Shuai Wang

Modeling Review Spam Using Temporal Patterns and Co-bursting Behaviors

2016 · arXiv (Cornell University)

Online reviews play a crucial role in helping consumers evaluate and compare products and services. However, review hosting sites are often targeted by opinion spamming. In recent years, many such sites have put a great …

Bimodal Distribution and Co-Bursting in Review Spam Detection

2017

Online reviews play a crucial role in helping consumers evaluate and compare products and services. This critical importance of reviews also incentivizes fraudsters (or spammers) to write fake or spam reviews to secretly promote or …

Construction and Querying of Ancient Poet Knowledge Graph

2019 · Journal of Physics Conference Series

Abstract In recent years, with the development of knowledge graph techniques, how to construct various of knowledge graphs from different application domains has become important issues. This paper proposes a construction and querying approach for …

Detecting nondeterministic payment bugs in Ethereum smart contracts

2019 · Repository for Publications and Research Data (ETH Zurich)

The term “smart contracts” has become ubiquitous to describe an enormous number of programs uploaded to the popular Ethereum blockchain system. Despite rapid growth of the smart contract ecosystem, errors and exploitations have been constantly …

F^2ed-Learning: Good Fences Make Good Neighbors

2021 · arXiv (Cornell University)

In this paper, we present F^2ed-Learning, the first federated learning protocol simultaneously defending against both semi-honest server and Byzantine malicious clients. Using a robust mean estimator called FilterL2, F^2ed-Learning is the first FL protocol with …

Automated Side Channel Analysis of Media Software with Manifold Learning

2021 · arXiv (Cornell University)

The prosperous development of cloud computing and machine learning as a service has led to the widespread use of media software to process confidential media data. This paper explores an adversary's ability to launch side …

Visual and Phonological Feature Enhanced Siamese BERT for Chinese Spelling Error Correction

2022 · Applied Sciences

Chinese Spelling Check (CSC) aims to detect and correct spelling errors in Chinese. Most CSC models rely on human-defined confusion sets to narrow the search space, failing to resolve errors outside the confusion set. However, …

Optimized Bandwidth Allocation for MEC Server in Blockchain-Enabled IoT Networks

2022 · Scientific Programming

Powered by the development of the fifth-generation mobile communication technology (5G), the Internet of things (IoT) has been widely applied in people’s life. Due to the limitation of storage and computing power, the data transmission …

Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkit

2022 · arXiv (Cornell University)

Speaker modeling is essential for many related tasks, such as speaker recognition and speaker diarization. The dominant modeling approach is fixed-dimensional vector representation, i.e., speaker embedding. This paper introduces a research and production oriented speaker …

Feature Alignment and Uniformity for Test Time Adaptation

2023 · arXiv (Cornell University)

Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples. In this setting, the model can only access online unlabeled test samples and pre-trained models on the …

Precise and Generalized Robustness Certification for Neural Networks

2023 · arXiv (Cornell University)

The objective of neural network (NN) robustness certification is to determine if a NN changes its predictions when mutations are made to its inputs. While most certification research studies pixel-level or a few geometrical-level and …

AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data

2023 · arXiv (Cornell University)

Recently, the utilization of extensive open-sourced text data has significantly advanced the performance of text-based large language models (LLMs). However, the use of in-the-wild large-scale speech data in the speech technology community remains constrained. One …

Privacy-Preserving Federated Primal—Dual Learning for Nonconvex and Nonsmooth Problems With Model Sparsification

2024 · IEEE Internet of Things Journal

Federated learning (FL) has been recognized as a rapidly growing research area, where the model is trained over massively distributed clients under the orchestration of a parameter server (PS) without sharing clients’ data. This paper …

Integrated Sensing and Communication for Edge Inference with End-to-End Multi-View Fusion

2024 · arXiv (Cornell University)

Integrated sensing and communication (ISAC) is a promising solution to accelerate edge inference via the dual use of wireless signals. However, this paradigm needs to minimize the inference error and latency under ISAC co-functionality interference, …

Exploring Multi-Lingual Bias of Large Code Models in Code Generation

2024 · arXiv (Cornell University)

Code generation aims to synthesize code and fulfill functional requirements based on natural language (NL) specifications, which can greatly improve development efficiency. In the era of large language models (LLMs), large code models (LCMs) have …

Joint Input and Output Coordination for Class-Incremental Learning

2024 · arXiv (Cornell University)

Incremental learning is nontrivial due to severe catastrophic forgetting. Although storing a small amount of data on old tasks during incremental learning is a feasible solution, current strategies still do not 1) adequately address the …

Exploring Large Language Models in Healthcare: Insights into Corpora Sources, Customization Strategies, and Evaluation Metrics

2025 · arXiv (Cornell University)

This study reviewed the use of Large Language Models (LLMs) in healthcare, focusing on their training corpora, customization techniques, and evaluation metrics. A systematic search of studies from 2021 to 2024 identified 61 articles. Four …