Papers with hybrid search
Automotive Document Labeling Using Large Language Models (2025.emnlp-industry)
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| Challenge: | Traditionally, mechanics manually browse lengthy documents to locate component information, a process that is time-consuming and error-prone. |
| Approach: | They propose to use large language models to enrich and unify a component database and use hybrid search to select the most relevant component for a document. |
| Outcome: | The proposed method outperforms baselines based on an expert-annotated dataset and significantly reduces the search space and improves retrieval efficiency. |
Simple and Effective Unsupervised Redundancy Elimination to Compress Dense Vectors for Passage Retrieval (2021.emnlp-main)
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| Challenge: | Dense passage retrieval improves ranking accuracy in open-domain question answering but at the cost of large space and memory requirements. |
| Approach: | They propose a simple unsupervised pipeline that includes principal component analysis (PCA), product quantization, and hybrid search to improve space efficiency. |
| Outcome: | The proposed pipeline achieves good accuracy–space trade-offs, for example, 48 compression with less than 3% drop in top-100 retrieval accuracy on average or 96 compression without drop in space requirements. |
Know When to Fuse: Investigating Non-English Hybrid Retrieval in the Legal Domain (2025.coling-main)
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| Challenge: | Existing research focuses on a limited set of retrieval methods, evaluated in pairs on domain-general datasets exclusively in English. |
| Approach: | They evaluate the efficacy of hybrid search across a variety of retrieval models in the french language . they find that fusion of different domain-general models consistently enhances performance . |
| Outcome: | The proposed model improves in-domain performance compared to a single model in a zero-shot context . the proposed model also improves when the models are trained in- domain . |