The very first sentence in the paper you link to says
The $(1 + (\lambda, \lambda))$ genetic algorithm (GA), proposed in , is a fairly
recent algorithm with very interesting properties.
We search for the given citation, and see that it says in Section 1.3 that
We use a uniform crossover that takes bits from the parent with probability $1 − c$ and from the winning offspring with
probability $c$ for some not too large crossover probability $c$. The outcome of such a crossover step will be close enough to
the parent to give us a good chance of keeping the positive aspects of the parent. To give newly found positive genes of the
winning offspring a reasonable chance to survive, we create again $\lambda$ offspring by this crossover. We call this algorithm the
$(1 + (\lambda, \lambda))$ GA.
You can do a similar lookup for the (1+1) EA algorithm.