1 citations · 1 across the 2 of their papers we have counts for
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Mixture-of-Experts Language Models Can Be Strong and Efficient Retrievers
Anubhav Shrestha, Safal Shrestha, Minwu Kim +2
Recent work has shown that fine-tuning decoder-only large language models (LLMs) for retrieval yields strong first-stage retrievers, with effectiveness improving as backbones grow…
Faster Learned Sparse Retrieval with Block-Max Pruning
Antonio Mallia, Torten Suel, Nicola Tonellotto
Learned sparse retrieval systems aim to combine the effectiveness of contextualized language models with the scalability of conventional data structures such as inverted indexes. N…
DeeperImpact: Optimizing Sparse Learned Index Structures
Soyuj Basnet, Jerry Gou, Antonio Mallia +1
A lot of recent work has focused on sparse learned indexes that use deep neural architectures to significantly improve retrieval quality while keeping the efficiency benefits of th…