CoEvo-AHD is an LLM-driven dual-population co-evolutionary method for automated heuristic design in bi-component coupled combinatorial optimization that achieves competitive results on TTP and TPP.
Ecpv2: Fast, efficient, and scalable global optimization of lipschitz functions.Proceedings of the AAAI Conference on Artificial Intelligence, 40(43): 36909–36918, Mar
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A two-stage weakly supervised pipeline pretrains on auto-generated school labels from sparse points and fine-tunes on only 50 manual examples to achieve strong detection performance in aerial imagery.
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LLM-Driven Co-Evolutionary Automated Heuristic Design for Bi-Component Coupled Combinatorial Optimization
CoEvo-AHD is an LLM-driven dual-population co-evolutionary method for automated heuristic design in bi-component coupled combinatorial optimization that achieves competitive results on TTP and TPP.
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Label-Efficient School Detection from Aerial Imagery via Weakly Supervised Pretraining and Fine-Tuning
A two-stage weakly supervised pipeline pretrains on auto-generated school labels from sparse points and fine-tunes on only 50 manual examples to achieve strong detection performance in aerial imagery.