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20142026
most citedDistilling Task-Specific Knowledge from BERT into Simple Neural Networks

335 citations · 1.7k across the 86 of their papers we have counts for

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Showing 2017Show all

8 papers · 1 filter

cs.CL2017★ 2 cited

Modeling Past and Future for Neural Machine Translation

Zaixiang Zheng, Hao Zhou, Shujian Huang +4

Existing neural machine translation systems do not explicitly model what has been translated and what has not during the decoding phase. To address this problem, we propose a novel…

cs.CL2017★ 10 cited

Why Do Neural Dialog Systems Generate Short and Meaningless Replies? A Comparison between Dialog and Translation

Bolin Wei, Shuai Lu, Lili Mou +4

This paper addresses the question: Why do neural dialog systems generate short and meaningless replies? We conjecture that, in a dialog system, an utterance may have multiple equal…

cs.CL2017★ 19 cited

Variational Attention for Sequence-to-Sequence Models

Hareesh Bahuleyan, Lili Mou, Olga Vechtomova +1

The variational encoder-decoder (VED) encodes source information as a set of random variables using a neural network, which in turn is decoded into target data using another neural…

cs.CL2017★ 4 cited

Affective Neural Response Generation

Nabiha Asghar, Pascal Poupart, Jesse Hoey +2

Existing neural conversational models process natural language primarily on a lexico-syntactic level, thereby ignoring one of the most crucial components of human-to-human dialogue…

cs.CL2017★ 13 cited

Order-Planning Neural Text Generation From Structured Data

Lei Sha, Lili Mou, Tianyu Liu +4

Generating texts from structured data (e.g., a table) is important for various natural language processing tasks such as question answering and dialog systems. In recent studies, r…

cs.CL2017★ 3 cited

Towards Neural Speaker Modeling in Multi-Party Conversation: The Task, Dataset, and Models

Zhao Meng, Lili Mou, Zhi Jin

Neural network-based dialog systems are attracting increasing attention in both academia and industry. Recently, researchers have begun to realize the importance of speaker modelin…

cs.CL2017

Hierarchical RNN with Static Sentence-Level Attention for Text-Based Speaker Change Detection

Zhao Meng, Lili Mou, Zhi Jin

Speaker change detection (SCD) is an important task in dialog modeling. Our paper addresses the problem of text-based SCD, which differs from existing audio-based studies and is us…

cs.CL2017★ 117 cited

RUBER: An Unsupervised Method for Automatic Evaluation of Open-Domain Dialog Systems

Chongyang Tao, Lili Mou, Dongyan Zhao +1

Open-domain human-computer conversation has been attracting increasing attention over the past few years. However, there does not exist a standard automatic evaluation metric for o…