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Trove: A Flexible Toolkit for Dense Retrieval

arXiv 2511.01857 ↗First posted 3 Nov 2025cs.IR cs.AIcited by 0

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Abstract (arXiv)

We introduce Trove, an easy-to-use open-source retrieval toolkit that simplifies research experiments without sacrificing flexibility or speed. For the first time, we introduce efficient data management features that load and process (filter, select, transform, and combine) retrieval datasets on the fly, with just a few lines of code. This gives users the flexibility to easily experiment with different dataset configurations without the need to compute and store multiple copies of large datasets. Trove is highly customizable: in addition to many built-in options, it allows users to freely modify existing components or replace them entirely with user-defined objects. It also provides a low-code and unified pipeline for evaluation and hard negative mining, which supports multi-node execution without any code changes. Trove's data management features reduce memory consumption by a factor of 2.6. Moreover, Trove's easy-to-use inference pipeline incurs no overhead, and inference times decrease linearly with the number of available nodes. Most importantly, we demonstrate how Trove simplifies retrieval experiments and allows for arbitrary customizations, thus facilitating exploratory research.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 30 references that are in the map. First posted on arXiv 3 Nov 2025.

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References · 19

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  3. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,591
  4. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,225
  5. 2020Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrievalcited by 846
  6. 2020RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answeringcited by 410
  7. 2023Fine-Tuning LLaMA for Multi-Stage Text Retrievalcited by 271
  8. 2022Promptagator: Few-shot Dense Retrieval From 8 Examplescited by 233
  9. 2024NV-Retriever: Improving text embedding models with effective hard-negative miningcited by 83
  10. 2023InPars-v2: Large Language Models as Efficient Dataset Generators for Information Retrievalcited by 73
  11. 2022Tevatron: An Efficient and Flexible Toolkit for Dense Retrievalcited by 47
  12. 2024Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Modelscited by 39
7 more
  1. 2020Declarative Experimentation in Information Retrieval using PyTerriercited by 29
  2. 2021TripClick: The Log Files of a Large Health Web Search Enginecited by 18
  3. 2024SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrievalcited by 14
  4. 2025Can Generative LLMs Create Query Variants for Test Collections? An Exploratory Studycited by 10
  5. 2023Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest Neighborscited by 5
  6. 2021CODER: An efficient framework for improving retrieval through COntextual Document Embedding Rerankingcited by 4
  7. 2025Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevancecited by 4

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