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Large Language Models for Information Retrieval: A Survey

ACM Transactions on Information Systems, 2023
As a primary means of information acquisition, information retrieval (IR) systems, such as search engines, have integrated themselves into our daily lives.
Yutao Zhu   +7 more
semanticscholar   +1 more source

InPars: Unsupervised Dataset Generation for Information Retrieval

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022
The Information Retrieval (IR) community has recently witnessed a revolution due to large pretrained transformer models. Another key ingredient for this revolution was the MS MARCO dataset, whose scale and diversity has enabled zero-shot transfer ...
L. Bonifacio   +3 more
semanticscholar   +1 more source

Reduce, Reuse, Recycle: Green Information Retrieval Research

Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022
Recent advances in Information Retrieval utilise energy-intensive hardware to produce state-of-the-art results. In areas of research highly related to Information Retrieval, such as Natural Language Processing and Machine Learning, there have been ...
Harrisen Scells   +2 more
semanticscholar   +1 more source

Retrieval-Augmented Generation for Large Language Models: A Survey

arXiv.org, 2023
Large Language Models (LLMs) showcase impressive capabilities but encounter challenges like hallucination, outdated knowledge, and non-transparent, untraceable reasoning processes.
Yunfan Gao   +10 more
semanticscholar   +1 more source

Cognitive Biases in Search: A Review and Reflection of Cognitive Biases in Information Retrieval

Conference on Human Information Interaction and Retrieval, 2021
People are susceptible to an array of cognitive biases, which can result in systematic errors and deviations from rational decision making. Over the past decade, an increasing amount of attention has been paid towards investigating how cognitive biases ...
L. Azzopardi
semanticscholar   +1 more source

Generating Clarifying Questions for Information Retrieval

The Web Conference, 2020
Search queries are often short, and the underlying user intent may be ambiguous. This makes it challenging for search engines to predict possible intents, only one of which may pertain to the current user.
Hamed Zamani   +4 more
semanticscholar   +1 more source

Knowledge Graphs: An Information Retrieval Perspective

Foundations and Trends in Information Retrieval, 2020
In this survey, we provide an overview of the literature on knowledge graphs (KGs) in the context of information retrieval (IR). Modern IR systems can benefit from information available in KGs in multiple ways, independent of whether the KGs are publicly ...
R. Reinanda, E. Meij, M. de Rijke
semanticscholar   +1 more source

A machine for information retrieval

Proceedings of the fourth workshop on Computer architecture for non-numeric processing - CAW '78, 1978
The described machine was conceived especially for nonnumeric computation. The possible applications are:- content and structures recognition in texts- language translation- modification of files format- etc...The first application of the machine will be “A library file query system”. The library file is available on a 300 Mbyte disk.
A. El Masri, D. Tusera, J. Rohmer
openaire   +2 more sources

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