6 citations · 16 across the 15 of their papers we have counts for
15 papers
Dynamic Stochastic Decoding Strategy for Open-Domain Dialogue Generation
Yiwei Li, Fei Mi, Yitong Li +4
Stochastic sampling strategies such as top-k and top-p have been widely used in dialogue generation task. However, as an open-domain chatting system, there will be two different co…
EXMODD: An EXplanatory Multimodal Open-Domain Dialogue dataset
Hang Yin, Pinren Lu, Ziang Li +2
The need for high-quality data has been a key issue hindering the research of dialogue tasks. Recent studies try to build datasets through manual, web crawling, and large pre-train…
Advances and Challenges of Multi-task Learning Method in Recommender System: A Survey
Mingzhu Zhang, Ruiping Yin, Zhen Yang +2
Multi-task learning has been widely applied in computational vision, natural language processing and other fields, which has achieved well performance. In recent years, a lot of wo…
Heterogeneous-Branch Collaborative Learning for Dialogue Generation
Yiwei Li, Shaoxiong Feng, Bin Sun +1
With the development of deep learning, advanced dialogue generation methods usually require a greater amount of computational resources. One promising approach to obtaining a high-…
Towards Diverse, Relevant and Coherent Open-Domain Dialogue Generation via Hybrid Latent Variables
Bin Sun, Yitong Li, Fei Mi +3
Conditional variational models, using either continuous or discrete latent variables, are powerful for open-domain dialogue response generation. However, previous works show that c…
Modeling Complex Dialogue Mappings via Sentence Semantic Segmentation Guided Conditional Variational Auto-Encoder
Bin Sun, Shaoxiong Feng, Yiwei Li +4
Complex dialogue mappings (CDM), including one-to-many and many-to-one mappings, tend to make dialogue models generate incoherent or dull responses, and modeling these mappings rem…