most citedLearning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

ExVideo: Extending Video Diffusion Models via Parameter-Efficient Post-Tuning

Zhongjie Duan, Wenmeng Zhou, Cen Chen +2

Recently, advancements in video synthesis have attracted significant attention. Video synthesis models such as AnimateDiff and Stable Video Diffusion have demonstrated the practica…

cs.CV20241 cited

Diffutoon: High-Resolution Editable Toon Shading via Diffusion Models

Zhongjie Duan, Chengyu Wang, Cen Chen +2

Toon shading is a type of non-photorealistic rendering task of animation. Its primary purpose is to render objects with a flat and stylized appearance. As diffusion models have asc…

cs.CV2023

FastBlend: a Powerful Model-Free Toolkit Making Video Stylization Easier

Zhongjie Duan, Chengyu Wang, Cen Chen +3

With the emergence of diffusion models and rapid development in image processing, it has become effortless to generate fancy images in tasks such as style transfer and image editin…

cs.CV2023

Improving Zero-shot Visual Question Answering via Large Language Models with Reasoning Question Prompts

Yunshi Lan, Xiang Li, Xin Liu +3

Zero-shot Visual Question Answering (VQA) is a prominent vision-language task that examines both the visual and textual understanding capability of systems in the absence of traini…

cs.CL20231 cited

Learning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding

Ruyao Xu, Taolin Zhang, Chengyu Wang +6

Knowledge-Enhanced Pre-trained Language Models (KEPLMs) improve the performance of various downstream NLP tasks by injecting knowledge facts from large-scale Knowledge Graphs (KGs)…

cs.CL2023

Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation

Yuanyuan Liang, Jianing Wang, Hanlun Zhu +3

The task of Question Generation over Knowledge Bases (KBQG) aims to convert a logical form into a natural language question. For the sake of expensive cost of large-scale question…