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cs.LG2026
Long-Horizon Scaling: How Model Capabilities Shape the Returns to Computation
Haoyu Zheng, Zhengyu Chen, Huaisheng Zhu +5
Long-horizon agents improve solutions through sustained interaction, execution, and task feedback. Scaling studies relate performance to resources and capabilities, yet how existin…
cs.LG2026
Meta-Reinforcement Learning with Self-Reflection for Agentic Search
Teng Xiao, Yige Yuan, Hamish Ivison +6
This paper introduces MR-Search, an in-context meta reinforcement learning (RL) formulation for agentic search with self-reflection. Instead of optimizing a policy within a single…