350 citations · 509 across the 27 of their papers we have counts for
27 papers
Cell-inspired, massive electromodulation of interfacial energy dissipation
Yu Zhang, Di Jin, Ran Tivony +2
Transient electric fields across cell bilayer membranes can lead to electroporation, as well as to cell fusion, and have been extensively studied. We find that transmembrane electr…
A Survey on Fairness-aware Recommender Systems
Di Jin, Luzhi Wang, He Zhang +4
As information filtering services, recommender systems have extremely enriched our daily life by providing personalized suggestions and facilitating people in decision-making, whic…
WebCPM: Interactive Web Search for Chinese Long-form Question Answering
Yujia Qin, Zihan Cai, Dian Jin +12
Long-form question answering (LFQA) aims at answering complex, open-ended questions with detailed, paragraph-length responses. The de facto paradigm of LFQA necessitates two proced…
Multi-lipid synergy in synovial lubrication: natural redundancy vs. natural selection
Yifeng Cao, Di Jin, Nir Kampf +1
The very low sliding friction of articular cartilage in the major synovial joints such as hips and knees is crucial for their well-being, and has been attributed to lubrication by…
Parameter-efficient Tuning of Large-scale Multimodal Foundation Model
Haixin Wang, Xinlong Yang, Jianlong Chang +5
Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence. The c…
Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptive Residual Module
Jingbo Zhou, Yixuan Du, Ruqiong Zhang +7
Graph Neural Networks (GNNs), a type of neural network that can learn from graph-structured data through neighborhood information aggregation, have shown superior performance in va…
KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks
Zhizhi Yu, Di Jin, Cuiying Huo +5
Social Internet of Things (SIoT), a promising and emerging paradigm that injects the notion of social networking into smart objects (i.e., things), paving the way for the next gene…
Parameter-Efficient Low-Resource Dialogue State Tracking by Prompt Tuning
Mingyu Derek Ma, Jiun-Yu Kao, Shuyang Gao +4
Dialogue state tracking (DST) is an important step in dialogue management to keep track of users' beliefs. Existing works fine-tune all language model (LM) parameters to tackle the…
T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation
Cuiying Huo, Di Jin, Yawen Li +3
Graph Neural Networks (GNNs) have been a prevailing technique for tackling various analysis tasks on graph data. A key premise for the remarkable performance of GNNs relies on comp…
A Systematic Evaluation of Response Selection for Open Domain Dialogue
Behnam Hedayatnia, Di Jin, Yang Liu +1
Recent progress on neural approaches for language processing has triggered a resurgence of interest on building intelligent open-domain chatbots. However, even the state-of-the-art…
RAW-GNN: RAndom Walk Aggregation based Graph Neural Network
Di Jin, Rui Wang, Meng Ge +4
Graph-Convolution-based methods have been successfully applied to representation learning on homophily graphs where nodes with the same label or similar attributes tend to connect…
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code
Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran +74
Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using…
TeKo: Text-Rich Graph Neural Networks with External Knowledge
Zhizhi Yu, Di Jin, Jianguo Wei +5
Graph Neural Networks (GNNs) have gained great popularity in tackling various analytical tasks on graph-structured data (i.e., networks). Typical GNNs and their variants follow a m…
TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature
Cuiying Huo, Di Jin, Chundong Liang +3
Trust evaluation is critical for many applications such as cyber security, social communication and recommender systems. Users and trust relationships among them can be seen as a g…
CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning
Di Jin, Luzhi Wang, Yizhen Zheng +4
Graph similarity learning refers to calculating the similarity score between two graphs, which is required in many realistic applications, such as visual tracking, graph classifica…
Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning
Cuiying Huo, Dongxiao He, Yawen Li +5
Heterogeneous graph neural network (HGNN) is a very popular technique for the modeling and analysis of heterogeneous graphs. Most existing HGNN-based approaches are supervised or s…
Graph Neural Networks for Graphs with Heterophily: A Survey
Xin Zheng, Yi Wang, Yixin Liu +5
Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriad graph analytic tasks and applications. Most GNNs rely on the homophily assu…
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View
Di Jin, Elena Sergeeva, Wei-Hung Weng +2
The increasing availability of large collections of electronic health record (EHR) data and unprecedented technical advances in deep learning (DL) have sparked a surge of research…
Leveraging the Graph Structure of Neural Network Training Dynamics
Fatemeh Vahedian, Ruiyu Li, Puja Trivedi +2
Understanding the training dynamics of deep neural networks (DNNs) is important as it can lead to improved training efficiency and task performance. Recent works have demonstrated…
Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation
Di Jin, Bunyamin Sisman, Hao Wei +2
Multi-source entity linkage focuses on integrating knowledge from multiple sources by linking the records that represent the same real world entity. This is critical in high-impact…
Towards Zero and Few-shot Knowledge-seeking Turn Detection in Task-orientated Dialogue Systems
Di Jin, Shuyang Gao, Seokhwan Kim +2
Most prior work on task-oriented dialogue systems is restricted to supporting domain APIs. However, users may have requests that are out of the scope of these APIs. This work focus…
A Comprehensive Survey on Community Detection with Deep Learning
Xing Su, Shan Xue, Fanzhen Liu +9
A community reveals the features and connections of its members that are different from those in other communities in a network. Detecting communities is of great significance in n…
Evaluation Toolkit For Robustness Testing Of Automatic Essay Scoring Systems
Anubha Kabra, Mehar Bhatia, Yaman Kumar +2
Automatic scoring engines have been used for scoring approximately fifteen million test-takers in just the last three years. This number is increasing further due to COVID-19 and t…
Learning Continuous-Time Dynamics by Stochastic Differential Networks
Yingru Liu, Yucheng Xing, Xuewen Yang +4
Learning continuous-time stochastic dynamics is a fundamental and essential problem in modeling sporadic time series, whose observations are irregular and sparse in both time and d…