activity
20192021
most citedSelection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets

3 citations · 12 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CL2021

A Neural Conversation Generation Model via Equivalent Shared Memory Investigation

Changzhen Ji, Yating Zhang, Xiaozhong Liu +4

Conversation generation as a challenging task in Natural Language Generation (NLG) has been increasingly attracting attention over the last years. A number of recent works adopted…

cs.CL2020

AI-lead Court Debate Case Investigation

Changzhen Ji, Xin Zhou, Conghui Zhu +1

The multi-role judicial debate composed of the plaintiff, defendant, and judge is an important part of the judicial trial. Different from other types of dialogue, questions are rai…

cs.CL2020

Cross Copy Network for Dialogue Generation

Changzhen Ji, Xin Zhou, Yating Zhang +4

In the past few years, audiences from different fields witness the achievements of sequence-to-sequence models (e.g., LSTM+attention, Pointer Generator Networks, and Transformer) t…

cs.CL2020

Reliable Evaluations for Natural Language Inference based on a Unified Cross-dataset Benchmark

Guanhua Zhang, Bing Bai, Jian Liang +3

Recent studies show that crowd-sourced Natural Language Inference (NLI) datasets may suffer from significant biases like annotation artifacts. Models utilizing these superficial cl…

cs.CL20202 cited

Understanding Learning Dynamics for Neural Machine Translation

Conghui Zhu, Guanlin Li, Lemao Liu +2

Despite the great success of NMT, there still remains a severe challenge: it is hard to interpret the internal dynamics during its training process. In this paper we propose to und…

cs.CL20201 cited

Detecting and Understanding Generalization Barriers for Neural Machine Translation

Guanlin Li, Lemao Liu, Conghui Zhu +2

Generalization to unseen instances is our eternal pursuit for all data-driven models. However, for realistic task like machine translation, the traditional approach measuring gener…