3 papers
cs.AI2025
e-boost: Boosted E-Graph Extraction with Adaptive Heuristics and Exact Solving
Jiaqi Yin, Zhan Song, Chen Chen +3
E-graphs have attracted growing interest in many fields, particularly in logic synthesis and formal verification. E-graph extraction is a challenging NP-hard combinatorial optimiza…
cs.LG2025
HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization
Hongzheng Chen, Yingheng Wang, Yaohui Cai +10
While Large Language Models (LLMs) have demonstrated significant advancements in reasoning and agent-based problem-solving, current evaluation methodologies fail to adequately asse…
cs.LG2025
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs
Zichao Yue, Chenhui Deng, Zhiru Zhang
Graph neural networks (GNNs) are widely used for learning node embeddings in graphs, typically adopting a message-passing scheme. This approach, however, leads to the neighbor expl…