3 papers
cs.SE2026
ARIADNE: Agentic Reward-Informed Adaptive Decision Exploration via Blackboard-Driven MCTS for Competitive Program Generation
Minnan Wei, Xiang Chen, Xiaoshuai Niu +1
Competitive program generation aims to automatically produce correct and efficient solutions for programming-contest problems under strict time and memory constraints. Existing LLM…
cs.SE2025
Improving vulnerability type prediction and line-level detection via adversarial training-based data augmentation and multi-task learning
Siyu Chen, Jiongyi Yang, Xiang Chen +3
Context: Software vulnerabilities pose a significant threat to modern software systems, as evidenced by the growing number of reported vulnerabilities and cyberattacks. These escal…
cs.SI2025
Evaluating and Improving Large Language Models for Competitive Program Generation
Minnan Wei, Ziming Li, Xiang Chen +5
Context: Due to the demand for strong algorithmic reasoning, complex logic implementation, and strict adherence to input/output formats and resource constraints, competitive progra…