VDialogUE: A Unified Evaluation Benchmark for Visually-grounded Dialogue

Yunshui Li, Binyuan Hui, Zhaochao Yin, Wanwei He, Run Luo +4 more
9/14/2023
cs.CLcs.CV

No confident code implementation found for this paper.

Abstract

Visually-grounded dialog systems, which integrate multiple modes of communication such as text and visual inputs, have become an increasingly popular area of investigation. However, the absence of a standardized evaluation framework poses a challenge in assessing the development of this field. To this end, we propose \textbf{VDialogUE}, a \textbf{V}isually-grounded \textbf{Dialog}ue benchmark for \textbf{U}nified \textbf{E}valuation. It defines five core multi-modal dialogue tasks and covers six datasets. Furthermore, in order to provide a comprehensive assessment of the model's performance across all tasks, we developed a novel evaluation metric called VDscore, which is based on the Analytic Hierarchy Process~(AHP) method. Additionally, we present a straightforward yet efficient baseline model, named \textbf{VISIT}~(\textbf{VIS}ually-grounded d\textbf{I}alog \textbf{T}ransformer), to promote the advancement of general multi-modal dialogue systems. It progressively builds its multi-modal foundation and dialogue capability via a two-stage pre-training strategy. We believe that the VDialogUE benchmark, along with the evaluation scripts and our baseline models, will accelerate the development of visually-grounded dialog systems and lead to the development of more sophisticated and effective pre-trained models.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{li2023vdialogue,
  title  = {VDialogUE: A Unified Evaluation Benchmark for Visually-grounded Dialogue},
  author = {Yunshui Li and Binyuan Hui and Zhaochao Yin and Wanwei He and Run Luo and Yuxing Long and Min Yang and Fei Huang and Yongbin Li},
  year   = {2023},
  eprint = {2309.07387},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.07387v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2309.07387.svg)](https://codeofpaper.com/paper/2309.07387)

Discussion