Semantic models for the first-stage retrieval: A comprehensive review
Multi-stage ranking pipelines have been a practical solution in modern search systems,
where the first-stage retrieval is to return a subset of candidate documents and latter stages …
where the first-stage retrieval is to return a subset of candidate documents and latter stages …
Approximate nearest neighbor negative contrastive learning for dense text retrieval
Conducting text retrieval in a dense learned representation space has many intriguing
advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires …
advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires …
Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
Existing neural information retrieval (IR) models have often been studied in homogeneous
and narrow settings, which has considerably limited insights into their out-of-distribution …
and narrow settings, which has considerably limited insights into their out-of-distribution …
Information retrieval: recent advances and beyond
This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …
utilized in the first and second stages of the typical information retrieval processing chain …
Colbert: Efficient and effective passage search via contextualized late interaction over bert
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 …
in Information Retrieval (IR), largely owed to fine-tuning deep language models (LMs) for …
RocketQA: An optimized training approach to dense passage retrieval for open-domain question answering
In open-domain question answering, dense passage retrieval has become a new paradigm
to retrieve relevant passages for finding answers. Typically, the dual-encoder architecture is …
to retrieve relevant passages for finding answers. Typically, the dual-encoder architecture is …
Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and
dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage …
dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage …
[BOOK][B] Pretrained transformers for text ranking: Bert and beyond
The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …
response to a query. Although the most common formulation of text ranking is search …
Overview of the TREC 2019 deep learning track
The Deep Learning Track is a new track for TREC 2019, with the goal of studying ad hoc
ranking in a large data regime. It is the first track with large human-labeled training sets …
ranking in a large data regime. It is the first track with large human-labeled training sets …
Rocketqav2: A joint training method for dense passage retrieval and passage re-ranking
In various natural language processing tasks, passage retrieval and passage re-ranking are
two key procedures in finding and ranking relevant information. Since both the two …
two key procedures in finding and ranking relevant information. Since both the two …