13 citations · 26 across the 17 of their papers we have counts for
4 papers · 1 filter
Interpreting Neural Combinatorial Optimization via Evolving Programmatic Bottlenecks
Haocheng Duan, Yuxin Guo, Jieyi Bi +4
Neural Combinatorial Optimization (NCO) achieves strong performance, yet its black-box nature remains a key roadblock to deployment and scientific diagnosis. Standard interpretabil…
FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization
Minwei Kong, Chonghe Jiang, Ao Qu +24
Large language models (LLMs) are increasingly used for optimization modeling and solver-code generation, yet practical operations research and optimization problems often require a…
CORAL: Towards Autonomous Multi-Agent Evolution for Open-Ended Discovery
Ao Qu, Han Zheng, Zijian Zhou +14
Large language model (LLM)-based evolution is a promising approach for open-ended discovery, where progress requires sustained search and knowledge accumulation. Existing methods s…
Probability-Aware Parking Selection
Cameron Hickert, Sirui Li, Zhengbing He +1
Current navigation systems conflate time-to-drive with the true time-to-arrive by ignoring parking search duration and the final walking leg. Such underestimation can significantly…