no code implementations • NAACL 2022 • Jiangang Bai, Yujing Wang, Hong Sun, Ruonan Wu, Tianmeng Yang, Pengfei Tang, Defu Cao, Mingliang Zhang1, Yunhai Tong, Yaming Yang, Jing Bai, Ruofei Zhang, Hao Sun, Wei Shen
Large-scale pre-trained language models have attracted extensive attentions in the research community and shown promising results on various tasks of natural language processing.
no code implementations • 17 Aug 2023 • Tianmeng Yang, Min Zhou, Yujing Wang, Zhengjie Lin, Lujia Pan, Bin Cui, Yunhai Tong
Graph Active Learning (GAL), which aims to find the most informative nodes in graphs for annotation to maximize the Graph Neural Networks (GNNs) performance, has attracted many research efforts but remains non-trivial challenges.
no code implementations • 26 Jun 2023 • Junyan Li, Li Lyna Zhang, Jiahang Xu, Yujing Wang, Shaoguang Yan, Yunqing Xia, Yuqing Yang, Ting Cao, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang
Deploying pre-trained transformer models like BERT on downstream tasks in resource-constrained scenarios is challenging due to their high inference cost, which grows rapidly with input sequence length.
1 code implementation • 23 May 2023 • Rui Li, Xu Chen, Chaozhuo Li, Yanming Shen, Jianan Zhao, Yujing Wang, Weihao Han, Hao Sun, Weiwei Deng, Qi Zhang, Xing Xie
Embedding models have shown great power in knowledge graph completion (KGC) task.
1 code implementation • 17 Mar 2023 • Yidan Zhang, Ting Zhang, Dong Chen, Yujing Wang, Qi Chen, Xing Xie, Hao Sun, Weiwei Deng, Qi Zhang, Fan Yang, Mao Yang, Qingmin Liao, Baining Guo
While generative modeling has been ubiquitous in natural language processing and computer vision, its application to image retrieval remains unexplored.
1 code implementation • 15 Mar 2023 • Daixuan Cheng, Shaohan Huang, Junyu Bi, Yuefeng Zhan, Jianfeng Liu, Yujing Wang, Hao Sun, Furu Wei, Denvy Deng, Qi Zhang
Large Language Models (LLMs) are popular for their impressive abilities, but the need for model-specific fine-tuning or task-specific prompt engineering can hinder their generalization.
no code implementations • 15 Mar 2023 • Li Lyna Zhang, Xudong Wang, Jiahang Xu, Quanlu Zhang, Yujing Wang, Yuqing Yang, Ningxin Zheng, Ting Cao, Mao Yang
The combination of Neural Architecture Search (NAS) and quantization has proven successful in automatically designing low-FLOPs INT8 quantized neural networks (QNN).
no code implementations • 4 Mar 2023 • Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu
Causal analysis for time series data, in particular estimating individualized treatment effect (ITE), is a key task in many real-world applications, such as finance, retail, healthcare, etc.
no code implementations • 30 Dec 2022 • Hong Guo, Yujing Wang, Jieyu Zhang, Zhengjie Lin, Yunhai Tong, Lei Yang, Luoxing Xiong, Congrui Huang
Time-series anomaly detection is an important task and has been widely applied in the industry.
1 code implementation • 16 Dec 2022 • Yujing Wang, Yaming Yang, Zhuo Li, Jiangang Bai, Mingliang Zhang, Xiangtai Li, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
To the best of our knowledge, this is the first work that explicitly models the layer-wise evolution of attention maps.
no code implementations • 30 Aug 2022 • Li Lyna Zhang, Youkow Homma, Yujing Wang, Min Wu, Mao Yang, Ruofei Zhang, Ting Cao, Wei Shen
Remarkably, under our latency requirement of 1900us on CPU, SwiftPruner achieves a 0. 86% higher AUC than the state-of-the-art uniform sparse baseline for BERT-Mini on a large scale real-world dataset.
no code implementations • 2 Aug 2022 • Jieyu Zhang, Yujing Wang, Yaming Yang, Yang Luo, Alexander Ratner
Thus, in this work, we study the application of WS on binary classification tasks with positive labeling sources only.
