MiniSat v1.13 - A SAT Solver with Conflict-Clause Minimization

By Niklas Sörensson, Niklas Eén. 2005

310 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/94a25711f91bc18d666ad343024c1c4ed6e62a8e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Xinyun Chen
2. Pushmeet Kohli
3. David Saxton
4. Edward Grefenstette
5. Yoshua Bengio
6. Yuandong Tian
7. Richard Evans
8. Mohit Bansal

Citations in the corpus

• Learning to Perform Local Rewriting for Combinatorial Optimization (2018, background): “It takes commercial solvers decades to tune to strong performance in practical problems [15, 44, 19].”
• AppSAT: Approximately deobfuscating integrated circuits (2017, methodology): “The framework utilizes Minisat [22] for SAT-solving and includes the conventional exact SAT attack augmented with intermediate key vector extraction, error estimation/calculation, and random query reinforcement routines.”
• Can Neural Networks Understand Logical Entailment? (2018, methodology): “To generate these 4-tuples, we first generate pairs (A,B) such thatA B. (To test ifA B, we test whether A ∧ ¬B is satisfiable, using minisat (Sorensson & Een, 2005)).”