activity
20162023
most citedA Parallel-Hierarchical Model for Machine Comprehension on Sparse Data

26 citations · 35 across the 5 of their papers we have counts for

collaborators

6 papers

cs.IR2023★ 2 cited

Towards Imperceptible Document Manipulations against Neural Ranking Models

Xuanang Chen, Ben He, Zheng Ye +2

Adversarial attacks have gained traction in order to identify potential vulnerabilities in neural ranking models (NRMs), but current attack methods often introduce grammatical erro…

cs.CL2021

Towards Quantifiable Dialogue Coherence Evaluation

Zheng Ye, Liucun Lu, Lishan Huang +2

Automatic dialogue coherence evaluation has attracted increasing attention and is crucial for developing promising dialogue systems. However, existing metrics have two major limita…

cs.CL2020★ 6 cited

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

Lishan Huang, Zheng Ye, Jinghui Qin +2

Automatically evaluating dialogue coherence is a challenging but high-demand ability for developing high-quality open-domain dialogue systems. However, current evaluation metrics c…

cs.CL2020★ 1 cited

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

Jinghui Qin, Zheng Ye, Jianheng Tang +1

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 conversatio…

cs.CL2016

Natural Language Comprehension with the EpiReader

Adam Trischler, Zheng Ye, Xingdi Yuan +1

We present the EpiReader, a novel model for machine comprehension of text. Machine comprehension of unstructured, real-world text is a major research goal for natural language proc…

cs.CL2016★ 26 cited

A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data

Adam Trischler, Zheng Ye, Xingdi Yuan +3

Understanding unstructured text is a major goal within natural language processing. Comprehension tests pose questions based on short text passages to evaluate such understanding.…