30 citations · 38 across the 3 of their papers we have counts for
3 papers
LexBoost: Improving Lexical Document Retrieval with Nearest Neighbors
Hrishikesh Kulkarni, Nazli Goharian, Ophir Frieder +1
Sparse retrieval methods like BM25 are based on lexical overlap, focusing on the surface form of the terms that appear in the query and the document. The use of inverted indices in…
Genetic Approach to Mitigate Hallucination in Generative IR
Hrishikesh Kulkarni, Nazli Goharian, Ophir Frieder +1
Generative language models hallucinate. That is, at times, they generate factually flawed responses. These inaccuracies are particularly insidious because the responses are fluent…
Lexically-Accelerated Dense Retrieval
Hrishikesh Kulkarni, Sean MacAvaney, Nazli Goharian +1
Retrieval approaches that score documents based on learned dense vectors (i.e., dense retrieval) rather than lexical signals (i.e., conventional retrieval) are increasingly popular…