Wei Wang

A Location-Based Personalized Focused Search System for Physically Challenged People

2015 · Advances in computer science research

Physically Challenged people are a special part of society, which need more care. Because of the huge differences in physical conditions, qualities of life, locations and personal backgrounds, there exists a lot of challenges for …

End-to-end encrypted traffic classification with one-dimensional convolution neural networks

2017

Traffic classification plays an important and basic role in network management and cyberspace security. With the widespread use of encryption techniques in network applications, encrypted traffic has recently become a great challenge for the traditional …

Graph summarization for source selection of querying over Linked Open Data

2017 · 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)

How to query Linked Open Data effectively is a challenge due to large amounts of distributed datasets and lacking of overall information about it. Source selection that filters query-relevant datasets is a challenge. We propose …

The Application of Jigsaw Teaching Mode in Medical Literature Retrieval

2018 · DEStech Transactions on Social Science Education and Human Science

The purpose of this study is to apply the Jigsaw teaching mode into the medical literature retrieval and discuss the effect of the new teaching one. According to the Jigsaw learning mode, the students are …

Multipartite Quantum Entanglement and Quantum Correlation from cascaded Four-wave Mixing Processes with spatial multiplexing

2018 · Conference on Lasers and Electro-Optics

Four-wave mixing (FWM) process with spatial multiplexing is a promising candidate for building quantum network. We experimentally investigate multipartite quantum correlation and theoretically study multipartite quantum entanglement from cascaded FWM processes.

Automatic Search of Bit-Based Division Property for ARX Ciphers and Word-Based Division Property.

2017 · IACR Cryptology ePrint Archive

Division property is a generalized integral property proposed by Todo at Eurocrypt 2015. Previous tools for automatic searching are mainly based on the Mixed Integer Linear Programming (MILP) method and trace the division property propagation …

Multi-Source Cross-Lingual Model Transfer: Learning What to Share

2019

Modern NLP applications have enjoyed a great boost utilizing neural networks models. Such deep neural models, however, are not applicable to most human languages due to the lack of annotated training data for various NLP …

MArk: Exploiting Cloud Services for Cost-Effective, SLO-Aware Machine Learning Inference Serving.

2019 · Rare & Special e-Zone (The Hong Kong University of Science and Technology)

The advances of Machine Learning (ML) have sparked a growing demand of ML-as-a-Service: developers train ML models and publish them in the cloud as online services to provide low-latency inference at scale. The key challenge …

Abnormal Client Behavior Detection in Federated Learning

2019 · arXiv (Cornell University)

In federated learning systems, clients are autonomous in that their behaviors are not fully governed by the server. Consequently, a client may intentionally or unintentionally deviate from the prescribed course of federated model training, resulting …

Computer-aided Detection of Squamous Carcinoma of the Cervix in Whole Slide Images

2019 · arXiv (Cornell University)

Goal: Squamous cell carcinoma of cervix is one of the most prevalent cancer worldwide in females. Traditionally, the most indispensable diagnosis of cervix squamous carcinoma is histopathological assessment which is achieved under microscope by pathologist. …

Partially Shared Adversarial Learning For Semi-supervised Multi-platform User Identity Linkage

2019

With the increasing popularity and diversity of social media, users tend to join multiple social platforms to enjoy different types of services. User identity linkage, which aims to link identical identities across different social platforms, …

Vetting Security and Privacy of Global COVID-19 Contact Tracing Applications

2020 · arXiv (Cornell University)

The rapid spread of COVID-19 has made traditional manual contact tracing to identify potential persons in close physical proximity to an known infected person challenging. Hence, a number of public health authorities have experimented with …

BatchCrypt: Efficient homomorphic encryption for cross-silo federated learning

2020 · Rare & Special e-Zone (The Hong Kong University of Science and Technology)

Cross-silo federated learning (FL) enables organizations (e.g., financial or medical) to collaboratively train a machine learning model by aggregating local gradient updates from each client without sharing privacy-sensitive data. To ensure no update is revealed …

IHF: Industrial High Frequency Operation Queue Discovery Algorithm

2020

When using traditional PrefixSpan algorithm to complete industrial Internet high-frequency operation sequence mining tasks, there are problems such as low efficiency and disordered output results. Based on the PrefixSpan algorithm, we propose an IHF algorithm …