1 code implementation • 6 Jun 2022 • Yujing Wang, Yingyan Hou, Haonan Wang, Ziming Miao, Shibin Wu, Hao Sun, Qi Chen, Yuqing Xia, Chengmin Chi, Guoshuai Zhao, Zheng Liu, Xing Xie, Hao Allen Sun, Weiwei Deng, Qi Zhang, Mao Yang
To this end, we propose Neural Corpus Indexer (NCI), a sequence-to-sequence network that generates relevant document identifiers directly for a designated query.
no code implementations • NAACL 2022 • Qingfeng Sun, Can Xu, Huang Hu, Yujing Wang, Jian Miao, Xiubo Geng, Yining Chen, Fei Xu, Daxin Jiang
(2) How to cohere with context and preserve the knowledge when generating a stylized response.
1 code implementation • 25 Dec 2021 • Jiayan Guo, Yaming Yang, Xiangchen Song, Yuan Zhang, Yujing Wang, Jing Bai, Yan Zhang
Specifically, we creatively propose Multi-granularity Intent Heterogeneous Session Graph which captures the interactions between different granularity intent units and relieves the burden of long-dependency.
no code implementations • ACL 2022 • Qingfeng Sun, Yujing Wang, Can Xu, Kai Zheng, Yaming Yang, Huang Hu, Fei Xu, Jessica Zhang, Xiubo Geng, Daxin Jiang
In such a low-resource setting, we devise a novel conversational agent, Divter, in order to isolate parameters that depend on multimodal dialogues from the entire generation model.
no code implementations • ICLR 2022 • Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner
Creating labeled training sets has become one of the major roadblocks in machine learning.
no code implementations • 3 Oct 2021 • Tianmeng Yang, Yujing Wang, Zhihan Yue, Yaming Yang, Yunhai Tong, Jing Bai
On the one hand, multi-hop-based approaches do not explicitly distinguish relevant nodes from a large number of multi-hop neighborhoods, leading to a severe over-smoothing problem.
1 code implementation • 23 Sep 2021 • Jieyu Zhang, Yue Yu, Yinghao Li, Yujing Wang, Yaming Yang, Mao Yang, Alexander Ratner
To address these problems, we introduce a benchmark platform, WRENCH, for thorough and standardized evaluation of WS approaches.
no code implementations • 5 Sep 2021 • Yankai Chen, Yaming Yang, Yujing Wang, Jing Bai, Xiangchen Song, Irwin King
However, simply integrating KGs in current KG-based RS models is not necessarily a guarantee to improve the recommendation performance, which may even weaken the holistic model capability.
Click-Through Rate Prediction
Knowledge-Aware Recommendation
+1
1 code implementation • 21 Jun 2021 • Jianpeng Chen, Yujing Wang, Ming Zeng, Zongyi Xiang, Bitan Hou, Yunhai Tong, Ole J. Mengshoel, Yazhou Ren
CustomGNN can automatically learn the high-level semantics for specific downstream tasks, highlight semantically relevant paths, and filter out task-irrelevant information in the graph.
1 code implementation • 19 Jun 2021 • Zhihan Yue, Yujing Wang, Juanyong Duan, Tianmeng Yang, Congrui Huang, Yunhai Tong, Bixiong Xu
Furthermore, to obtain the representation of an arbitrary sub-sequence in the time series, we can apply a simple aggregation over the representations of corresponding timestamps.
2 code implementations • NeurIPS 2020 • Defu Cao, Yujing Wang, Juanyong Duan, Ce Zhang, Xia Zhu, Conguri Huang, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang
In this paper, we propose Spectral Temporal Graph Neural Network (StemGNN) to further improve the accuracy of multivariate time-series forecasting.
1 code implementation • EACL 2021 • Jiangang Bai, Yujing Wang, Yiren Chen, Yaming Yang, Jing Bai, Jing Yu, Yunhai Tong
Pre-trained language models like BERT achieve superior performances in various NLP tasks without explicit consideration of syntactic information.
