WARP: An Efficient Engine for Multi-Vector Retrieval
Fuente:
arXiv
Saved in:
| Main Authors: | Scheerer, Jan Luca, Zaharia, Matei, Potts, Christopher, Alonso, Gustavo, Khattab, Omar |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
by: Saad-Falcon, Jon, et al.
Published: (2023)
by: Saad-Falcon, Jon, et al.
Published: (2023)
ColBERT-serve: Efficient Multi-Stage Memory-Mapped Scoring
by: Huang, Kaili, et al.
Published: (2025)
by: Huang, Kaili, et al.
Published: (2025)
Drowning in Documents: Consequences of Scaling Reranker Inference
by: Jacob, Mathew, et al.
Published: (2024)
by: Jacob, Mathew, et al.
Published: (2024)
ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data
by: Patel, Liana, et al.
Published: (2024)
by: Patel, Liana, et al.
Published: (2024)
LIR: The First Workshop on Late Interaction and Multi Vector Retrieval @ ECIR 2026
by: Clavié, Benjamin, et al.
Published: (2025)
by: Clavié, Benjamin, et al.
Published: (2025)
OBLIQ-Bench: Exposing Overlooked Bottlenecks in Modern Retrievers with Latent and Implicit Queries
by: Tchuindjo, Diane, et al.
Published: (2026)
by: Tchuindjo, Diane, et al.
Published: (2026)
Efficient Multi-Vector Dense Retrieval Using Bit Vectors
by: Nardini, Franco Maria, et al.
Published: (2024)
by: Nardini, Franco Maria, et al.
Published: (2024)
DS SERVE: A Framework for Efficient and Scalable Neural Retrieval
by: Liu, Jinjian, et al.
Published: (2025)
by: Liu, Jinjian, et al.
Published: (2025)
Can QPP Choose the Right Query Variant? Evaluating Query Variant Selection for RAG Pipelines
by: Arabzadeh, Negar, et al.
Published: (2026)
by: Arabzadeh, Negar, et al.
Published: (2026)
Image and Data Mining in Reticular Chemistry Using GPT-4V
by: Zheng, Zhiling, et al.
Published: (2023)
by: Zheng, Zhiling, et al.
Published: (2023)
Backtracing: Retrieving the Cause of the Query
by: Wang, Rose E., et al.
Published: (2024)
by: Wang, Rose E., et al.
Published: (2024)
Efficient Constant-Space Multi-Vector Retrieval
by: MacAvaney, Sean, et al.
Published: (2025)
by: MacAvaney, Sean, et al.
Published: (2025)
RAG over Thinking Traces Can Improve Reasoning Tasks
by: Arabzadeh, Negar, et al.
Published: (2026)
by: Arabzadeh, Negar, et al.
Published: (2026)
LangProBe: a Language Programs Benchmark
by: Tan, Shangyin, et al.
Published: (2025)
by: Tan, Shangyin, et al.
Published: (2025)
Incorporating Token Importance in Multi-Vector Retrieval
by: S, Archish, et al.
Published: (2025)
by: S, Archish, et al.
Published: (2025)
Why Large Language Models can Secretly Outperform Embedding Similarity in Information Retrieval
by: Benescu, Matei, et al.
Published: (2026)
by: Benescu, Matei, et al.
Published: (2026)
Generative Retrieval as Multi-Vector Dense Retrieval
by: Wu, Shiguang, et al.
Published: (2024)
by: Wu, Shiguang, et al.
Published: (2024)
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
by: Lee, Jinhyuk, et al.
Published: (2023)
by: Lee, Jinhyuk, et al.
Published: (2023)
LEMUR: Learned Multi-Vector Retrieval
by: Jääsaari, Elias, et al.
Published: (2026)
by: Jääsaari, Elias, et al.
Published: (2026)
Document Optimization for Black-Box Retrieval via Reinforcement Learning
by: Uzan, Omri, et al.
Published: (2026)
by: Uzan, Omri, et al.
Published: (2026)
FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents
by: Thakur, Nandan, et al.
Published: (2025)
by: Thakur, Nandan, et al.
Published: (2025)
SpatCode: Rotary-based Unified Encoding Framework for Efficient Spatiotemporal Vector Retrieval
by: Hu, Bingde, et al.
Published: (2026)
by: Hu, Bingde, et al.
