12 citations · 37 across the 7 of their papers we have counts for
7 papers
Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks
Xinsong Zhang, Yan Zeng, Jipeng Zhang +1
Foundation models or pre-trained models have substantially improved the performance of various language, vision, and vision-language understanding tasks. However, existing foundati…
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…
EfficientVLM: Fast and Accurate Vision-Language Models via Knowledge Distillation and Modal-adaptive Pruning
Tiannan Wang, Wangchunshu Zhou, Yan Zeng +1
Pre-trained vision-language models (VLMs) have achieved impressive results in a range of vision-language tasks. However, popular VLMs usually consist of hundreds of millions of par…
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…
VLUE: A Multi-Task Benchmark for Evaluating Vision-Language Models
Wangchunshu Zhou, Yan Zeng, Shizhe Diao +1
Recent advances in vision-language pre-training (VLP) have demonstrated impressive performance in a range of vision-language (VL) tasks. However, there exist several challenges for…
AMBERT: A Pre-trained Language Model with Multi-Grained Tokenization
Xinsong Zhang, Pengshuai Li, Hang Li
Pre-trained language models such as BERT have exhibited remarkable performances in many tasks in natural language understanding (NLU). The tokens in the models are usually fine-gra…
Multi-labeled Relation Extraction with Attentive Capsule Network
Xinsong Zhang, Pengshuai Li, Weijia Jia +1
To disclose overlapped multiple relations from a sentence still keeps challenging. Most current works in terms of neural models inconveniently assuming that each sentence is explic…