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[2502.07971] Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency
Summary
The paper presents Retreever, a tree-based hierarchical retrieval method that enhances efficiency and transparency in information retrieval systems, outperforming traditional flat methods.
Why It Matters
As information retrieval is crucial for intelligent systems, improving its efficiency and transparency can significantly enhance performance across various applications. Retreever's innovative approach addresses the limitations of existing methods, making it a valuable contribution to the field.
Key Takeaways
- Retreever optimizes hierarchical retrieval for better performance and transparency.
- The method balances cost and utility by indexing data at multiple tree levels.
- Retreever achieves high retrieval accuracy with low latency compared to traditional methods.
- Hierarchical retrieval can be practical for large-scale applications.
- The paper contributes to the ongoing discourse on efficient information retrieval techniques.
Computer Science > Information Retrieval arXiv:2502.07971 (cs) [Submitted on 11 Feb 2025 (v1), last revised 13 Feb 2026 (this version, v2)] Title:Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency Authors:Shubham Gupta, Zichao Li, Tianyi Chen, Cem Subakan, Siva Reddy, Perouz Taslakian, Valentina Zantedeschi View a PDF of the paper titled Hierarchical Retrieval at Scale: Bridging Transparency and Efficiency, by Shubham Gupta and Zichao Li and Tianyi Chen and Cem Subakan and Siva Reddy and Perouz Taslakian and Valentina Zantedeschi View PDF Abstract:Information retrieval is a core component of many intelligent systems as it enables conditioning of outputs on new and large-scale datasets. While effective, the standard practice of encoding data into high-dimensional representations for similarity search entails large memory and compute footprints, and also makes it hard to inspect the inner workings of the system. Hierarchical retrieval methods offer an interpretable alternative by organizing data at multiple granular levels, yet do not match the efficiency and performance of flat retrieval approaches. In this paper, we propose Retreever, a tree-based method that makes hierarchical retrieval viable at scale by directly optimizing its structure for retrieval performance while naturally providing transparency through meaningful semantic groupings. Our method offers the flexibility to balance cost and utility by indexing data using representations from any tree...