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cs.AI2026
On Training Large Language Models for Long-Horizon Tasks: An Empirical Study of Horizon Length
Sunghwan Kim, Junhee Cho, Beong-woo Kwak +6
Large language models (LLMs) have shown promise as interactive agents that solve tasks through extended sequences of environment interactions. While prior work has primarily focuse…
cs.AI2026
RefineRL: Advancing Competitive Programming with Self-Refinement Reinforcement Learning
Shaopeng Fu, Xingxing Zhang, Li Dong +2
While large language models (LLMs) have demonstrated strong performance on complex reasoning tasks such as competitive programming (CP), existing methods predominantly focus on sin…