Lune

ACL2020Top-tier venue

USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation

Shikib Mehri, Maxine Eskénazi

2020Year
10Citations
58Top-tier citations

Abstract

The lack of meaningful automatic evaluation metrics for dialog has impeded open-domain dialog research. Standard language generation metrics have been shown to be ineffective for evaluating dialog models. To this end, this paper presents USR, an UnSupervised and Reference-free evaluation metric for dialog. USR is a reference-free metric that trains unsupervised models to measure several desirable qualities of dialog. USR is shown to strongly correlate with human judgment on both Topical-Chat (turn-level: 0.42, systemlevel: 1.0) and PersonaChat (turn-level: 0.48 and system-level: 1.0). USR additionally produces interpretable measures for several desirable properties of dialog.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 8ee848df-308a-49f2-953e-e6ee960c26f5

Cited by top-tier papers58

Ask how each one uses it

Builds on2

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines