Showing 2026Show all
2 papers · 1 filter
cs.DC2026
Scheduling the Unschedulable: Taming Black-Box LLM Inference at Scale
Renzhong Yuan, Yijun Zeng, Xiaosong Gao +3
When output token counts can be predicted at submission time (Gan et al., 2026), client-side scheduling against a black-box LLM API becomes semi-clairvoyant: decisions condition on…
cs.LG2026
SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
Peng Xia, Jianwen Chen, Hanyang Wang +10
Large Language Model (LLM) agents have shown stunning results in complex tasks, yet they often operate in isolation, failing to learn from past experiences. Existing memory-based m…