2 papers
cs.LG2026
Domain-Adaptable Reinforcement Learning for Code Generation with Dense Rewards
Erfan Aghadavoodi Jolfaei, Daniel Maninger, Abhinav Anand +2
Large language models show strong potential for automated code generation, but lack guarantees for correctness, quality, safety, and domain-specific constraints. For instance in ro…
cs.SE2026
Deep Graph-Language Fusion for Structure-Aware Code Generation
Mert Tiftikci, Amir Molzam Sharifloo, Mira Mezini
Pre-trained Language Models (PLMs) have the potential to transform software development tasks. However, despite significant advances, current PLMs struggle to capture the structure…