no code implementations • 5 Feb 2024 • Jing Yan, Liu Jiang, Jianfei Cui, Zhichen Zhao, Xingyan Bin, Feng Zhang, Zuotao Liu
Interest modeling in recommender system has been a constant topic for improving user experience, and typical interest modeling tasks (e. g. multi-interest, long-tail interest and long-term interest) have been investigated in many existing works.
no code implementations • 29 Sep 2023 • Yong Wu, Mingzhou Liu, Jing Yan, Yanwei Fu, Shouyan Wang, Yizhou Wang, Xinwei Sun
To accommodate these scenarios, we consider a new setting dubbed as multiple treatments and multiple outcomes.
no code implementations • 28 Feb 2023 • Yanchen Liu, Jing Yan, Yan Chen, Jing Liu, Hua Wu
Recent studies reveal that various biases exist in different NLP tasks, and over-reliance on biases results in models' poor generalization ability and low adversarial robustness.
no code implementations • 7 Oct 2022 • Japinder Nijjer, Mrityunjay Kothari, Changhao Li, Thomas Henzel, Qiuting Zhang, Jung-Shen B. Tai, Shuang Zhou, Sulin Zhang, Tal Cohen, Jing Yan
Active nematics are the nonequilibrium analog of passive liquid crystals in which anisotropic units consume free energy to drive emergent behavior.
no code implementations • 19 Jul 2022 • Jing Yan, Jie Wang, Robert Dallmann, Renquan Lu, Jérôme Charmet
Immunoaffinity-based liquid biopsies of circulating tumor cells (CTCs) hold great promise for cancer management, but typically suffer from low throughput, relative complexity and post-processing limitations.
1 code implementation • 25 May 2022 • Yanrui Du, Jing Yan, Yan Chen, Jing Liu, Sendong Zhao, Qiaoqiao She, Hua Wu, Haifeng Wang, Bing Qin
In this study, we focus on the spurious correlation between word features and labels that models learn from the biased data distribution of training data.
1 code implementation • 16 Dec 2021 • Hongyu Zhu, Yan Chen, Jing Yan, Jing Liu, Yu Hong, Ying Chen, Hua Wu, Haifeng Wang
For this purpose, we create a Chinese dataset namely DuQM which contains natural questions with linguistic perturbations to evaluate the robustness of question matching models.
no code implementations • 12 Sep 2018 • Yuanzhe Yao, Zeheng Wang, Liang Li, Kun Lu, Runyu Liu, Zhiyuan Liu, Jing Yan
In this work, an ontology-based model for AI-assisted medicine side-effect (SE) prediction is developed, where three main components, including the drug model, the treatment model, and the AI-assisted prediction model, of proposed model are presented.
no code implementations • 22 May 2018 • Ruida Zhou, Chao Gan, Jing Yan, Cong Shen
For the online setting, we propose a Cost-aware Cas- cading Upper Confidence Bound (CC-UCB) algo- rithm, and show that the cumulative regret scales in O(log T ).