A Multipulse Radar Signal Recognition Approach via HRF‐Net Deep Learning Models

2021 · Computational Intelligence and Neuroscience

In the field of electronic countermeasure, the recognition of radar signals is extremely important. This paper uses GNU Radio and Universal Software Radio Peripherals to generate 10 classes of close-to-real multipulse radar signals, namely, Barker, …

Learning to Copy Coherent Knowledge for Response Generation

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

Knowledge-driven dialog has shown remarkable performance to alleviate the problem of generating uninformative responses in the dialog system. However, incorporating knowledge coherently and accurately into response generation is still far from being solved. Previous works …

ADKGN: An Attentive Dynamic Knowledge Graph Network for Sequential Recommendation

2021

Sequential recommendation system's goal is to predict users' next actions based on their historical behavior sequences. As we know, more recent items have a larger impact than the previous ones. Meanwhile, modeling users' current interests …

Revisit Systematic Generalization via Meaningful Learning

2020 · arXiv (Cornell University)

Humans can systematically generalize to novel compositions of existing concepts. Recent studies argue that neural networks appear inherently ineffective in such cognitive capacity, leading to a pessimistic view and a lack of attention to optimistic …

Improving Empathetic Response Generation by Recognizing Emotion Cause in Conversations

2021

Current approaches to empathetic response generation focus on learning a model to predict an emotion label and generate a response based on this label, and have achieved promising results. However, the emotion cause, an essential …

Old Wine in A New Bottle: A Homogeneous Fraud Sites Discovery Framework

2021 · 2021 7th International Conference on Computer and Communications (ICCC)

Internet fraud is a serious threat to the normal order of the Internet, endangering the personal and property safety of its users. Nowadays in China, the most rampant forms of Internet fraud include false winning, …

Second‐order asymmetric convolution network for breast cancer histopathology image classification

2022 · Journal of Biophotonics

Recently, convolutional neural networks (CNNs) have been widely utilized for breast cancer histopathology image classification. Besides, research works have also convinced that deep high-order statistic models obviously outperform corresponding first-order counterparts in vision tasks. Inspired …

Detecting Overlapping Community Structures with PCA Technology and Member Index

2016

The community structures reflect the basic property of social networks and the key point is to detect them effectively. Traditional solutions such as the nonnegative matrix factorization approach have a high time and space complexity, …

Translation-Based Implicit Annotation Projection for Zero-Shot Cross-Lingual Event Argument Extraction

2022 · Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Zero-shot cross-lingual event argument extraction (EAE) is a challenging yet practical problem in Information Extraction. Most previous works heavily rely on external structured linguistic features, which are not easily accessible in real-world scenarios. This paper …

Language-agnostic BERT Sentence Embedding

2020 · arXiv (Cornell University)

While BERT is an effective method for learning monolingual sentence embeddings for semantic similarity and embedding based transfer learning (Reimers and Gurevych, 2019), BERT based cross-lingual sentence embeddings have yet to be explored. We systematically …

Long bet will lose: demystifying seemingly fair gambling via two-armed Futurity bandit

2022 · arXiv (Cornell University)

No matter how much some gamblers occasionally win, as long as they continue to gamble, sooner or later they will lose more to the casino, which is the so-called long bet will lose. Our results …

G<scp>otta</scp>: Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation

2023 · Society for Industrial and Applied Mathematics eBooks

Few-shot question answering (QA) aims at precisely discovering answers to a set of questions from context passages while only a few training samples are available. Although existing studies have made some progress and can usually …

Beyond Phish: Toward Detecting Fraudulent e-Commerce Websites at Scale

2023

Despite recent advancements in malicious website detection and phishing mitigation, the security ecosystem has paid little attention to Fraudulent e-Commerce Websites (FCWs), such as fraudulent shopping websites, fake charities, and cryptocurrency scam websites. Even worse, …

A method for military entity relation extraction based on two-level attention mechanism

2023 · IET conference proceedings.