2 code implementations • 20 Feb 2021 • Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
In this paper, we propose a novel and generic mechanism based on evolving attention to improve the performance of transformers.
no code implementations • 1 Jan 2021 • Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Yunhai Tong
Instead, we model their dependencies via a chain of prediction models that take previous attention maps as input to predict the attention maps of a new layer through convolutional neural networks.
no code implementations • 14 Oct 2020 • Yiren Chen, Yaming Yang, Hong Sun, Yujing Wang, Yu Xu, Wei Shen, Rong Zhou, Yunhai Tong, Jing Bai, Ruofei Zhang
We add the model designed by AutoADR as a sub-model into the production Ad Relevance model.
1 code implementation • 16 Sep 2020 • Jing Yu, Yuan Chai, Yujing Wang, Yue Hu, Qi Wu
We first build a cognitive structure CogTree to organize the relationships based on the prediction of a biased SGG model.
Ranked #2 on
Scene Graph Generation
on Visual Genome
(mean Recall @20 metric)
2 code implementations • 4 Sep 2020 • Hang Zhao, Yujing Wang, Juanyong Duan, Congrui Huang, Defu Cao, Yunhai Tong, Bixiong Xu, Jing Bai, Jie Tong, Qi Zhang
Anomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications.
no code implementations • 31 Aug 2020 • Jing Yu, Zihao Zhu, Yujing Wang, Weifeng Zhang, Yue Hu, Jianlong Tan
Finally, we perform graph neural networks to infer the global-optimal answer by jointly considering all the concepts.
no code implementations • 25 Aug 2020 • Yuanxiang Ying, Juanyong Duan, Chunlei Wang, Yujing Wang, Congrui Huang, Bixiong Xu
The task is challenging because of the complex characteristics of time-series, which are messy, stochastic, and often without proper labels.
no code implementations • 16 Jun 2020 • Zihao Zhu, Jing Yu, Yujing Wang, Yajing Sun, Yue Hu, Qi Wu
In this paper, we depict an image by a multi-modal heterogeneous graph, which contains multiple layers of information corresponding to the visual, semantic and factual features.
no code implementations • COLING 2020 • Yihuan Mao, Yujing Wang, Chufan Wu, Chen Zhang, Yang Wang, Yaming Yang, Quanlu Zhang, Yunhai Tong, Jing Bai
BERT is a cutting-edge language representation model pre-trained by a large corpus, which achieves superior performances on various natural language understanding tasks.
1 code implementation • 6 Jan 2020 • Yuge Zhang, Zejun Lin, Junyang Jiang, Quanlu Zhang, Yujing Wang, Hui Xue, Chen Zhang, Yaming Yang
With the success of deep neural networks, Neural Architecture Search (NAS) as a way of automatic model design has attracted wide attention.
no code implementations • 23 Dec 2019 • Yujing Wang, Yaming Yang, Yiren Chen, Jing Bai, Ce Zhang, Guinan Su, Xiaoyu Kou, Yunhai Tong, Mao Yang, Lidong Zhou
Learning text representation is crucial for text classification and other language related tasks.
no code implementations • 21 Nov 2019 • Bitan Hou, Yujing Wang, Ming Zeng, Shan Jiang, Ole J. Mengshoel, Yunhai Tong, Jing Bai
For these applications, graph embedding is crucial as it provides vector representations of the graph.
no code implementations • 10 Oct 2019 • Xupeng Miao, Nezihe Merve Gürel, Wentao Zhang, Zhichao Han, Bo Li, Wei Min, Xi Rao, Hansheng Ren, Yinan Shan, Yingxia Shao, Yujie Wang, Fan Wu, Hui Xue, Yaming Yang, Zitao Zhang, Yang Zhao, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang
Despite the wide application of Graph Convolutional Network (GCN), one major limitation is that it does not benefit from the increasing depth and suffers from the oversmoothing problem.
3 code implementations • 10 Jun 2019 • Hansheng Ren, Bixiong Xu, Yujing Wang, Chao Yi, Congrui Huang, Xiaoyu Kou, Tony Xing, Mao Yang, Jie Tong, Qi Zhang
At Microsoft, we develop a time-series anomaly detection service which helps customers to monitor the time-series continuously and alert for potential incidents on time.