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Model Counting and Uniform Sampling Instances

<p>These instances mainly consist of the formulas that have been used in the evaluation of recent model counting techniques. A significant set of benchmarks involving sampling set, i.e., they are meant for projected model counting.<br> <br> The specification for reading such files&nbsp;can be found at&nbsp;<a href="https://github.com/meelgroup/approxmc">https://github.com/meelgroup/approxmc</a><br> <br> Here is list of some of the papers that have reported results on these instances:</p> <p>1.&nbsp;BIRD: Engineering an Efficient CNF-XOR SAT Solver and its Applications to Approximate Model Counting<br> Mate Soos and Kuldeep S. Meel<br> Proceedings of AAAI Conference on Artificial Intelligence (AAAI),&nbsp;2019.</p> <p>2.&nbsp;Accelerating Approximate Techniques for Counting and Sampling Models Through Refined CNF-XOR Solving<br> Mate Soos, Stephan Gocht, and Kuldeep S. Meel<br> Proceedings of International Conference on Computer-Aided Verification (CAV),&nbsp;2020.<br> &nbsp;</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

Topics