Junping Du
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View article: Achieving Empirical Potential Efficiency with DFT Accuracy: A Neuroevolution Potential for the $α$-Fe--C--H System
Achieving Empirical Potential Efficiency with DFT Accuracy: A Neuroevolution Potential for the $α$-Fe--C--H System Open
A neuroevolution potential (NEP) for the ternary $α$-Fe--C--H system was developed based on a database generated from spin-polarized density functional theory (DFT) calculations, achieving empirical potential efficiency with DFT accuracy. …
View article: ELMM: Efficient Lightweight Multimodal Large Language Models for Multimodal Knowledge Graph Completion
ELMM: Efficient Lightweight Multimodal Large Language Models for Multimodal Knowledge Graph Completion Open
Multimodal Knowledge Graphs (MKGs) extend traditional knowledge graphs by incorporating visual and textual modalities, enabling richer and more expressive entity representations. However, existing MKGs often suffer from incompleteness, whi…
View article: Unified Representation Learning for Multi-Intent Diversity and Behavioral Uncertainty in Recommender Systems
Unified Representation Learning for Multi-Intent Diversity and Behavioral Uncertainty in Recommender Systems Open
This paper addresses the challenge of jointly modeling user intent diversity and behavioral uncertainty in recommender systems. A unified representation learning framework is proposed. The framework builds a multi-intent representation mod…
View article: Scalable Multi-Party Collaborative Data Mining Based on Federated Learning
Scalable Multi-Party Collaborative Data Mining Based on Federated Learning Open
This paper proposes a federated learning-based method for multi-party collaborative mining and heterogeneous data source fusion. The goal is to address the shortcomings of traditional centralized learning in data privacy protection and cro…
View article: Deriving Early Citrus Fruit Yield Estimation by Combining Multiple Growing Period Data and Improved YOLOv8 Modeling
Deriving Early Citrus Fruit Yield Estimation by Combining Multiple Growing Period Data and Improved YOLOv8 Modeling Open
Early crop yield prediction is a major challenge in precision agriculture, and efficient and rapid yield prediction is highly important for sustainable fruit production. The accurate detection of major fruit characteristics, including flow…
View article: Privacy-Enhanced Federated Learning for Distributed Heterogeneous Data
Privacy-Enhanced Federated Learning for Distributed Heterogeneous Data Open
This paper proposes a heterogeneous federated learning method for collaborative modeling, addressing data heterogeneity and privacy protection in multi-center scenarios. Based on the traditional federated learning framework, the method int…
View article: Kongzi: A Historical Large Language Model with Fact Enhancement
Kongzi: A Historical Large Language Model with Fact Enhancement Open
The capabilities of the latest large language models (LLMs) have been extended from pure natural language understanding to complex reasoning tasks. However, current reasoning models often exhibit factual inaccuracies in longer reasoning ch…
View article: Delay of airfoil stall via bio-inspired herringbone groove array
Delay of airfoil stall via bio-inspired herringbone groove array Open
View article: Improving Harmful Text Detection with Joint Retrieval and External Knowledge
Improving Harmful Text Detection with Joint Retrieval and External Knowledge Open
Harmful text detection has become a crucial task in the development and deployment of large language models, especially as AI-generated content continues to expand across digital platforms. This study proposes a joint retrieval framework t…
View article: IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web
IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web Open
View article: DependEval: Benchmarking LLMs for Repository Dependency Understanding
DependEval: Benchmarking LLMs for Repository Dependency Understanding Open
View article: IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web
IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web Open
Recently advancements in large multimodal models have led to significant strides in image comprehension capabilities. Despite these advancements, there is a lack of the robust benchmark specifically for assessing the Image-to-Web conversio…
View article: Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction
Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction Open
Asynchronous federated learning (AFL) is a distributed machine learning technique that allows multiple devices to collaboratively train deep learning models without sharing local data. However, AFL suffers from low efficiency due to poor c…
View article: Self-Supervised Multi-Modal Knowledge Graph Contrastive Hashing for Cross-Modal Search
Self-Supervised Multi-Modal Knowledge Graph Contrastive Hashing for Cross-Modal Search Open
Deep cross-modal hashing technology provides an effective and efficient cross-modal unified representation learning solution for cross-modal search. However, the existing methods neglect the implicit fine-grained multimodal knowledge relat…
View article: Relation Extraction Model Based on Semantic Enhancement Mechanism
Relation Extraction Model Based on Semantic Enhancement Mechanism Open
Relational extraction is one of the basic tasks related to information extraction in the field of natural language processing, and is an important link and core task in the fields of information extraction, natural language understanding, …
View article: Topic model based on co-occurrence word networks for unbalanced short text datasets
Topic model based on co-occurrence word networks for unbalanced short text datasets Open
