2 papers
cs.SE2026
SPROUT: Scaling Agentic Reinforcement Learning for Long-Horizon Software Engineering
Mengyang Liu, Weiming Wang, Haixin Nan +6
Reinforcement learning (RL) has driven substantial progress in coding agents by relying on verified successful trajectories as learning signals. However, such trajectories are scar…
cs.CL2026
Archer: Adaptive Reuse of Cached Hidden States for Efficient Rollback in Diffusion Language Models
Xuning He, Zinan Sheng, Qingyuan Shi +5
Diffusion language models (DLMs) can revise earlier predictions as context evolves, but rollback requires costly full-sequence recomputation. Conventional key-value (KV) caching as…