1 code implementation • ACL 2021 • Zheng Ye, Liucun Lu, Lishan Huang, Liang Lin, Xiaodan Liang
To address these limitations, we propose Quantifiable Dialogue Coherence Evaluation (QuantiDCE), a novel framework aiming to train a quantifiable dialogue coherence metric that can reflect the actual human rating standards.
1 code implementation • EMNLP 2020 • Lishan Huang, Zheng Ye, Jinghui Qin, Liang Lin, Xiaodan Liang
Capitalized on the topic-level dialogue graph, we propose a new evaluation metric GRADE, which stands for Graph-enhanced Representations for Automatic Dialogue Evaluation.