Search Results for author: Jing Bai

Found 23 papers, 7 papers with code

Enhancing Self-Attention with Knowledge-Assisted Attention Maps

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.

Multi-Task Learning Natural Language Understanding

Parameter-efficient is not sufficient: Exploring Parameter, Memory, and Time Efficient Adapter Tuning for Dense Predictions

no code implementations16 Jun 2023 Dongshuo Yin, Xueting Han, Bin Li, Hao Feng, Jing Bai

Despite their success, the existing PETL methods in CV can be computationally expensive and require large amounts of memory and time cost during training, which limits low-resource users from conducting research and applications on large models.

Transfer Learning

Time-aware Graph Structure Learning via Sequence Prediction on Temporal Graphs

1 code implementation13 Jun 2023 Haozhen Zhang, Xueting Han, Xi Xiao, Jing Bai

To address these issues, we propose a Time-aware Graph Structure Learning (TGSL) approach via sequence prediction on temporal graphs, which learns better graph structures for downstream tasks through adding potential temporal edges.

Contrastive Learning Data Augmentation +3

AdapterGNN: Efficient Delta Tuning Improves Generalization Ability in Graph Neural Networks

no code implementations19 Apr 2023 Shengrui Li, Xueting Han, Jing Bai

We have also provided a theoretical justification for delta tuning can improve the generalization ability of GNNs by applying generalization bounds.

Generalization Bounds

An Automated Question-Answering Framework Based on Evolution Algorithm

no code implementations26 Jan 2022 Sinan Tan, Hui Xue, Qiyu Ren, Huaping Liu, Jing Bai

Our framework is based on an innovative evolution algorithm, which is stable and suitable for multiple dataset scenario.

Question Answering

Learning Multi-granularity User Intent Unit for Session-based Recommendation

1 code implementation25 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.

Session-Based Recommendations

Graph Pointer Neural Networks

no code implementations3 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.

Node Classification

Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation

no code implementations5 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

Adaptive Transfer Learning on Graph Neural Networks

1 code implementation19 Jul 2021 Xueting Han, Zhenhuan Huang, Bang An, Jing Bai

We design an adaptive auxiliary loss weighting model to learn the weights of auxiliary tasks by quantifying the consistency between auxiliary tasks and the target task.

Meta-Learning Multi-Task Learning

Syntax-BERT: Improving Pre-trained Transformers with Syntax Trees

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.

Natural Language Understanding

Evolving Attention with Residual Convolutions

2 code implementations20 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.

Image Classification Machine Translation +2

Predictive Attention Transformer: Improving Transformer with Attention Map Prediction

no code implementations1 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.

Machine Translation

Multivariate Time-series Anomaly Detection via Graph Attention Network

2 code implementations4 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.

Anomaly Detection Graph Attention +3

LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression

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.

Blocking Knowledge Distillation +2

Contractive De-noising Auto-encoder

no code implementations17 May 2013 Fu-qiang Chen, Yan Wu, Guo-dong Zhao, Jun-ming Zhang, Ming Zhu, Jing Bai

Auto-encoder is a special kind of neural network based on reconstruction.

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