research
∙
12/04/2022
Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation
Large pretrained language models can easily produce toxic or biased cont...
share
research
∙
09/30/2021
Towards Efficient Post-training Quantization of Pre-trained Language Models
Network quantization has gained increasing attention with the rapid grow...
research
∙
03/05/2021
Non-invasive Self-attention for Side Information Fusion in Sequential Recommendation
Sequential recommender systems aim to model users' evolving interests fr...
research
∙
06/21/2020
Enriching Large-Scale Eventuality Knowledge Graph with Entailment Relations
Computational and cognitive studies suggest that the abstraction of even...
research
∙
08/21/2019
Dialog State Tracking with Reinforced Data Augmentation
Neural dialog state trackers are generally limited due to the lack of qu...
research
∙
06/24/2019
Decomposable Neural Paraphrase Generation
Paraphrasing exists at different granularity levels, such as lexical lev...
research
∙
12/26/2018
Meta Learning for Few-shot Keyword Spotting
Keyword spotting with limited training data is a challenging task which ...
research
∙
11/01/2017
Paraphrase Generation with Deep Reinforcement Learning
Automatic generation of paraphrases for a given sentence is an important...
research
∙
11/07/2016
Neural Machine Translation with Reconstruction
Although end-to-end Neural Machine Translation (NMT) has achieved remark...
research
∙
12/04/2015
Neural Generative Question Answering
This paper presents an end-to-end neural network model, named Neural Gen...
research
∙
04/23/2015
Multimodal Convolutional Neural Networks for Matching Image and Sentence
In this paper, we propose multimodal convolutional neural networks (m-CN...
research
∙
03/09/2015
Neural Responding Machine for Short-Text Conversation
We propose Neural Responding Machine (NRM), a neural network-based respo...
research
∙
11/25/2013
