size of a task) it can allocate storage for it in the stack frame of
One by-product of weighing the candidates by their distance is that the resulting output image is prone to false contours or banding. Increasing reduces this effect at the cost of added granularity or high frequency noise due to the introduction of ever more distant colours to the set. I recommend taking a look at the original paper if you’re interested in learning a bit more about the algorithm[1].
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For the test to be fair for LLMs, the SAT instance should be reasonably large, but not too big. I can't just give SAT problems with thousands of variables. But also it shouldn't be too easy.
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