activity
20172024
most citedLearning to Select Knowledge for Response Generation in Dialog Systems

23 citations · 37 across the 7 of their papers we have counts for

collaborators
Showing 2019Show all

5 papers · 1 filter

cs.CL2019★ 10 cited

DAL: Dual Adversarial Learning for Dialogue Generation

Shaobo Cui, Rongzhong Lian, Di Jiang +3

In open-domain dialogue systems, generative approaches have attracted much attention for response generation. However, existing methods are heavily plagued by generating safe respo…

cs.CL2019★ 1 cited

Know More about Each Other: Evolving Dialogue Strategy via Compound Assessment

Siqi Bao, Huang He, Fan Wang +2

In this paper, a novel Generation-Evaluation framework is developed for multi-turn conversations with the objective of letting both participants know more about each other. For the…

cs.CL2019

Proactive Human-Machine Conversation with Explicit Conversation Goals

Wenquan Wu, Zhen Guo, Xiangyang Zhou +4

Though great progress has been made for human-machine conversation, current dialogue system is still in its infancy: it usually converses passively and utters words more as a matte…

cs.LG2019

Artificial Intelligence for Prosthetics - challenge solutions

Łukasz Kidziński, Carmichael Ong, Sharada Prasanna Mohanty +47

In the NeurIPS 2018 Artificial Intelligence for Prosthetics challenge, participants were tasked with building a controller for a musculoskeletal model with a goal of matching a giv…

cs.CL2019★ 23 cited

Learning to Select Knowledge for Response Generation in Dialog Systems

Rongzhong Lian, Min Xie, Fan Wang +2

End-to-end neural models for intelligent dialogue systems suffer from the problem of generating uninformative responses. Various methods were proposed to generate more informative…