This paper proposes using noisy binary node labels, which indicate cluster membership, to improve local graph clustering. By constructing a weighted graph based on the noisy labels, then performing diffusion on this graph, they are able to recover target clusters more accurately. With theoretical analysis and experiments on real datasets, they show that even fairly inac...