Passage Retrieval
111 papers with code • 4 benchmarks • 8 datasets
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.
Benchmarks
These leaderboards are used to track progress in Passage Retrieval
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Libraries
Use these libraries to find Passage Retrieval models and implementations
Natural Questions
MS MARCO
BEIR
EntityQuestions
QAMPARI
CoreSearch
Most implemented papers
Dealing with Typos for BERT-based Passage Retrieval and Ranking
ielab/typos-aware-bert
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EMNLP 2021
Our experimental results on the MS MARCO passage ranking dataset show that, with our proposed typos-aware training, DR and BERT re-ranker can become robust to typos in queries, resulting in significantly improved effectiveness compared to models trained without appropriately accounting for typos.
Robust Retrieval Augmented Generation for Zero-shot Slot Filling
ibm/kgi-slot-filling
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EMNLP 2021
Automatically inducing high quality knowledge graphs from a given collection of documents still remains a challenging problem in AI.
Slot Filling for Biomedical Information Extraction
ypapanik/biomedical-slot-filling
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BioNLP (ACL) 2022
In this work we present a slot filling approach to the task of biomedical IE, effectively replacing the need for entity and relation-specific training data, allowing us to deal with zero-shot settings.
Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?
facebookresearch/dpr-scale
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Despite their recent popularity and well-known advantages, dense retrievers still lag behind sparse methods such as BM25 in their ability to reliably match salient phrases and rare entities in the query and to generalize to out-of-domain data.
DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine
baidu/DuReader
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In this paper, we present DuReader_retrieval, a large-scale Chinese dataset for passage retrieval.
ConTextual Masked Auto-Encoder for Dense Passage Retrieval
caskcsg/ir
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Dense passage retrieval aims to retrieve the relevant passages of a query from a large corpus based on dense representations (i. e., vectors) of the query and the passages.
Query-as-context Pre-training for Dense Passage Retrieval
caskcsg/ir
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Recently, methods have been developed to improve the performance of dense passage retrieval by using context-supervised pre-training.
DAPR: A Benchmark on Document-Aware Passage Retrieval
This drives us to build a benchmark for this task including multiple datasets from heterogeneous domains.
Discriminative Information Retrieval for Question Answering Sentence Selection
We propose a framework for discriminative IR atop linguistic features, trained to improve the recall of answer candidate passage retrieval, the initial step in text-based question answering.
On the Effect of Low-Frequency Terms on Neural-IR Models
sebastian-hofstaetter/sigir19-neural-ir
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Low-frequency terms are a recurring challenge for information retrieval models, especially neural IR frameworks struggle with adequately capturing infrequently observed words.
