activity
20182026
most citedA Unified Pre-training Framework for Conversational AI

5 citations · 13 across the 11 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.CL2021★ 3 cited

TOD-DA: Towards Boosting the Robustness of Task-oriented Dialogue Modeling on Spoken Conversations

Xin Tian, Xinxian Huang, Dongfeng He +11

Task-oriented dialogue systems have been plagued by the difficulties of obtaining large-scale and high-quality annotated conversations. Furthermore, most of the publicly available…

cs.CL2021

Amendable Generation for Dialogue State Tracking

Xin Tian, Liankai Huang, Yingzhan Lin +6

In task-oriented dialogue systems, recent dialogue state tracking methods tend to perform one-pass generation of the dialogue state based on the previous dialogue state. The mistak…

cs.CL2021

PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation

Siqi Bao, Huang He, Fan Wang +11

To explore the limit of dialogue generation pre-training, we present the models of PLATO-XL with up to 11 billion parameters, trained on both Chinese and English social media conve…

cs.CL2021★ 5 cited

A Unified Pre-training Framework for Conversational AI

Siqi Bao, Bingjin Chen, Huang He +7

In this work, we explore the application of PLATO-2 on various dialogue systems, including open-domain conversation, knowledge grounded dialogue, and task-oriented conversation. PL…

cs.CL2021

Learning to Select External Knowledge with Multi-Scale Negative Sampling

Huang He, Hua Lu, Siqi Bao +4

The Track-1 of DSTC9 aims to effectively answer user requests or questions during task-oriented dialogues, which are out of the scope of APIs/DB. By leveraging external knowledge r…