We propose a straightforward solution for detecting scarce topics in unbalanced short-text datasets. Our approach, named CWUTM (Topic model based on co-occurrence word networks for unbalanced short text datasets), Our approach addresses th…
View article: Epidemic Decision-making System Based Federated Reinforcement Learning
Epidemic Decision-making System Based Federated Reinforcement Learning Open
Epidemic decision-making can effectively help the government to comprehensively consider public security and economic development to respond to public health and safety emergencies. Epidemic decision-making can effectively help the governm…
View article: Dynamic Fair Federated Learning Based on Reinforcement Learning
Dynamic Fair Federated Learning Based on Reinforcement Learning Open
Federated learning enables a collaborative training and optimization of global models among a group of devices without sharing local data samples. However, the heterogeneity of data in federated learning can lead to unfair representation o…
View article: Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation Open
The heterogeneous information network (HIN), which contains rich semantics depicted by meta-paths, has emerged as a potent tool for mitigating data sparsity in recommender systems. Existing HIN-based recommender systems operate under the a…
View article: Reinforcement Federated Learning Method Based on Adaptive OPTICS Clustering
Reinforcement Federated Learning Method Based on Adaptive OPTICS Clustering Open
Federated learning is a distributed machine learning technology, which realizes the balance between data privacy protection and data sharing computing. To protect data privacy, feder-ated learning learns shared models by locally executing …
View article: InfoMax Classification-Enhanced Learnable Network for Few-Shot Node Classification
InfoMax Classification-Enhanced Learnable Network for Few-Shot Node Classification Open
Graph neural networks have a wide range of applications, such as citation networks, social networks, and knowledge graphs. Among various graph analyses, node classification has garnered much attention. While many of the recent network embe…
View article: Identification of adaptor proteins by incorporating deep learning and PSSM profiles
Identification of adaptor proteins by incorporating deep learning and PSSM profiles Open
Adaptor proteins, also known as signal transduction adaptor proteins, are important proteins in signal transduction pathways, and play a role in connecting signal proteins for signal transduction between cells. Studies have shown that adap…
View article: Cross-modal Search Method of Technology Video based on Adversarial Learning and Feature Fusion
Cross-modal Search Method of Technology Video based on Adversarial Learning and Feature Fusion Open
Technology videos contain rich multi-modal information. In cross-modal information search, the data features of different modalities cannot be compared directly, so the semantic gap between different modalities is a key problem that needs …
View article: Scientific and Technological News Recommendation Based on Knowledge Graph with User Perception
Scientific and Technological News Recommendation Based on Knowledge Graph with User Perception Open
Existing research usually utilizes side information such as social network or item attributes to improve the performance of collaborative filtering-based recommender systems. In this paper, the knowledge graph with user perception is used …
View article: CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer
CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer Open
In this paper, we aim to devise a universally versatile style transfer method capable of performing artistic, photo-realistic, and video style transfer jointly, without seeing videos during training. Previous single-frame methods assume a …
View article: Aspect-Based Sentiment Analysis using Local Context Focus Mechanism with DeBERTa
Aspect-Based Sentiment Analysis using Local Context Focus Mechanism with DeBERTa Open
Text sentiment analysis, also known as opinion mining, is research on the calculation of people's views, evaluations, attitude and emotions expressed by entities. Text sentiment analysis can be divided into text-level sentiment analysis, s…
View article: A Rare Topic Discovery Model for Short Texts Based on Co-occurrence word Network
A Rare Topic Discovery Model for Short Texts Based on Co-occurrence word Network Open
We provide a simple and general solution for the discovery of scarce topics in unbalanced short-text datasets, namely, a word co-occurrence network-based model CWIBTD, which can simultaneously address the sparsity and unbalance of short-te…
View article: Chinese Word Sense Embedding with SememeWSD and Synonym Set
Chinese Word Sense Embedding with SememeWSD and Synonym Set Open
Word embedding is a fundamental natural language processing task which can learn feature of words. However, most word embedding methods assign only one vector to a word, even if polysemous words have multi-senses. To address this limitatio…
View article: Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency
Social Network Community Detection Based on Textual Content Similarity and Sentimental Tendency Open
Shared travel has gradually become one of the hot topics discussed on social networking platforms such as Micro Blog. In a timely manner, deeper network community detection on the evaluation content of shared travel in social networks can …
View article: Sentiment Analysis of Online Travel Reviews Based on Capsule Network and Sentiment Lexicon
Sentiment Analysis of Online Travel Reviews Based on Capsule Network and Sentiment Lexicon Open
With the development of online travel services, it has great application prospects to timely mine users' evaluation emotions for travel services and use them as indicators to guide the improvement of online travel service quality. In this …