1 code implementation • 25 Apr 2024 • Sifan Long, Linbin Wang, Zhen Zhao, Zichang Tan, Yiming Wu, Shengsheng Wang, Jingdong Wang
In light of this, we propose Training-Free Unsupervised Prompts (TFUP), which maximally preserves the inherent representation capabilities and enhances them with a residual connection to similarity-based prediction probabilities in a training-free and labeling-free manner.
1 code implementation • 15 May 2023 • Bing Wang, Ximing Li, Zhiyao Yang, Yuanyuan Guan, Jiayin Li, Shengsheng Wang
To solve the problems, we fine-tune PLMs by leveraging the frequency information of words and propose a novel USRL framework, namely Sentence Representation Learning with Frequency-induced Adversarial tuning and Incomplete sentence filtering (SLT-FAI).
no code implementations • ICCV 2023 • Sifan Long, Zhen Zhao, Junkun Yuan, Zichang Tan, JiangJiang Liu, Luping Zhou, Shengsheng Wang, Jingdong Wang
A contrastive loss is employed to align such augmented text and image representations on downstream tasks.
1 code implementation • CVPR 2023 • Sifan Long, Zhen Zhao, Jimin Pi, Shengsheng Wang, Jingdong Wang
In this paper, we emphasize the cruciality of diverse global semantics and propose an efficient token decoupling and merging method that can jointly consider the token importance and diversity for token pruning.
Ranked #4 on Efficient ViTs on ImageNet-1K (with DeiT-T)
no code implementations • 15 Jul 2021 • Wenzhuo Song, Shoujin Wang, Yan Wang, Shengsheng Wang
The obtained similar sessions are then utilized to complement and optimize the preference representation learned from the current short session by the local module for more accurate next-item recommendations in this short session.
no code implementations • 29 Oct 2019 • Wenzhuo Song, Hongxu Chen, Xueyan Liu, Hongzhe Jiang, Shengsheng Wang
Signed network embedding methods aim to learn vector representations of nodes in signed networks.