Search Results for author: Zheng Ye

Found 7 papers, 4 papers with code

Towards Quantifiable Dialogue Coherence Evaluation

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.

Coherence Evaluation Dialogue Evaluation +1

Co-BERT: A Context-Aware BERT Retrieval Model Incorporating Local and Query-specific Context

no code implementations17 Apr 2021 Xiaoyang Chen, Kai Hui, Ben He, Xianpei Han, Le Sun, Zheng Ye

BERT-based text ranking models have dramatically advanced the state-of-the-art in ad-hoc retrieval, wherein most models tend to consider individual query-document pairs independently.

Learning-To-Rank Re-Ranking

GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems

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.

Dialogue Evaluation

Dynamic Knowledge Routing Network For Target-Guided Open-Domain Conversation

1 code implementation4 Feb 2020 Jinghui Qin, Zheng Ye, Jianheng Tang, Xiaodan Liang

Target-guided open-domain conversation aims to proactively and naturally guide a dialogue agent or human to achieve specific goals, topics or keywords during open-ended conversations.

A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data

1 code implementation ACL 2016 Adam Trischler, Zheng Ye, Xingdi Yuan, Jing He, Phillip Bachman, Kaheer Suleman

The parallel hierarchy enables our model to compare the passage, question, and answer from a variety of trainable perspectives, as opposed to using a manually designed, rigid feature set.

Question Answering Reading Comprehension

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