no code implementations • 5 Mar 2024 • Xiaoyu Zhan, Jianxin Yang, Yuanqi Li, Jie Guo, Yanwen Guo, Wenping Wang
SHERT applies semantic- and normal-based sampling between the detailed surface (e. g. mesh and SDF) and the corresponding SMPL-X model to obtain a partially sampled semantic mesh and then generates the complete semantic mesh by our specifically designed self-supervised completion and refinement networks.
2 code implementations • 8 Nov 2023 • Jianxin Yang
We present LongQLoRA, an efficient and effective method to extend context length of large language models with less training resources.
1 code implementation • CVPR 2023 • Yunpeng Han, Lisai Zhang, Qingcai Chen, Zhijian Chen, Zhonghua Li, Jianxin Yang, Zhao Cao
We propose a method for fine-grained fashion vision-language pre-training based on fashion Symbols and Attributes Prompt (FashionSAP) to model fine-grained multi-modalities fashion attributes and characteristics.
2 code implementations • 3 Sep 2021 • Xiao Gu, Jianxin Yang, Hanxiao Zhang, Jianing Qiu, Frank Po Wen Lo, Yao Guo, Guang-Zhong Yang, Benny Lo
It can generalize well on the real-world data from all the other unseen views.
1 code implementation • IJCNLP 2019 • Shiyuan Xiao, Yuanxin Ouyang, Wenge Rong, Jianxin Yang, Zhang Xiong
The segmentation problem is one of the fundamental challenges associated with name entity recognition (NER) tasks that aim to reduce the boundary error when detecting a sequence of entity words.
Ranked #18 on Named Entity Recognition (NER) on WNUT 2017
1 code implementation • NAACL 2019 • Jianxin Yang, Wenge Rong, Libin Shi, Zhang Xiong
So the QA pairs capture features and information from both question text and answer text, interacting and improving vector representations iteratively through hops.