2 papers
cs.LG2025
SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms
Alex Havrilla, Edward Hughes, Mikayel Samvelyan +1
Large language model (LLM) driven synthetic data generation has emerged as a powerful method for improving model reasoning capabilities. However, most methods either distill large…
cs.LG2025
Can Transformers Reason Logically? A Study in SAT Solving
Leyan Pan, Vijay Ganesh, Jacob Abernethy +2
We formally study the logical reasoning capabilities of decoder-only Transformers in the context of the boolean satisfiability (SAT) problem. First, we prove by construction that d…