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 …
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 …
Colbertv2: Effective and efficient retrieval via lightweight late interaction
Neural information retrieval (IR) has greatly advanced search and other knowledge-
intensive language tasks. While many neural IR methods encode queries and documents …
intensive language tasks. While many neural IR methods encode queries and documents …
Promptagator: Few-shot dense retrieval from 8 examples
Much recent research on information retrieval has focused on how to transfer from one task
(typically with abundant supervised data) to various other tasks where supervision is limited …
(typically with abundant supervised data) to various other tasks where supervision is limited …
Dense text retrieval based on pretrained language models: A survey
Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …
required to return relevant information resources to user's queries in natural language. From …
Autoregressive search engines: Generating substrings as document identifiers
Abstract Knowledge-intensive language tasks require NLP systems to both provide the
correct answer and retrieve supporting evidence for it in a given corpus. Autoregressive …
correct answer and retrieve supporting evidence for it in a given corpus. Autoregressive …
Unsupervised corpus aware language model pre-training for dense passage retrieval
L Gao, J Callan - arxiv preprint arxiv:2108.05540, 2021 - arxiv.org
Recent research demonstrates the effectiveness of using fine-tuned language models~(LM)
for dense retrieval. However, dense retrievers are hard to train, typically requiring heavily …
for dense retrieval. However, dense retrievers are hard to train, typically requiring heavily …
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 …
[BUCH][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 …
From distillation to hard negative sampling: Making sparse neural ir models more effective
Neural retrievers based on dense representations combined with Approximate Nearest
Neighbors search have recently received a lot of attention, owing their success to distillation …
Neighbors search have recently received a lot of attention, owing their success to distillation …