Multi-spatial Semantic Information Aggregation Network for 3D Human Motion Prediction
2025
In recent years, GCN-based methods have achieved great success in skeleton-based human motion prediction tasks due to the human body graph structure. However, existing methods leveraged single semantic...
Scalable graph attention-based instance selection via mini-batch sampling and hierarchical hashing
2025
Instance selection (IS) addresses the critical challenge of reducing dataset size while keeping informative characteristics, becoming increasingly important as datasets grow to millions of instances....
Multi-scale texture loss for CT denoising with GANs
2025
Generative Adversarial Networks (GANs) have proved as a powerful framework for denoising applications in medical imaging. However, GAN-based denoising algorithms still suffer from limitations in capturing...
Robust emotion recognition using hybrid Bayesian LSTM based on Laban movement analysis
2025
Emotion recognition has become increasingly significant in artificial intelligence; however, the impact of body movements on emotion interpretation remains under-explored. This paper presents a novel...
ADAP: Adaptive & Dynamic Arc Padding for predicting seam profiles in Multi-Layer-Multi-Pass robotic welding
2025
Welding thick metal plates using Multi-Layer-Multi-Pass (MLMP) techniques demands precise control over the weld seam profile as it evolves during the cooling process. In MLMP welding, typically executed...
AI-generated content in landscape architecture: A survey
2025
Landscape design is a complex process that requires designers to engage in intricate planning, analysis, and decision-making. This process involves the integration and reconstruction of science, art,...
Computer audition for healthcare: A survey on speech analysis
2025
Intelligent speech analysis (ISA) constitutes a significant component within the realm of computer audition (CA) technology. Speech, as a fundamental tool for human communication, not only conveys rich...
From tools to partners: How large language models are transforming urban planning
2025
Recent advances in large language models have transformed urban planning from passive tool-assisted workflows to active human–AI collaborative partnerships, enabling natural language-driven design generation,...
LLMKG＋: Systematically improving knowledge quality and coverage in KGs using LLMs – A case study in medical domain
2025
Knowledge graphs (KGs) encode structured information about real-world entities and their relations, supporting core NLP tasks such as question answering and retrieval. Existing LLM-based methods for...
Advancing AI for science: From the revolution of tools to the tools for revolution
2025
Scientific research is not a linear pipeline but a dynamic system built upon the ever-shifting interactions among three elements — research objects, tools, and researchers. And sustained progress depends...
Symbolic learning enables self-evolving agents
2025
The AI community has been exploring a pathway to artificial general intelligence (AGI) by developing “language agents”, which are complex large language models (LLMs) workflows involving both prompting...
Adaptive negative representations for graph contrastive learning
2024
Graph contrastive learning (GCL) has emerged as a promising paradigm for learning graph representations. Recently, the idea of hard negatives is introduced to GCL, which can provide more challenging...
How to generate popular post headlines on social media?
2024
Posts, as important containers of user-generated-content on social media, are of tremendous social influence and commercial value. As an integral component of post, headline has decisive influence on...
PM2.5 forecasting under distribution shift: A graph learning approach
2024
We present a new benchmark task for graph-based machine learning, aiming to predict future air quality (PM2.5 concentration) observed by a geographically distributed network of environmental sensors....
Label-aware debiased causal reasoning for Natural Language Inference
2024
Recently, researchers have argued that the impressive performance of Natural Language Inference (NLI) models is highly due to the spurious correlations existing in training data, which makes models...
Improving trajectory classification through Kramers–Moyal coefficients
2024
Trajectory classification focuses on predicting the class or category of a moving object based on its observed movement over time. The classification of trajectory data using classical approaches can...
Authorship style transfer with inverse transfer data augmentation
2024
Authorship style transfer aims to modify the style of neutral text to match the unique speaking or writing style of a particular individual. While Large Language Models (LLMs) present promising solutions,...
Relation-aware deep neural network enables more efficient biomedical knowledge acquisition from massive literature
2024
Biomedical knowledge is typically organized in a relational scheme, such as chemical-disease relation, gene-disease relation, and gene-pathway relation. Biomedical scientists heavily rely on search...
A study of natural robustness of deep reinforcement learning algorithms towards adversarial perturbations
2024
Deep reinforcement learning (DRL) has been shown to have numerous potential applications in the real world. However, DRL algorithms are still extremely sensitive to noise and adversarial perturbations,...
CellBoost: A pipeline for machine assisted annotation in neuroanatomy
2024
One of the important yet labor intensive tasks in neuroanatomy is the identification of select populations of cells. Current high-throughput techniques enable marking cells with histochemical fluorescent...
Large language models in law: A survey
2024
The advent of artificial intelligence (AI) has significantly impacted the traditional judicial industry. Moreover, recently, with the development of AI-generated content (AIGC), AI and law have found...
Publisher's Note
2024
