Author

Kishore Konda

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Preprint Aug 2026

Hypergraph Embedding Indexing for Efficient Dense Vector Retrieval

Dense vector retrieval has become the foundation of modern semantic search, yet existing approximate nearest neighbor (ANN) indexes treat an embedding as an indivisible point in a high-dimensional space. In this work, we propose the Hypergraph Embedding Index (HEI), a framework that instead organizes documents accordin...

Kishore Konda · 0 citations

Preprint Aug 2026

Domain-Specific Text Embedding Models for Entity Resolution

General-purpose text embedding models are designed to capture semantic similarity but are not optimised for distinguishing entity records that represent the same real-world business or person. This limitation affects applications such as entity resolution and duplicate record retrieval, where small textual differences...

Khajesh Sapram, S. Raju, Kishore Konda · 0 citations