activity
20202022
most citedPLAID: An Efficient Engine for Late Interaction Retrieval

8 citations · 25 across the 5 of their papers we have counts for

collaborators

6 papers

cs.IR2022

Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking

Keshav Santhanam, Jon Saad-Falcon, Martin Franz +7

Neural information retrieval (IR) systems have progressed rapidly in recent years, in large part due to the release of publicly available benchmarking tasks. Unfortunately, some di…

cs.IR20228 cited

PLAID: An Efficient Engine for Late Interaction Retrieval

Keshav Santhanam, Omar Khattab, Christopher Potts +1

Pre-trained language models are increasingly important components across multiple information retrieval (IR) paradigms. Late interaction, introduced with the ColBERT model and rece…

cs.IR20227 cited

Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction

Sebastian Hofstätter, Omar Khattab, Sophia Althammer +2

Recent progress in neural information retrieval has demonstrated large gains in effectiveness, while often sacrificing the efficiency and interpretability of the neural model compa…

cs.CL20213 cited

Hindsight: Posterior-guided training of retrievers for improved open-ended generation

Ashwin Paranjape, Omar Khattab, Christopher Potts +2

Many text generation systems benefit from using a retriever to retrieve passages from a textual knowledge corpus (e.g., Wikipedia) which are then provided as additional context to…

cs.IR20217 cited

Learning Passage Impacts for Inverted Indexes

Antonio Mallia, Omar Khattab, Nicola Tonellotto +1

Neural information retrieval systems typically use a cascading pipeline, in which a first-stage model retrieves a candidate set of documents and one or more subsequent stages re-ra…

cs.IR2020

ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

Omar Khattab, Matei Zaharia

Recent progress in Natural Language Understanding (NLU) is driving fast-paced advances in Information Retrieval (IR), largely owed to fine-tuning deep language models (LMs) for doc…