Peng Wang

Protection of Location Privacy Based on Distributed Collaborative Recommendations

2016 · PLoS ONE

In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users' location. For this, we presented a new distributed collaborative recommendation strategy …

Shilling Attack Detection Based on Data Tracking

2018

Collaborative filtering recommender system is one of the most widely used recommender systems, while it is vulnerable to shilling attack because of its openness. In recent years, many shilling attack detection methods have been proposed …

Flash

2019

Offchain networks emerge as a promising solution to address the scalability challenge of blockchain. Participants make payments through offchain networks instead of committing transactions on-chain. Routing is critical to the performance of offchain networks. Existing …

To Balance or Not to Balance: An Embarrassingly Simple Approach for Learning with Long-Tailed Distributions.

2019 · arXiv (Cornell University)

Real-world visual data often exhibits a long-tailed distribution, where some ''head'' classes have a large number of samples, yet only a few samples are available for ''tail'' classes. Such imbalanced distribution causes a great challenge …

Dynamic Prediction of the Thermal Nonlinear Process Based on Deep Hybrid Neural Network

2020 · E3S Web of Conferences

Nonlinear system prediction plays an important role in the practical thermal process, and deep learning algorithm is now popular in nonlinear dynamic system modeling because of its powerful learning ability. In this paper, the dynamic …

High-Performance Password Recovery Hardware Going From GPU to Hybrid CPU-FPGA Platform

2020 · IEEE Consumer Electronics Magazine

Password recovery has a high demand for computing power. This article aims to provide an overview of password recovery systems, including the basic concepts of password recovery, the popular hardware platforms ranging from the traditional …

Deep learning to predict the modulation schemes of real OFDM signals

2021

The goal of this effort is to train Deep Learning (DL) models using synthetic Orthogonal Frequency-Division Multiplexing (OFDM) datasets to predict the modulation schemes of real OFDM signals without transfer learning. To facilitate our study, …

Rooftop photovoltaics potential assessment：A framework to integrate technological, economic, environmental and social benefit

2020 · E3S Web of Conferences

Buildings have a significant impact on global and local energy demand and climate change. Consequently, the issue of photovoltaic (PV) potential assessment of building roofs have been extensively studied. Although studies have adopted different methods …

Client Scheduling in Wireless Federated Learning Based on Channel and Learning Qualities

2022 · IEEE Wireless Communications Letters

Federated learning (FL) emerges as a distributed training method in the Internet of Things (IoT), allowing participating clients to use their local data to train local models and upload parameters for global model aggregation after …

Knowledge Rumination for Pre-trained Language Models

2023 · arXiv (Cornell University)

Previous studies have revealed that vanilla pre-trained language models (PLMs) lack the capacity to handle knowledge-intensive NLP tasks alone; thus, several works have attempted to integrate external knowledge into PLMs. However, despite the promising outcome, …

PasCore: A Chinese Overlapping Relation Extraction Model Based on Global Pointer Annotation Strategy

2023

Recent work for extracting relations from texts has achieved excellent performance. However, existing studies mainly focus on simple relation extraction, these methods perform not well on overlapping triple problem because the tags of shared entities …

Pre-training with Large Language Model-based Document Expansion for Dense Passage Retrieval

2023 · arXiv (Cornell University)

In this paper, we systematically study the potential of pre-training with Large Language Model(LLM)-based document expansion for dense passage retrieval. Concretely, we leverage the capabilities of LLMs for document expansion, i.e. query generation, and effectively …

Weakly Supervised Video Anomaly Detection Based on Cross-Batch Clustering Guidance

2023

Weakly supervised video anomaly detection (WSVAD) is a challenging task since only video-level labels are available for training. In previous studies, the discriminative power of the learned features is not strong enough, and the data …

A Trustworthy and Consistent Blockchain Oracle Scheme for Industrial Internet of Things

2023 · arXiv (Cornell University)

Blockchain provides decentralization and trustlessness features for the Industrial Internet of Things (IIoT), which expands the application scenarios of IIoT. To address the problem that the blockchain cannot actively obtain off-chain data, the blockchain oracle …

Open-Vocabulary Video Anomaly Detection

2023 · arXiv (Cornell University)

Video anomaly detection (VAD) with weak supervision has achieved remarkable performance in utilizing video-level labels to discriminate whether a video frame is normal or abnormal. However, current approaches are inherently limited to a closed-set setting …

FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models

2023 · arXiv (Cornell University)

The effective assessment of the instruction-following ability of large language models (LLMs) is of paramount importance. A model that cannot adhere to human instructions might be not able to provide reliable and helpful responses. In …

Electronic Warfare UAV Combat Effectiveness Evaluation Based on GrC-Elm

2023

To increase the combat capability of Electronic Warfare Unmanned Air Vehicle (EWUAV), a combat effectiveness evaluation method is proposed based on Granular Computing (GrC) and modified Extreme Learning Machine (ELM). In the method, the combat …

Learning Social Graph for Inactive User Recommendation

2024 · arXiv (Cornell University)

Social relations have been widely incorporated into recommender systems to alleviate data sparsity problem. However, raw social relations don't always benefit recommendation due to their inferior quality and insufficient quantity, especially for inactive users, whose …

Efficient Smart Contract Mechanism for New Energy Vehicle Supply Chain Based on Alliance Chain

2024 · SAE International journal of sustainable transportation, energy, environment & policy

<div>Supply chain management is key to industry efficiency, while information security and transparency are at the core of operations management. Blockchain technology shows great potential in this regard and can effectively make up for existing …

Knowledge Mechanisms in Large Language Models: A Survey and Perspective

2024

Mengru Wang, Yunzhi Yao, Ziwen Xu, Shuofei Qiao, Shumin Deng, Peng Wang, Xiang Chen, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Huajun Chen, Ningyu Zhang. Findings of the Association for Computational Linguistics: EMNLP 2024. …

Geochemical-integrated machine learning approach predicts the distribution of cadmium speciation in European and Chinese topsoils

2025 · Communications Earth & Environment

Evaluating heavy metals bioavailable is crucial for comprehensive soil contamination assessment but challenging at large scales due to complex and resource-intensive analytical procedures, and the amount of dissolved metal in soils represents the relative solubility …

Understanding Generalization in Diffusion Distillation via Probability Flow Distance

2025 · ArXiv.org

Diffusion distillation provides an effective approach for learning lightweight and few-steps diffusion models with efficient generation. However, evaluating their generalization remains challenging: theoretical metrics are often impractical for high-dimensional data, while no practical metrics rigorously …

Multi-Tenant Deployment with Anomaly Isolation in Public Clouds

2025

Cloud vendors provide network services to tenants through shared service nodes, which may cause the abnormal traffic of one tenant to affect others. Deploying auxiliary systems such as firewalls will reduce the frequency of abnormal …

Research on Deep Learning-Based Identification Methods for Geological Interface Types and Their Application in Mineral Exploration Prediction—A Case Study of the Gouli Region in Qinghai, China

2025 · Minerals

Geological interfaces are crucial elements governing deposit formation, such as silica–calcium surfaces, intrusive contact interfaces, and unconformities can serve as key symbols for mineral exploration prediction. Geological maps provide relatively detailed representations of primary geological …