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Passage Retrieval

Passage retrieval is a specialized type of IR application that retrieves relevant passages (or pieces of text) rather than an entire ranked set of documents.

Papers

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Showing 51–75 of 268 papers

TitleStatusHype
Densifying Sparse Representations for Passage Retrieval by Representational SlicingCode1
Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?Code1
MFAQ: a Multilingual FAQ DatasetCode1
Simple Entity-Centric Questions Challenge Dense RetrieversCode1
Phrase Retrieval Learns Passage Retrieval, TooCode1
R2-D2: A Modular Baseline for Open-Domain Question AnsweringCode1
Robust Retrieval Augmented Generation for Zero-shot Slot FillingCode1
Dealing with Typos for BERT-based Passage Retrieval and RankingCode1
On Single and Multiple Representations in Dense Passage RetrievalCode1
Unsupervised Corpus Aware Language Model Pre-training for Dense Passage RetrievalCode1
One Question Answering Model for Many Languages with Cross-lingual Dense Passage RetrievalCode1
Exemplars-guided Empathetic Response Generation Controlled by the Elements of Human CommunicationCode1
Efficient Passage Retrieval with Hashing for Open-domain Question AnsweringCode1
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat ViolenceCode1
Passage Retrieval for Outside-Knowledge Visual Question AnsweringCode1
Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage RetrievalCode1
Overview of the TREC 2020 deep learning trackCode1
Weakly Supervised Label SmoothingCode1
Structural Text Segmentation of Legal DocumentsCode1
CoRT: Complementary Rankings from TransformersCode1
Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and EfficientlyCode1
Open-Domain Question Answering Goes Conversational via Question RewritingCode1
Embedding-based Zero-shot Retrieval through Query GenerationCode1
Generation-Augmented Retrieval for Open-domain Question AnsweringCode1
Leveraging Passage Retrieval with Generative Models for Open Domain Question AnsweringCode1
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