Trove: A Flexible Toolkit for Dense Retrieval
Authors: name: Reza Esfandiarpoor, name: Max Zuo, name: Stephen H. Bach
Organization: Bats Research

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.