To address the challenge of limited training data for entity relation extraction in the military domain, training instances within this domain are automatically generated employing the distant supervision method. Subsequently, to mitigate the problem of …

Fairness Oriented Spectrum Auction for Blockchain-assisted Dynamic Spectrum Sharing

2023

Leveraging the unique characteristics of blockchain, secure and efficient dynamic spectrum sharing (DSS) can be achieved, which has been regarded as a promising solution to meet the spectrum requirement in future wireless communication systems. However, …

Golgi

2023

This paper introduces Golgi, a novel scheduling system designed for serverless functions, with the goal of minimizing resource provisioning costs while meeting the function latency requirements. To achieve this, Golgi judiciously over-commits functions based on …

Research on Secure Communication Model for Station Based on Multi-Factor Identity Authentication

2023

With the advancement of communication technology, the diversity and number of terminal devices in the station communication network continue to grow, and the traditional single authentication method has been difficult to meet the needs of …

Learning to Edit: Aligning LLMs with Knowledge Editing

2024 · arXiv (Cornell University)

Knowledge editing techniques, aiming to efficiently modify a minor proportion of knowledge in large language models (LLMs) without negatively impacting performance across other inputs, have garnered widespread attention. However, existing methods predominantly rely on memorizing …

Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI

2024 · IEEE Transactions on Biomedical Engineering

Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in the brain and is widely used for brain disorder analysis. Previous studies focus on extracting fMRI representations using machine/deep learning methods, but these …

Fast Detection Algorithm for Equal Length Frame Signals Based on Pattern Matching

2023

Aiming at the problems of slow speed and low efficiency of the existing signal frame header detection algorithm in the field of cooperative communication, a pattern matching based frame header detection algorithm is proposed. The …

Improved Bounds for Pure Private Agnostic Learning: Item-Level and User-Level Privacy

2024 · arXiv (Cornell University)

Machine Learning has made remarkable progress in a wide range of fields. In many scenarios, learning is performed on datasets involving sensitive information, in which privacy protection is essential for learning algorithms. In this work, …

Hierarchical Federated Edge Learning With Adaptive Clustering in Internet of Things

2024 · IEEE Internet of Things Journal

The expansion of the Internet of Things (IoT) has led to a significant surge in data flow over edge networks, posing substantial challenges to data mining and management. While federated edge learning (FEEL) effectively accomplishes …

How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition

2024

Guanting Dong, Hongyi Yuan, Keming Lu, Chengpeng Li, Mingfeng Xue, Dayiheng Liu, Wei Wang, Zheng Yuan, Chang Zhou, Jingren Zhou. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long …

Four overlooked errors in ROC analysis: how to prevent and avoid

2024 · BMJ Evidence-Based Medicine

Diagnostic tests are frequently applied within clinical practice to assist with disease diagnosis, differential diagnosis, disease grading and prognosis evaluation. Receiver operating characteristic (ROC) curve analysis is one common approach for analysing discriminative performance of …

Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models

2024

Parameter-Efficient Fine-Tuning (PEFT) methods have gained significant popularity for adapting pre-trained Large Language Models (LLMs) to downstream tasks, primarily due to their potential to significantly reduce memory and computational overheads.However, a common limitation in most …

A universal adversarial perturbations generation method based on feature aggregation

2024

Universal Adversarial Perturbations (UAP) is a sample-independent adversarial attack that can be added to all natural samples to change most of their predictive labels. Aiming at the problems of the existing universal adversarial attack methods …

Adaptive Zero-Crossing Regulation Algorithm for Multi-Winding Parallel-Wound Distribution TransFormers

2024

Transformer losses significantly impact grid losses. The adaptive load distribution transformer can adjust voltage taps and automatically switch operating modes based on system conditions without disconnecting the load. This reduces no-load losses, cutting grid losses …

Security Attacks on LLM-based Code Completion Tools

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

The rapid development of large language models (LLMs) has significantly advanced code completion capabilities, giving rise to a new generation of LLM-based Code Completion Tools (LCCTs). Unlike general-purpose LLMs, these tools possess unique workflows, integrating …

Study on Exercise Intensity Level and Heart Rate Standard for Promoting Physical Health of Middle School Students

2025 · Education Reform and Development

Since the introduction of the “Physical Education and Health Curriculum Standards for Compulsory Education (2022 edition),” which emphasized the importance of physical education intensity, there has been scholarly debate and discussion among experts and physical …

UnifiedMLLM: Enabling Unified Representation for Multi-modal Multi-tasks With Large Language Model

2025

Significant advancements has recently been achieved in the field of multi-modal large language models (MLLMs), demonstrating their remarkable capabilities in understanding and reasoning across diverse tasks.However, these models are often trained for specific tasks and …

