3 papers
cs.MA2025
AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs
Florian Grötschla, Luis Müller, Jan Tönshoff +2
Large-language models (LLMs) have demonstrated powerful problem-solving capabilities, in particular when organized in multi-agent systems. However, the advent of such systems also…
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
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…