Published: (2026)
CRISP: Clustering Multi-Vector Representations for Denoising and Pruning
by: Veneroso, João, et al.
Published: (2025)
by: Veneroso, João, et al.
Published: (2025)
DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning
by: Jiang, Pengcheng, et al.
Published: (2025)
by: Jiang, Pengcheng, et al.
Published: (2025)
FUTURAL: A Metasearch Platform for Empowering Rural Areas with Smart Solutions
by: Popovici, Matei, et al.
Published: (2026)
by: Popovici, Matei, et al.
Published: (2026)
AIANO: Enhancing Information Retrieval with AI-Augmented Annotation
by: Khattab, Sameh, et al.
Published: (2026)
by: Khattab, Sameh, et al.
Published: (2026)
Efficient and Effective Retrieval of Dense-Sparse Hybrid Vectors using Graph-based Approximate Nearest Neighbor Search
by: Zhang, Haoyu, et al.
Published: (2024)
by: Zhang, Haoyu, et al.
Published: (2024)
TakeLab Retriever: AI-Driven Search Engine for Articles from Croatian News Outlets
by: Dukić, David, et al.
Published: (2024)
by: Dukić, David, et al.
Published: (2024)
Aligned Query Expansion: Efficient Query Expansion for Information Retrieval through LLM Alignment
by: Yang, Adam, et al.
Published: (2025)
by: Yang, Adam, et al.
Published: (2025)
No More K-means: Single-Stage Sparse Coding for Efficient Multi-Vector Retrieval
by: Guo, Lixuan, et al.
Published: (2026)
by: Guo, Lixuan, et al.
Published: (2026)
Prompts as Auto-Optimized Training Hyperparameters: Training Best-in-Class IR Models from Scratch with 10 Gold Labels
by: Xian, Jasper, et al.
Published: (2024)
by: Xian, Jasper, et al.
Published: (2024)
Foundations of Vector Retrieval
by: Bruch, Sebastian
Published: (2024)
by: Bruch, Sebastian
Published: (2024)
KBest: Efficient Vector Search on Kunpeng CPU
by: Ma, Kaihao, et al.
Published: (2025)
by: Ma, Kaihao, et al.
Published: (2025)
AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings
by: Reddy, Revanth Gangi, et al.
Published: (2024)
by: Reddy, Revanth Gangi, et al.
Published: (2024)
Real-time Indexing for Large-scale Recommendation by Streaming Vector Quantization Retriever
by: Bin, Xingyan, et al.
Published: (2025)
by: Bin, Xingyan, et al.
Published: (2025)
Query, Decompose, Compress: Structured Query Expansion for Efficient Multi-Hop Retrieval
by: Yun, JungMin, et al.
Published: (2026)
by: Yun, JungMin, et al.
Published: (2026)
Simple but Efficient: A Multi-Scenario Nearline Retrieval Framework for Recommendation on Taobao
by: Ma, Yingcai, et al.
Published: (2024)
by: Ma, Yingcai, et al.
Published: (2024)
Large Language Models vs. Search Engines: Evaluating User Preferences Across Varied Information Retrieval Scenarios
by: Caramancion, Kevin Matthe
Published: (2024)
by: Caramancion, Kevin Matthe
Published: (2024)
DocPruner: A Storage-Efficient Framework for Multi-Vector Visual Document Retrieval via Adaptive Patch-Level Embedding Pruning
by: Yan, Yibo, et al.
Published: (2025)
by: Yan, Yibo, et al.
Published: (2025)
Hybrid-Vector Retrieval for Visually Rich Documents: Combining Single-Vector Efficiency and Multi-Vector Accuracy
by: Kim, Juyeon, et al.
Published: (2025)
by: Kim, Juyeon, et al.
Published: (2025)
Similar Items
-
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
by: Saad-Falcon, Jon, et al.
Published: (2023) -
ColBERT-serve: Efficient Multi-Stage Memory-Mapped Scoring
by: Huang, Kaili, et al.
Published: (2025) -
Drowning in Documents: Consequences of Scaling Reranker Inference
by: Jacob, Mathew, et al.
Published: (2024) -
ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data
by: Patel, Liana, et al.
Published: (2024) -
LIR: The First Workshop on Late Interaction and Multi Vector Retrieval @ ECIR 2026
by: Clavié, Benjamin, et al.
Published: (2025)