OpenVNA: A Framework for Analyzing the Behavior of Multimodal Language Understanding System under Noisy Scenarios

TL;DR

OpenVNA is an open-source framework that enables comprehensive analysis of multimodal language understanding systems' robustness under noisy conditions, supporting both global and local behavior evaluation.

Contribution

It introduces a flexible, extensible toolkit with a benchmark library and GUI for analyzing system robustness and behavior in noisy scenarios.

Findings

Provides a customizable noise evaluation platform

Enables batch and instance-level robustness analysis

Accessible via open-source repository and web interface

Abstract

We present OpenVNA, an open-source framework designed for analyzing the behavior of multimodal language understanding systems under noisy conditions. OpenVNA serves as an intuitive toolkit tailored for researchers, facilitating convenience batch-level robustness evaluation and on-the-fly instance-level demonstration. It primarily features a benchmark Python library for assessing global model robustness, offering high flexibility and extensibility, thereby enabling customization with user-defined noise types and models. Additionally, a GUI-based interface has been developed to intuitively analyze local model behavior. In this paper, we delineate the design principles and utilization of the created library and GUI-based web platform. Currently, OpenVNA is publicly accessible at \url{https://github.com/thuiar/OpenVNA}, with a demonstration video available at \url{https://youtu.be/0Z9cW7RGct4}.