2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2025
Learning from Algorithm Feedback: One-Shot SAT Solver Guidance with GNNs
Jan Tönshoff, Martin Grohe
Boolean Satisfiability (SAT) solvers are foundational to computer science, yet their performance typically hinges on hand-crafted heuristics. This work introduces Reinforcement Lea…
cs.LG2025★ 2 cited
Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks
Maya Bechler-Speicher, Ben Finkelshtein, Fabrizio Frasca +9
While machine learning on graphs has demonstrated promise in drug design and molecular property prediction, significant benchmarking challenges hinder its further progress and rele…