activity
20182026
most citedThe JDDC Corpus: A Large-Scale Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service

40 citations · 59 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

POSPAN: Position-Constrained Span Masking for Language Model Pre-training

Zhenyu Zhang, Lei Shen, Yuming Zhao +2

Span-level masked language modeling (MLM) has shown to be advantageous to pre-trained language models over the original single-token MLM, as entities/phrases and their dependencies…

cs.CL2023★ 1 cited

DiffusEmp: A Diffusion Model-Based Framework with Multi-Grained Control for Empathetic Response Generation

Guanqun Bi, Lei Shen, Yanan Cao +4

Empathy is a crucial factor in open-domain conversations, which naturally shows one's caring and understanding to others. Though several methods have been proposed to generate empa…

cs.CL2020★ 12 cited

CDL: Curriculum Dual Learning for Emotion-Controllable Response Generation

Lei Shen, Yang Feng

Emotion-controllable response generation is an attractive and valuable task that aims to make open-domain conversations more empathetic and engaging. Existing methods mainly enhanc…

cs.CL2020★ 3 cited

Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation

Lei Shen, Xiaoyu Guo, Meng Chen

Chinese poetry is an important part of worldwide culture, and classical and modern sub-branches are quite different. The former is a unique genre and has strict constraints, while…

cs.CL2019★ 40 cited

The JDDC Corpus: A Large-Scale Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service

Meng Chen, Ruixue Liu, Lei Shen +5

Human conversations are complicated and building a human-like dialogue agent is an extremely challenging task. With the rapid development of deep learning techniques, data-driven m…

cs.CL2019★ 3 cited

Modeling Semantic Relationship in Multi-turn Conversations with Hierarchical Latent Variables

Lei Shen, Yang Feng, Haolan Zhan

Multi-turn conversations consist of complex semantic structures, and it is still a challenge to generate coherent and diverse responses given previous utterances. It's practical th…

cs.CL2018

Speeding Up Neural Machine Translation Decoding by Cube Pruning

Wen Zhang, Liang Huang, Yang Feng +2

Although neural machine translation has achieved promising results, it suffers from slow translation speed. The direct consequence is that a trade-off has to be made between transl…