no code implementations • 15 Dec 2024 • Ziang Zhou, Zhihao Ding, Jieming Shi, Qing Li, Shiqi Shen
Moreover, we observe that in a GNN layer, FT and GP operations often have opposing smoothing effects: GP is aggressive, while FT is conservative, in smoothing.
1 code implementation • 10 Aug 2024 • Yiran Li, Gongyao Guo, Jieming Shi, Renchi Yang, Shiqi Shen, Qing Li, Jun Luo
In this paper, we first present AHCKA as an efficient approach to attributed hypergraph clustering (AHC).
1 code implementation • 17 Jun 2024 • Wenkai Yang, Shiqi Shen, Guangyao Shen, Wei Yao, Yong liu, Zhi Gong, Yankai Lin, Ji-Rong Wen
However, we are concerned that behind such a promising phenomenon, whether there exists an issue of weak-to-strong deception, where strong models deceive weak models by exhibiting well-aligned in areas known to weak models but producing misaligned behaviors in cases weak models do not know.
no code implementations • NeurIPS 2023 • Zeyang Zhang, Xin Wang, Ziwei Zhang, Guangyao Shen, Shiqi Shen, Wenwu Zhu
To address the challenge, we propose a novel Disentangled Self-supervised Graph Neural Architecture Search (DSGAS) model, which is able to discover the optimal architectures capturing various latent graph factors in a self-supervised fashion based on unlabeled graph data.
1 code implementation • 16 Oct 2023 • Zhihao Ding, Jieming Shi, Shiqi Shen, Xuequn Shang, Jiannong Cao, Zhipeng Wang, Zhi Gong
We find that substructure differences commonly exist between ID and OOD graphs, and design SGOOD with a series of techniques to encode task-agnostic substructures for effective OOD detection.
1 code implementation • 18 Sep 2022 • Teodora Baluta, Shiqi Shen, S. Hitarth, Shruti Tople, Prateek Saxena
Our causal models also show a new connection between generalization and MI attacks via their shared causal factors.
no code implementations • 25 Jun 2019 • Teodora Baluta, Shiqi Shen, Shweta Shinde, Kuldeep S. Meel, Prateek Saxena
Neural networks are increasingly employed in safety-critical domains.
6 code implementations • 20 Jun 2017 • Jiacheng Zhang, Yanzhuo Ding, Shiqi Shen, Yong Cheng, Maosong Sun, Huanbo Luan, Yang Liu
This paper introduces THUMT, an open-source toolkit for neural machine translation (NMT) developed by the Natural Language Processing Group at Tsinghua University.
no code implementations • 7 Apr 2016 • Ayana, Shiqi Shen, Yu Zhao, Zhiyuan Liu, Maosong Sun
Recently, neural models have been proposed for headline generation by learning to map documents to headlines with recurrent neural networks.
1 code implementation • 15 Dec 2015 • Yong Cheng, Shiqi Shen, Zhongjun He, wei he, Hua Wu, Maosong Sun, Yang Liu
The attentional mechanism has proven to be effective in improving end-to-end neural machine translation.
1 code implementation • ACL 2016 • Shiqi Shen, Yong Cheng, Zhongjun He, wei he, Hua Wu, Maosong Sun, Yang Liu
We propose minimum risk training for end-to-end neural machine translation.