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cs.IR2026
Spike Hijacking in Late-Interaction Retrieval
Karthik Suresh, Tushar Vatsa, Tracy King +2
Late-interaction retrieval models rely on hard maximum similarity (MaxSim) to aggregate token-level similarities. Although effective, this winner-take-all pooling rule may structur…
cs.IR2024
Smart Multi-Modal Search: Contextual Sparse and Dense Embedding Integration in Adobe Express
Cherag Aroraa, Tracy Holloway King, Jayant Kumar +6
As user content and queries become increasingly multi-modal, the need for effective multi-modal search systems has grown. Traditional search systems often rely on textual and metad…
cs.IR2024
Semantic In-Domain Product Identification for Search Queries
Sanat Sharma, Jayant Kumar, Twisha Naik +3
Accurate explicit and implicit product identification in search queries is critical for enhancing user experiences, especially at a company like Adobe which has over 50 products an…