no code implementations • 17 Apr 2024 • Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
The progress of humanity is driven by those successful discoveries accompanied by countless failed experiments.
1 code implementation • 9 Apr 2024 • Haotian Chen, Anna Kuzina, Babak Esmaeili, Jakub M Tomczak
We model gradient updates as a probabilistic model and utilize stochastic variational inference (SVI) to derive an efficient and effective update rule.
no code implementations • 9 Oct 2023 • Chang'an Yi, Haotian Chen, Yifan Zhang, Yonghui Xu, Lizhen Cui
This pronounced emphasis on classification might lead numerous newcomers and engineers to mistakenly assume that classic TTA methods designed for classification can be directly applied to segmentation.
1 code implementation • 20 Jun 2023 • Haotian Chen, Bingsheng Chen, Xiangdong Zhou
Then, we conduct investigations and reveal the fact that: In contrast to humans, the representative state-of-the-art (SOTA) models in DocRE exhibit different decision rules.
no code implementations • 7 May 2023 • Chang'an Yi, Haotian Chen, Yonghui Xu, Yifan Zhang
Federated domain adaptation (FDA) aims to collaboratively transfer knowledge from source clients (domains) to the related but different target client, without communicating the local data of any client.
1 code implementation • 29 Mar 2023 • Xinxin Hu, Haotian Chen, Junjie Zhang, Hongchang Chen, Shuxin Liu, Xing Li, Yahui Wang, xiangyang xue
Extensive experiments on two real-world telecom fraud detection datasets demonstrate that our proposed method is effective for the graph imbalance problem, outperforming the state-of-the-art GNNs and GNN-based fraud detectors.
1 code implementation • 28 Mar 2023 • Xinxin Hu, Haotian Chen, Hongchang Chen, Shuxin Liu, Xing Li, Shibo Zhang, Yahui Wang, xiangyang xue
But the imbalance problem in the aforementioned data, which could severely hinder the effectiveness of fraud detectors based on graph neural networks(GNN), has hardly been addressed in previous work.
no code implementations • 14 Nov 2022 • Yiran Liu, Xiao Liu, Haotian Chen, Yang Yu
We use our theoretical framework to explain why the current debiasing methods cause performance degradation.
no code implementations • 6 Nov 2022 • Haotian Chen, Lingwei Zhang, Yiran Liu, Fanchao Chen, Yang Yu
To validate our theoretical analysis, we further propose another method using our proposed Causality-Aware Self-Attention Mechanism (CASAM) to guide the model to learn the underlying causality knowledge in legal texts.
no code implementations • Knowledge-Based Systems 2022 • Changan Yi, Haotian Chen, Yonghui Xu, Yong liu, Lei Jiang, Haishu Tan
Accordingly, ATPL will use the pseudo-labeled information to improve the adversarial training process, which can guarantee the feature transferability by generating adversarial data to fill in the domain gap.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Haotian Chen, Andrej Zukov-Gregoric, Xi David Li, Sahil Wadhwa
We propose yet another entity linking model (YELM) which links words to entities instead of spans.