56 citations · 140 across the 14 of their papers we have counts for
14 papers
Uncovering Cross-Domain Recommendation Ability of Large Language Models
Xinyi Liu, Ruijie Wang, Dachun Sun +2
Cross-Domain Recommendation (CDR) seeks to enhance item retrieval in low-resource domains by transferring knowledge from high-resource domains. While recent advancements in Large L…
Foundation Models for CPS-IoT: Opportunities and Challenges
Ozan Baris, Yizhuo Chen, Gaofeng Dong +9
Methods from machine learning (ML) have transformed the implementation of Perception-Cognition-Communication-Action loops in Cyber-Physical Systems (CPS) and the Internet of Things…
Perturbation-based Graph Active Learning for Weakly-Supervised Belief Representation Learning
Dachun Sun, Ruijie Wang, Jinning Li +4
This paper addresses the problem of optimizing the allocation of labeling resources for semi-supervised belief representation learning in social networks. The objective is to strat…
On the Efficiency and Robustness of Vibration-based Foundation Models for IoT Sensing: A Case Study
Tomoyoshi Kimura, Jinyang Li, Tianshi Wang +9
This paper demonstrates the potential of vibration-based Foundation Models (FMs), pre-trained with unlabeled sensing data, to improve the robustness of run-time inference in (a cla…
SudokuSens: Enhancing Deep Learning Robustness for IoT Sensing Applications using a Generative Approach
Tianshi Wang, Jinyang Li, Ruijie Wang +7
This paper introduces SudokuSens, a generative framework for automated generation of training data in machine-learning-based Internet-of-Things (IoT) applications, such that the ge…
FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space
Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu +5
This paper proposes a novel contrastive learning framework, called FOCAL, for extracting comprehensive features from multimodal time-series sensing signals through self-supervised…
Influence Pathway Discovery on Social Media
Xinyi Liu, Ruijie Wang, Dachun Sun +13
This paper addresses influence pathway discovery, a key emerging problem in today's online media. We propose a discovery algorithm that leverages recently published work on unsuper…
Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning
Ruijie Wang, Baoyu Li, Yichen Lu +6
This paper studies speculative reasoning task on real-world knowledge graphs (KG) that contain both \textit{false negative issue} (i.e., potential true facts being excluded) and \t…
Unsupervised Image Classification by Ideological Affiliation from User-Content Interaction Patterns
Xinyi Liu, Jinning Li, Dachun Sun +6
The proliferation of political memes in modern information campaigns calls for efficient solutions for image classification by ideological affiliation. While significant advances h…
Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs
Ruijie Wang, Zheng Li, Dachun Sun +4
In this paper, we investigate a realistic but underexplored problem, called few-shot temporal knowledge graph reasoning, that aims to predict future facts for newly emerging entiti…
Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders
Jinning Li, Huajie Shao, Dachun Sun +6
This paper develops a novel unsupervised algorithm for belief representation learning in polarized networks that (i) uncovers the latent dimensions of the underlying belief space a…
DyDiff-VAE: A Dynamic Variational Framework for Information Diffusion Prediction
Ruijie Wang, Zijie Huang, Shengzhong Liu +7
This paper describes a novel diffusion model, DyDiff-VAE, for information diffusion prediction on social media. Given the initial content and a sequence of forwarding users, DyDiff…
Revisiting Over-smoothing in Deep GCNs
Chaoqi Yang, Ruijie Wang, Shuochao Yao +2
Oversmoothing has been assumed to be the major cause of performance drop in deep graph convolutional networks (GCNs). In this paper, we propose a new view that deep GCNs can actual…
Hierarchical Overlapping Belief Estimation by Structured Matrix Factorization
Chaoqi Yang, Jinyang Li, Ruijie Wang +6
Much work on social media opinion polarization focuses on a flat categorization of stances (or orthogonal beliefs) of different communities from media traces. We extend in this wor…