Optimal RoPE extension via Bayesian Optimization for training-free length generalization
2025
Transformers are designed to process input of variable length without resource constraints. However, their performance significantly deteriorates when the input surpasses a threshold slightly larger...
Share article
Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: A comprehensive review of COVID-19 detection
2025
This study presents a comprehensive review of the potential of multimodal deep learning (DL) in medical diagnosis, using COVID-19 as a case example. Motivated by the success of artificial intelligence...
Share article
ChatLLM network: More brains, more intelligence
2025
Dialogue-based language models mark a huge milestone in the field of artificial intelligence, by their impressive ability to interact with users, as well as a series of challenging tasks prompted by...
Share article
Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks
2025
The accelerated progress of artificial intelligence (AI) has popularized deep learning models across various domains, yet their inherent opacity poses challenges, particularly in critical fields like...
Share article
Methodologies and their comparison in complex compound aspect-based sentiment analysis: A survey
2025
Sentiment analysis as a part of natural language processing (NLP) has received much attention following the demand to understand people’s opinions. Aspect-based sentiment analysis (ABSA) is a fine-grained...
Share article
FedGPA: Federated Learning with Global Personalized Aggregation
2025
A significant challenge in Federated Learning (FL) is addressing the heterogeneity of local data distribution across clients. Personalized Federated Learning (PFL), an emerging method aimed at overcoming...
Share article
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...
Share article
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...
Share article
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....
Share article
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...
Share article
Boosting graph search with attention network for solving the general orienteering problem
2024
Recently, several studies explore to use neural networks(NNs) to solve different routing problems, which is an auspicious direction. These studies usually design an encoder–decoder based framework that...
Share article
An ecosystem for personal knowledge graphs: A survey and research roadmap
2024
This paper presents an ecosystem for personal knowledge graphs (PKGs), commonly defined as resources of structured information about entities related to an individual, their attributes, and the relations...
Share article
Few-shot Named Entity Recognition via encoder and class intervention
2024
In the real world, the large and complex nature of text increases the difficulty of tagging and results in a limited amount of tagged text. Few-shot Named Entity Recognition(NER) only uses a small amount...
Share article
CPT: Colorful Prompt Tuning for pre-trained vision-language models
2024
Vision-Language Pre-training (VLP) models have shown promising capabilities in grounding natural language in image data, facilitating a broad range of cross-modal tasks. However, we note that there...
Share article
Enhancing neural network classification using fractional-order activation functions
2024
In this paper, a series of novel activation functions is presented, which is derived using the improved Riemann–Liouville conformable fractional derivative (RLCFD). This study investigates the use of...
Share article
GPT understands, too
2024
Prompting a pretrained language model with natural language patterns has been proved effective for natural language understanding (NLU). However, our preliminary study reveals that manual discrete prompts...
Share article
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...
Share article
MindLLM: Lightweight large language model pre-training, evaluation and domain application
2024
Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial...
Share article
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,...
Share article
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...
Share article
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,...
Share article
Wave2Graph: Integrating spectral features and correlations for graph-based learning in sound waves
2024
This paper investigates a novel graph-based representation of sound waves inspired by the physical phenomenon of correlated vibrations. We propose a Wave2Graph framework for integrating multiple acoustic...
Share article
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...
Share article
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...
Share article
Generating graph perturbations to enhance the generalization of GNNs
2024
Graph neural networks (GNNs) have become the standard approach for performing machine learning on graphs. Such models need large amounts of training data, however, in several graph classification and...
Share article
