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Information retrieval: recent advances and beyond
KA Hambarde, H Proenca - IEEE Access, 2023 - ieeexplore.ieee.org
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 …
Robust neural information retrieval: An adversarial and out-of-distribution perspective
YA Liu, R Zhang, J Guo, M de Rijke, Y Fan… - arxiv preprint arxiv …, 2024 - arxiv.org
Recent advances in neural information retrieval (IR) models have significantly enhanced
their effectiveness over various IR tasks. The robustness of these models, essential for …
their effectiveness over various IR tasks. The robustness of these models, essential for …
Toward best practices for training multilingual dense retrieval models
Dense retrieval models using a transformer-based bi-encoder architecture have emerged as
an active area of research. In this article, we focus on the task of monolingual retrieval in a …
an active area of research. In this article, we focus on the task of monolingual retrieval in a …
Robust information retrieval
YA Liu, R Zhang, J Guo, M de Rijke - … of the 47th International ACM SIGIR …, 2024 - dl.acm.org
Beyond effectiveness, the robustness of an information retrieval (IR) system is increasingly
attracting attention. When deployed, a critical technology such as IR should not only deliver …
attracting attention. When deployed, a critical technology such as IR should not only deliver …
Reasoning over public and private data in retrieval-based systems
Users an organizations are generating ever-increasing amounts of private data from a wide
range of sources. Incorporating private context is important to personalize open-domain …
range of sources. Incorporating private context is important to personalize open-domain …
Nir-prompt: A multi-task generalized neural information retrieval training framework
Information retrieval aims to find information that meets users' needs from the corpus.
Different needs correspond to different IR tasks such as document retrieval, open-domain …
Different needs correspond to different IR tasks such as document retrieval, open-domain …
AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification
Recent work has found that few-shot sentence classification based on pre-trained Sentence
Encoders (SEs) is efficient, robust, and effective. In this work, we investigate strategies for …
Encoders (SEs) is efficient, robust, and effective. In this work, we investigate strategies for …
Ms-shift: An analysis of ms marco distribution shifts on neural retrieval
S Lupart, T Formal, S Clinchant - European Conference on Information …, 2023 - Springer
Abstract Pre-trained Language Models have recently emerged in Information Retrieval as
providing the backbone of a new generation of neural systems that outperform traditional …
providing the backbone of a new generation of neural systems that outperform traditional …
Simple Domain Adaptation for Sparse Retrievers
M Vast, Y Zong, B Piwowarski, L Soulier - European Conference on …, 2024 - Springer
Abstract In Information Retrieval, and more generally in Natural Language Processing,
adapting models to specific domains is conducted through fine-tuning. Despite the …
adapting models to specific domains is conducted through fine-tuning. Despite the …
Generalized Weak Supervision for Neural Information Retrieval
Neural ranking models (NRMs) have demonstrated effective performance in several
information retrieval (IR) tasks. However, training NRMs often requires large-scale training …
information retrieval (IR) tasks. However, training NRMs often requires large-scale training …