mlsanityData to 14 Oct 2026

Balancing the Blend: An Experimental Analysis of Trade-offs in Hybrid Search

arXiv 2508.01405 ↗First posted 2 Aug 2025cs.DBcited by 4

On the map: Retrieval-augmented generation → RAG pipeline design and evaluation

Abstract (arXiv)

Hybrid search, the integration of lexical and semantic retrieval, has become a cornerstone of modern information retrieval systems, driven by demanding applications like Retrieval-Augmented Generation (RAG). The architectural design space for these systems is vast and complex, yet a systematic understanding of the trade-offs among their core components -- retrieval paradigms, combination schemes, and re-ranking methods -- is lacking. To address this, and informed by our experience building the Infinity open-source database, we present the first experimental analysis of advanced hybrid search architectures. Our framework integrates four retrieval paradigms -- Full-Text Search (FTS), Sparse Vector Search (SVS), Dense Vector Search (DVS), and Tensor Search (TenS) -- and evaluates their combinations and re-ranking strategies across 11 real-world datasets. Our results reveal three key findings: (1) A "weakest link" phenomenon, where a weak path can substantially degrade overall accuracy, highlighting the need for path-wise quality assessment before fusion. (2) A data-driven map of performance trade-offs, demonstrating that optimal configurations depend heavily on resource constraints and data characteristics, precluding a one-size-fits-all solution. (3) The identification of Tensor-based Re-ranking Fusion (TRF) as a high-efficacy alternative to mainstream fusion methods, offering the semantic power of tensor search at a fraction of the computational and memory cost. Our findings offer concrete guidelines for designing adaptive, scalable hybrid search systems and identify key directions for future research.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in RAG pipeline design and evaluation, one of 15 directions in Retrieval-augmented generation. Builds on 49 of its 140 references that are in the map. First posted on arXiv 2 Aug 2025.

Builds on

49 of 140 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024Automatic Database Configuration Debugging using Retrieval-Augmented Language Models10 Dec
  2. 2024Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based Retrievers22 Mar
  3. 2023Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models15 Oct

Other references · 46

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  3. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
  4. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,605
  5. 2016Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphscited by 861
  6. 2020Fact or Fiction: Verifying Scientific Claimscited by 554
  7. 2024NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Modelscited by 472
  8. 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 430
  9. 2021SPLADE: Sparse Lexical and Expansion Model for First Stage Rankingcited by 286
  10. 2024mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrievalcited by 236
  11. 2020Sparse, Dense, and Attentional Representations for Text Retrievalcited by 214
  12. 2021SPLADE v2: Sparse Lexical and Expansion Model for Information Retrievalcited by 127
34 more
  1. 2013A Theoretical Analysis of NDCG Type Ranking Measurescited by 119
  2. 2021COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted Listcited by 113
  3. 2017Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graphcited by 104
  4. 2022PLAID: An Efficient Engine for Late Interaction Retrievalcited by 101
  5. 2021A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Searchcited by 82
  6. 2024SPLADE-v3: New baselines for SPLADEcited by 72
  7. 2021A Few Brief Notes on DeepImpact, COIL, and a Conceptual Framework for Information Retrieval Techniquescited by 69
  8. 2022An Analysis of Fusion Functions for Hybrid Retrievalcited by 51
  9. 2024RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Searchcited by 48
  10. 2023Survey of Vector Database Management Systemscited by 39
  11. 2025KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Modelcited by 36
  12. 2021Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performancecited by 35
  13. 2023High-Dimensional Approximate Nearest Neighbor Search: with Reliable and Efficient Distance Comparison Operationscited by 26
  14. 2024Jina-ColBERT-v2: A General-Purpose Multilingual Late Interaction Retrievercited by 25
  15. 2024Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representationscited by 24
  16. 2023Similarity search in the blink of an eye with compressed indicescited by 21
  17. 2025A Survey of Model Architectures in Information Retrievalcited by 20
  18. 2023A Unified Framework for Learned Sparse Retrievalcited by 17
  19. 2024Starling: An I/O-Efficient Disk-Resident Graph Index Framework for High-Dimensional Vector Similarity Search on Data Segmentcited by 17
  20. 2024BIRCO: A Benchmark of Information Retrieval Tasks with Complex Objectivescited by 15
  21. 2024JaColBERTv2.5: Optimising Multi-Vector Retrievers to Create State-of-the-Art Japanese Retrievers with Constrained Resourcescited by 15
  22. 2024AIR-Bench: Automated Heterogeneous Information Retrieval Benchmarkcited by 12
  23. 2025Graph-Based Vector Search: An Experimental Evaluation of the State-of-the-Artcited by 11
  24. 2022LIDER: An Efficient High-dimensional Learned Index for Large-scale Dense Passage Retrievalcited by 8
  25. 2023Bridging Dense and Sparse Maximum Inner Product Searchcited by 8
  26. 2024Generative Retrieval as Multi-Vector Dense Retrievalcited by 8
  27. 2024boldsymbolSteiner-Hardness: A Query Hardness Measure for Graph-Based ANN Indexescited by 8
  28. 2019Efficient Inner Product Approximation in Hybrid Spacescited by 6
  29. 2024Pairing Clustered Inverted Indexes with kNN Graphs for Fast Approximate Retrieval over Learned Sparse Representationscited by 5
  30. 2024An Interactive Multi-modal Query Answering System with Retrieval-Augmented Large Language Modelscited by 4
  31. 2025Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasetscited by 4
  32. 2023Optimizing Guided Traversal for Fast Learned Sparse Retrievalcited by 3
  33. 2019Techniques for Inverted Index Compressioncited by 2
  34. 2021Anytime Ranking on Document-Ordered Indexescited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026HELP: HyperNode Expansion and Logical Path-Guided Evidence Localization for Accurate and Efficient GraphRAGcited by 1
  2. 2026Self-MedRAG: a Self-Reflective Hybrid Retrieval-Augmented Generation Framework for Reliable Medical Question Answeringcited by 0
  3. 2026Medical Knowledge Simplification for Patients in the Era of LLMs: A Case Study on Diabetescited by 0
  4. 2026Efficient LLM Distillation for Bangladesh Legal Context: A Smartphone-Compatible Retrieval-Augmented Generation Modelcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026SearchGym: A Modular Infrastructure for Cross-Platform Benchmarking and Hybrid Search Orchestration
  2. 2026From BM25 to Corrective RAG: Benchmarking Retrieval Strategies for Text-and-Table Documents
  3. 2025Rethinking Hybrid Retrieval: When Small Embeddings and LLM Re-ranking Beat Bigger Models
  4. 2026HAKARI-Bench: A Lightweight Benchmark for Comparing Retrieval Architectures and Efficiency Settings under Unified Conditions
  5. 2025DAT: Dynamic Alpha Tuning for Hybrid Retrieval in Retrieval-Augmented Generation
  6. 2026Quanta: A Self-Contained Python Library for Hybrid Retrieval over Quantised Embeddings, Lexical Indexes, and Knowledge Graphs
  7. 2026Orion-RAG: Path-Aligned Hybrid Retrieval for Graphless Data
  8. 2026Scaling Retrieval Augmented Generation with RAG Fusion: Lessons from an Industry Deployment