research
∙
03/09/2023
Cloudless-Training: A Framework to Improve Efficiency of Geo-Distributed ML Training
Geo-distributed ML training can benefit many emerging ML scenarios (e.g....
share
research
∙
09/14/2021
Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
Being able to reply with a related, fluent, and informative response is ...
research
∙
09/13/2021
Text is NOT Enough: Integrating Visual Impressions intoOpen-domain Dialogue Generation
Open-domain dialogue generation in natural language processing (NLP) is ...
research
∙
06/26/2021
Improving Sequential Recommendation Consistency with Self-Supervised Imitation
Most sequential recommendation models capture the features of consecutiv...
research
∙
10/21/2020
TargetDrop: A Targeted Regularization Method for Convolutional Neural Networks
Dropout regularization has been widely used in deep learning but perform...
research
∙
09/16/2020
Group-wise Contrastive Learning for Neural Dialogue Generation
Neural dialogue response generation has gained much popularity in recent...
research
∙
04/06/2020
Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight
Current state-of-the-art neural dialogue models learn from human convers...
research
∙
03/02/2020
Learning from Easy to Complex: Adaptive Multi-curricula Learning for Neural Dialogue Generation
Current state-of-the-art neural dialogue systems are mainly data-driven ...
research
∙
01/18/2020
Adaptive Parameterization for Neural Dialogue Generation
Neural conversation systems generate responses based on the sequence-to-...
research
∙
05/02/2018