Graphs are a standard representation for data in the social sciences, cybersecurity, computer infrastructure, bioinformatics, and more. Typical real-world graphs are sparse, meaning the average degree is small (in the tens, while the number of vertices is more than millions). When graph data is collected from a source,...
This work introduces EigenLI, a spectral approximation framework that compresses late-interaction representations via document-specific low-dimensional subspaces and consistently outperforms comparable single-vector surrogates such as MUVERA.
S. Archish, Sabyasachi Basu, Ankit Garg et al.· 0 citations
This work provides the first explicit family of query and document sets, together with their relevance matrices, for which single-vector embeddings that rank all relevant documents above irrelevant ones require exponential size, whereas polynomial-size multi-vector embeddings suffice.
Mihir Agarwal, Viraj Agrawal, Sabyasachi Basu et al.· 1 citation
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