PLMs) and graph neural networks (GNNs), which capture complementary semantic and structural information.…
Mining the YARA Ecosystem: From Ad-Hoc Sharing to Data-Driven Threat Intelligence
Dectot--Le Monnier de Gouville Esteban, Mohammad Hamdaqa, Moataz Chouchen
YARA has established itself as the de facto standard for "Detection as Code," enabling analysts and DevSecOps practitioners to define signatures for malware identification across t…