8 citations · 23 across the 10 of their papers we have counts for
10 papers
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…
Decoding the Silent Majority: Inducing Belief Augmented Social Graph with Large Language Model for Response Forecasting
Chenkai Sun, Jinning Li, Yi R. Fung +4
Automatic response forecasting for news media plays a crucial role in enabling content producers to efficiently predict the impact of news releases and prevent unexpected negative…
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…
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…