Interaction Privacy Vulnerability in Federated Recommendation and Lossless Countermeasure

2025 · ACM Transactions on Information Systems

Federated Recommendation (FedRec) systems are recognized as privacy-preserving solutions for collaboratively training recommender models without sharing users’ private data. However, recent studies have revealed that FedRec systems are vulnerable to interaction-level membership inference attacks. In …

GradPower: Powering Gradients for Faster Language Model Pre-Training

2025 · ArXiv.org

We propose GradPower, a lightweight gradient-transformation technique for accelerating language model pre-training. Given a gradient vector $g=(g_i)_i$, GradPower first applies the elementwise sign-power transformation: $φ_p(g)=({\rm sign}(g_i)|g_i|^p)_{i}$ for a fixed $p&gt;0$, and then feeds the transformed …

From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling

2025 · arXiv (Cornell University)

Recent advancements in improving the reasoning capabilities of Large Language Models have underscored the efficacy of Process Reward Models (PRMs) in addressing intermediate errors through structured feedback mechanisms. This study analyzes PRMs from multiple perspectives, …

Do Theory of Mind Benchmarks Need Explicit Human-like Reasoning in Language Models?

2025 · arXiv (Cornell University)

Theory of Mind (ToM), the ability to attribute mental states to others, is fundamental for human social intelligence and a critical capability for advanced Artificial Intelligence. Recent advancements in Large Language Models (LLMs) have shown …

Fuzzy C4.5 Decision Tree Model for Effect Analysis and Optimization of College Physical Education Courses

2025 · Journal of Circuits Systems and Computers

In studying college physical education course effect analysis and optimization, the traditional C4.5 algorithm has weak processing capabilities for fuzzy data. It is prone to imprecise decision tree nodes and cannot effectively handle the complex …

Novel Global Network Signal Station Sorting Algorithm Based on Hop Describe Word (HDW) and Clustering-Assisted Temporal Sorting

2026 · Mathematics

To address the sorting challenge of multiple stations and multiple networking modes (networks with inconsistent features and networks with similar features but asynchrony) in complex electromagnetic environments, this paper proposes a full-network station sorting algorithm …

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

2016 · arXiv (Cornell University)

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based translation systems. Unfortunately, NMT systems are known to be computationally expensive …

KBQA

2017 · Proceedings of the VLDB Endowment

Question answering (QA) has become a popular way for humans to access billion-scale knowledge bases. Unlike web search, QA over a knowledge base gives out accurate and concise results, provided that natural language questions can …

Multi-Granularity Hierarchical Attention Fusion Networks for Reading Comprehension and Question Answering

2018

This paper describes a novel hierarchical attention network for reading comprehension style question answering, which aims to answer questions for a given narrative paragraph. In the proposed method, attention and fusion are conducted horizontally and …

VOPRec: Vector Representation Learning of Papers with Text Information and Structural Identity for Recommendation

2018 · IEEE Transactions on Emerging Topics in Computing

Finding relevant papers is a non-trivial problem for scholars due to the tremendous amount of academic information in the era of scholarly big data. Scientific paper recommendation systems have been developed to solve such problem …

Learning Gender-Neutral Word Embeddings

2018

Word embedding models have become a fundamental component in a wide range of Natural Language Processing (NLP) applications. However, embeddings trained on human-generated corpora have been demonstrated to inherit strong gender stereotypes that reflect social …

A Knowledge-Enhanced Deep Recommendation Framework Incorporating GAN-Based Models

2018

Although many researchers of recommender systems have noted that encoding user-item interactions based on DNNs promotes the performance of collaborative filtering, they ignore that embedding the latent features collected from external sources, e.g., knowledge graphs …

Denoising Neural Machine Translation Training with Trusted Data and Online Data Selection

2018

Measuring domain relevance of data and identifying or selecting well-fit domain data for machine translation (MT) is a well-studied topic, but denoising is not yet. Denoising is concerned with a different type of data quality …

Language-agnostic BERT Sentence Embedding

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

While BERT is an effective method for learning monolingual sentence embeddings for semantic similarity and embedding based transfer learning (Reimers and Gurevych, 2019), BERT based cross-lingual sentence embeddings have yet to be explored. We systematically …