  OpenMatch is a Python-based library that serves for Neural Information
Retrieval (Neu-IR) research. It provides self-contained neural and traditional
IR modules, making it easy to build customized and higher-capacity IR systems.
In order to develop the advantages of Neu-IR models for users, OpenMatch
provides implementations of recent neural IR models, complicated experiment
instructions, and advanced few-shot training methods. OpenMatch reproduces
corresponding ranking results of previous work on widely-used IR benchmarks,
liberating users from surplus labor in baseline reimplementation. Our
OpenMatch-based solutions conduct top-ranked empirical results on various
ranking tasks, such as ad hoc retrieval and conversational retrieval,
illustrating the convenience of OpenMatch to facilitate building an effective
IR system. The library, experimental methodologies and results of OpenMatch are
all publicly available at https://github.com/thunlp/OpenMatch.
