ACCoRD trains an ANN with PPO-Clip reinforcement learning to select conflict resolution actions in O-RAN, reducing negative network events versus rule-based methods in medium and high traffic simulations.
2108.12627 , archivePrefix=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A two-stage residual-aware framework adds a meta-corrector after a base transformer to model structured errors and reports state-of-the-art results on eight time-series benchmarks.
citing papers explorer
-
ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps
ACCoRD trains an ANN with PPO-Clip reinforcement learning to select conflict resolution actions in O-RAN, reducing negative network events versus rule-based methods in medium and high traffic simulations.
-
One Step Closer to Ground Truth: A Multi-Scale Residual-Aware Representation Learning Pipeline for Predicting Time Series Data
A two-stage residual-aware framework adds a meta-corrector after a base transformer to model structured errors and reports state-of-the-art results on eight time-series benchmarks.