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cs.LG2026
Bi-EZP: LLM-Guided Bilevel Program Evolution for Ensemble Zero-Cost Proxy Discovery
Yutao Lai, Kezhao Lai, Hai-Lin Liu
Zero-cost proxies enable neural architecture search (NAS) to rank candidate networks from statistics computed at initialization, avoiding repeated training. However, different prox…
cs.LG2026
CoAction: Cross-task Correlation-aware Pareto Set Learning
Xinyue Chen, Yingxuan Liang, Yiqin Huang +3
Pareto set learning (PSL) is an emerging paradigm in multi-objective optimization that trains neural networks to map preference vectors to Pareto optimal solutions. However, existi…
cs.LG2026
Beyond the Node: Clade-level Selection for Efficient MCTS in Automatic Heuristic Design
Kezhao Lai, Yutao Lai, Hai-Lin Liu
While Monte Carlo Tree Search (MCTS) shows promise in Large Language Model (LLM) based Automatic Heuristic Design (AHD), it suffers from a critical over-exploitation tendency under…