DoSA: Dots Sparse Attention

DoSA (Dots Sparse Attention) is a lossless method that makes sparse attention computation conditional by using a seed set and bounds to direct full scoring toward eligible candidates, accelerating the Indexer by up to 2.74 times over SGLang and 1.69 times over LiteTopK.