61 citations · 105 across the 6 of their papers we have counts for
6 papers
Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!
Zecheng Tang, Pinzheng Wang, Keyan Zhou +3
Diffusion models have been successfully adapted to text generation tasks by mapping the discrete text into the continuous space. However, there exist nonnegligible gaps between tra…
Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening
Min Cao, Yang Bai, Jingyao Wang +3
Under the flourishing development in performance, current image-text retrieval methods suffer from -related time complexity, which hinders their application in practice. Targeti…
Visual Subtitle Feature Enhanced Video Outline Generation
Qi Lv, Ziqiang Cao, Wenrui Xie +10
With the tremendously increasing number of videos, there is a great demand for techniques that help people quickly navigate to the video segments they are interested in. However, c…
Revising Image-Text Retrieval via Multi-Modal Entailment
Xu Yan, Chunhui Ai, Ziqiang Cao +4
An outstanding image-text retrieval model depends on high-quality labeled data. While the builders of existing image-text retrieval datasets strive to ensure that the caption match…
Improving Multi-Document Summarization via Text Classification
Ziqiang Cao, Wenjie Li, Sujian Li +1
Developed so far, multi-document summarization has reached its bottleneck due to the lack of sufficient training data and diverse categories of documents. Text classification just…
Joint Copying and Restricted Generation for Paraphrase
Ziqiang Cao, Chuwei Luo, Wenjie Li +1
Many natural language generation tasks, such as abstractive summarization and text simplification, are paraphrase-orientated. In these tasks, copying and rewriting are two main wri…