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Imagine handling collisions in a hash table by storing, in each cell, the bit-wise exclusive-or of the set of keys hashing there. This appears to be a terrible idea: For $αn$ keys and $n$ buckets, where $α$ is constant, we expect that a constant fraction of the keys will be unrecoverable due to collisions. We show that if this collision resolution strategy is repeated three times independently the situation reverses: If $α$ is below a threshold of $\approx 0.81$ then we can recover the set of all inserted keys in linear time with high probability. Even though the description of our data structure is simple, its analysis is nontrivial. Our approach can be seen as a variant of the Invertible Bloom Filter (IBF) of Eppstein and Goodrich. While IBFs involve an explicit checksum per bucket to decide whether the bucket stores a single key, we exploit the idea of quotienting, namely that some bits of the key are implicit in the location where it is stored. We let those serve as an implicit checksum. These bits are not quite enough to ensure that no errors occur and the main technical challenge is to show that decoding can recover from these errors.