Typically, the risk can be identified by jointly considering product content (e. g., title and image) and seller behavior.
Among ubiquitous multimodal data in the real world, text is the modality generated by human, while image reflects the physical world honestly.
Large-scale knowledge graphs (KGs) are shown to become more important in current information systems.
Deep reinforcement learning (RL) has been a commonly-used strategy for the abstractive summarization task to address both the exposure bias and non-differentiable task issues.
The pre-trained network is then fine-tuned using human-annotated disfluency detection training data.
Semantically controlled neural response generation on limited-domain has achieved great performance.
Ranked #5 on Data-to-Text Generation on MULTIWOZ 2.1
Distant supervision can effectively label data for relation extraction, but suffers from the noise labeling problem.
The experimental results show that the proposed strategy significantly improves the performance of distant supervision comparing to state-of-the-art systems.