241 citations · 884 across the 50 of their papers we have counts for
7 papers · 2 filters
Quam: Adaptive Retrieval through Query Affinity Modelling
Mandeep Rathee, Sean MacAvaney, Avishek Anand
Building relevance models to rank documents based on user information needs is a central task in information retrieval and the NLP community. Beyond the direct ad-hoc search settin…
DyVo: Dynamic Vocabularies for Learned Sparse Retrieval with Entities
Thong Nguyen, Shubham Chatterjee, Sean MacAvaney +3
Learned Sparse Retrieval (LSR) models use vocabularies from pre-trained transformers, which often split entities into nonsensical fragments. Splitting entities can reduce retrieval…
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…
Neural Passage Quality Estimation for Static Pruning
Xuejun Chang, Debabrata Mishra, Craig Macdonald +1
Neural networks -- especially those that use large, pre-trained language models -- have improved search engines in various ways. Most prominently, they can estimate the relevance o…
Shallow Cross-Encoders for Low-Latency Retrieval
Aleksandr V. Petrov, Sean MacAvaney, Craig Macdonald
Transformer-based Cross-Encoders achieve state-of-the-art effectiveness in text retrieval. However, Cross-Encoders based on large transformer models (such as BERT or T5) are comput…
Evaluating the Explainability of Neural Rankers
Saran Pandian, Debasis Ganguly, Sean MacAvaney
Information retrieval models have witnessed a paradigm shift from unsupervised statistical approaches to feature-based supervised approaches to completely data-driven ones that mak…
A Deep Learning Approach for Selective Relevance Feedback
Suchana Datta, Debasis Ganguly, Sean MacAvaney +1
Pseudo-relevance feedback (PRF) can enhance average retrieval effectiveness over a sufficiently large number of queries. However, PRF often introduces a drift into the original inf…