We have 2 of 5 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This paper examines whether synthetic training artifacts can support the complete SFT-to-RL cycle for competitive programming, and synthesizes tasks, verified solutions, and reliable test cases that serve as reward signals for reinforcement learning.
DPIAgent is proposed, a structured agentic framework built on three principles, Divide, Protocol, Isolate (DPI), that mitigates compound-objective ambiguity and goal drift, and shows that architectural structure and backbone capability are complementary axes rather than substitutes, demonstrating DPI's generalizability...
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
