EP07 - Efficient Neural Search: Rethinking Inverted Indexes for Learned Sparse Representations. With Dr. Franco Maria Nardini
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EP07 - Efficient Neural Search: Rethinking Inverted Indexes for Learned Sparse Representations. With Dr. Franco Maria Nardini
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About this listen
In this episode of targz, Franco Maria Nardini, Research Director at ISTI-CNR, explains Seismic, a two-level inverted index for fast retrieval over learned sparse representations. It beats graph-based state-of-the-art methods by up to 3.5x in speed with comparable memory, and opens new directions in inference-free and edge retrieval.
Want to know more? checkout the paper: Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations
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