5 citations · 16 across the 4 of their papers we have counts for
4 papers
Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models Memories
Shizhe Diao, Tianyang Xu, Ruijia Xu +2
Pre-trained language models (PLMs) demonstrate excellent abilities to understand texts in the generic domain while struggling in a specific domain. Although continued pre-training…
X-VLM: All-In-One Pre-trained Model For Vision-Language Tasks
Yan Zeng, Xinsong Zhang, Hang Li +3
Vision language pre-training aims to learn alignments between vision and language from a large amount of data. Most existing methods only learn image-text alignments. Some others u…
Write and Paint: Generative Vision-Language Models are Unified Modal Learners
Shizhe Diao, Wangchunshu Zhou, Xinsong Zhang +1
Recent advances in vision-language pre-training have pushed the state-of-the-art on various vision-language tasks, making machines more capable of multi-modal writing (image-to-tex…
ArT: All-round Thinker for Unsupervised Commonsense Question-Answering
Jiawei Wang, Hai Zhao
Without labeled question-answer pairs for necessary training, unsupervised commonsense question-answering (QA) appears to be extremely challenging due to its indispensable unique p…