no code implementations • NAACL 2022 • Ao Jia, Yu He, Yazhou Zhang, Sagar Uprety, Dawei Song, Christina Lioma
Desire is a strong wish to do or have something, which involves not only a linguistic expression, but also underlying cognitive phenomena driving human feelings.
1 code implementation • 3 Apr 2024 • Zihan Yao, Yu He, Tianyu Qi, Ming Li
Our experiments on two different sizes of open-source large language models, the Llama2 7B and 13B, achieve state-of-the-art results compared to existing mainstream Model Editing methods.
no code implementations • 29 Feb 2024 • Yu He, Alexander Lam, Minming Li
Consequently, we characterize the conditions on scaling functions which ensure that agents have single-peaked preferences.
1 code implementation • 31 Dec 2023 • Licai Sun, Zheng Lian, Kexin Wang, Yu He, Mingyu Xu, Haiyang Sun, Bin Liu, JianHua Tao
Video-based facial affect analysis has recently attracted increasing attention owing to its critical role in human-computer interaction.
Ranked #3 on Dynamic Facial Expression Recognition on FERV39k
Dynamic Facial Expression Recognition Emotion Recognition +2
no code implementations • 14 Nov 2023 • Thomas Christie, Yu He
To address this issue, recent works have explored using expander graphs, which are highly-connected sparse graphs with low diameters, to perform message passing.
1 code implementation • 15 Oct 2023 • Tianyuan Zou, Zixuan Gu, Yu He, Hideaki Takahashi, Yang Liu, Ya-Qin Zhang
Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish cooperative training without exposing their raw data or model parameters.
3 code implementations • 18 Apr 2023 • Zheng Lian, Haiyang Sun, Licai Sun, Kang Chen, Mingyu Xu, Kexin Wang, Ke Xu, Yu He, Ying Li, Jinming Zhao, Ye Liu, Bin Liu, Jiangyan Yi, Meng Wang, Erik Cambria, Guoying Zhao, Björn W. Schuller, JianHua Tao
The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia.
no code implementations • 28 Mar 2023 • Yuan-Chen Guo, Yan-Pei Cao, Chen Wang, Yu He, Ying Shan, XiaoHu Qie, Song-Hai Zhang
With the emergence of neural radiance fields (NeRFs), view synthesis quality has reached an unprecedented level.
no code implementations • 8 Feb 2023 • Feng Qian, Yuehua Yue, Yu He, Hongtao Yu, Yingjie Zhou, Jinliang Tang, Guangmin Hu
Seismic acquisition footprints appear as stably faint and dim structures and emerge fully spatially coherent, causing inevitable damage to useful signals during the suppression process.
no code implementations • 29 Nov 2022 • Yu He, Petar Veličković, Pietro Liò, Andreea Deac
Neural algorithmic reasoning studies the problem of learning algorithms with neural networks, especially with graph architectures.
1 code implementation • 20 Mar 2022 • Yuezihan Jiang, Yu Cheng, Hanyu Zhao, Wentao Zhang, Xupeng Miao, Yu He, Liang Wang, Zhi Yang, Bin Cui
We introduce ZOOMER, a system deployed at Taobao, the largest e-commerce platform in China, for training and serving GNN-based recommendations over web-scale graphs.
no code implementations • CVPR 2022 • Yuan-Chen Guo, Di Kang, Linchao Bao, Yu He, Song-Hai Zhang
Specifically, we propose to split a scene into transmitted and reflected components, and model the two components with separate neural radiance fields.
no code implementations • 17 Oct 2020 • Hanzi Huang, Yetian Huang, Yu He, Haoshuo Chen, Yong Zhang, Qianwu Zhang, Nicolas K. Fontaine, Roland Ryf, Yingxiong Song, Yikai Su
We experimentally demonstrate a record net capacity per wavelength of 1. 23~Tb/s over a single silicon-on-insulator (SOI) multimode waveguide for optical interconnects employing on-chip mode-division multiplexing and 11$\times$11 multiple-in-multiple-out (MIMO) digital signal processing.
1 code implementation • 18 Nov 2019 • JianXin Li, Cheng Ji, Hao Peng, Yu He, Yangqiu Song, Xinmiao Zhang, Fanzhang Peng
However, despite the success of current random-walk-based methods, most of them are usually not expressive enough to preserve the personalized higher-order proximity and lack a straightforward objective to theoretically articulate what and how network proximity is preserved.
no code implementations • 25 Sep 2019 • Yu He, Shiyang Wen, Wenjin Wu, Yan Zhang, Siran Yang, Yuan Wei, Di Zhang, Guojie Song, Wei Lin, Liang Wang, Bo Zheng
The Graph Convolutional Network (GCN) and its variants are powerful models for graph representation learning and have recently achieved great success on many graph-based applications.
no code implementations • 7 Sep 2019 • Yu He, Yangqiu Song, Jian-Xin Li, Cheng Ji, Jian Peng, Hao Peng
Heterogeneous information network (HIN) embedding has gained increasing interests recently.