aceLarge Language Models for Information Retrieval: A Survey
As a primary means of information acquisition, information retrieval (IR) systems, such as search engines, have integrated themselves into our daily lives. These systems also serve as components of dialogue, question-answering, and recommender systems. The trajectory of IR has evolved dynamically from its origins in term-based methods to its integration with advanced neural models. While the neural models excel at capturing complex contextual signals and semantic nuances, they still face challenges such as data…
Neural retrieval models still struggle with data scarcity, limited interpretability, and producing plausible but potentially inaccurate responses, so search systems need to blend them with traditional methods.
The source is an abstract of a survey and reports no measured outcomes; it flags that neural models still face data scarcity, interpretability, and plausible but inaccurate responses.
Evidence
- Peer-reviewedACM Transactions on Information Systems2025-09-05
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Truvace Impact Record TRV-2026-1332, v1: “Large Language Models for Information Retrieval: A Survey.” Truvace, 2026-10-14. /record/TRV-2026-1332 (accessed at citation time). sha256 a3fe23283488b5de…
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