17 citations · 72 across the 10 of their papers we have counts for
12 papers
CLIP Models are Few-shot Learners: Empirical Studies on VQA and Visual Entailment
Haoyu Song, Li Dong, Wei-Nan Zhang +2
CLIP has shown a remarkable zero-shot capability on a wide range of vision tasks. Previously, CLIP is only regarded as a powerful visual encoder. However, after being pre-trained b…
BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data
Haoyu Song, Yan Wang, Kaiyan Zhang +2
Maintaining consistent personas is essential for dialogue agents. Although tremendous advancements have been brought, the limited-scale of annotated persona-dense data are still ba…
A Compare Aggregate Transformer for Understanding Document-grounded Dialogue
Longxuan Ma, Weinan Zhang, Runxin Sun +1
Unstructured documents serving as external knowledge of the dialogues help to generate more informative responses. Previous research focused on knowledge selection (KS) in the docu…
Generate, Delete and Rewrite: A Three-Stage Framework for Improving Persona Consistency of Dialogue Generation
Haoyu Song, Yan Wang, Wei-Nan Zhang +2
Maintaining a consistent personality in conversations is quite natural for human beings, but is still a non-trivial task for machines. The persona-based dialogue generation task is…
A Survey of Document Grounded Dialogue Systems (DGDS)
Longxuan Ma, Wei-Nan Zhang, Mingda Li +1
Dialogue system (DS) attracts great attention from industry and academia because of its wide application prospects. Researchers usually divide the DS according to the function. How…
Counterfactual Off-Policy Training for Neural Response Generation
Qingfu Zhu, Weinan Zhang, Ting Liu +1
Open-domain dialogue generation suffers from the data insufficiency problem due to the vast size of potential responses. In this paper, we propose to explore potential responses by…