Case study applies verifier-guided LLM evolutionary agents to contraction-order optimization in tensor networks and concludes that human validation remains essential.
Computing Tree Decompositions with FlowCutter: PACE 2017 Submission
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abstract
We describe the algorithm behind our PACE 2017 submission to the heuristic tree decomposition computation track. It was the only competitor to solve all instances and won a tight second place. The algorithm was originally developed in the context of accelerating shortest path computation on road graphs using multilevel partitions. We illustrate how this seemingly unrelated field fits into tree decomposition and parameterized complexity theory.
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2026 1verdicts
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Algorithmic algorithm development with LLMs: A Case Study on LLM-Usage for Contraction Order Optimization in Tensor Networks
Case study applies verifier-guided LLM evolutionary agents to contraction-order optimization in tensor networks and concludes that human validation remains essential.