ECO uses supervised warm-up plus iterative batched DPO on a Mamba backbone to reach top neural performance on TSP and CVRP while lowering memory growth and raising throughput.
Genetic algorithms,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Curriculum-based heterogeneous-agent PPO algorithm yields over 30% better sensing performance than baselines in simulated multi-UAV ISAC tasks.
citing papers explorer
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Rethinking Efficiency in Neural Combinatorial Optimization: Batched Preference Optimization with Mamba
ECO uses supervised warm-up plus iterative batched DPO on a Mamba backbone to reach top neural performance on TSP and CVRP while lowering memory growth and raising throughput.
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Curriculum-Guided Heterogeneous Multi-Agent Intelligence for Multi-UAV Cooperative ISAC
Curriculum-based heterogeneous-agent PPO algorithm yields over 30% better sensing performance than baselines in simulated multi-UAV ISAC tasks.