117 citations · 692 across the 53 of their papers we have counts for
4 papers · 1 filter
Fine-Grained Distillation for Long Document Retrieval
Yucheng Zhou, Tao Shen, Xiubo Geng +4
Long document retrieval aims to fetch query-relevant documents from a large-scale collection, where knowledge distillation has become de facto to improve a retriever by mimicking a…
LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval
Tao Shen, Xiubo Geng, Chongyang Tao +5
In large-scale retrieval, the lexicon-weighting paradigm, learning weighted sparse representations in vocabulary space, has shown promising results with high quality and low latenc…
Towards Robust Ranker for Text Retrieval
Yucheng Zhou, Tao Shen, Xiubo Geng +5
A ranker plays an indispensable role in the de facto 'retrieval & rerank' pipeline, but its training still lags behind -- learning from moderate negatives or/and serving as an auxi…
UnifieR: A Unified Retriever for Large-Scale Retrieval
Tao Shen, Xiubo Geng, Chongyang Tao +4
Large-scale retrieval is to recall relevant documents from a huge collection given a query. It relies on representation learning to embed documents and queries into a common semant…