A decoupled planner-executor GUI agent, trained by per-app reinforcement learning followed by specialist-to-generalist distillation, lifts ScienceBoard success from about 7.6% to 21.0% average and 40% pass@8.
Claude’s extended thinking
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
CODA: Coordinating the Cerebrum and Cerebellum for a Dual-Brain Computer Use Agent with Decoupled Reinforcement Learning
A decoupled planner-executor GUI agent, trained by per-app reinforcement learning followed by specialist-to-generalist distillation, lifts ScienceBoard success from about 7.6% to 21.0% average and 40% pass@8.