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- Is a Large Language Model a Good Annotator for Event Extraction?84
This paper introduces an innovative approach where Large Language Models are employed as expert annotators for event extraction, and strategically include sample data from the training dataset in the prompt as a reference, ensuring alignment between the data distribution of LLM-generated samples and that of the benchmark dataset.
- On neural networks and learning systems for business computing84
Different applications of artificial intelligence technologies in several domains of business administration, including finance, retail industry, manufacturing industry, and enterprise management are summarized and it is concluded that the rapid development of artificial Intelligence will show its great impact on more fields.
- Guaranteeing Data Privacy in Federated Unlearning With Dynamic User Participation28
This work systematically explores the integration of SecAgg protocols within the most widely used federated unlearning scheme, which is based on clustering, to establish a privacy-preserving FU framework, aimed at ensuring privacy while effectively managing dynamic user participation.
- KnowFormer: Revisiting Transformers for Knowledge Graph Reasoning12
This paper revisits the application of transformers for knowledge graph reasoning to address the constraints faced by path-based methods and proposes a novel method KnowFormer, which utilizes a transformer architecture to perform reasoning on knowledge graphs from the message-passing perspective.
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- A dataset for exploring gaze behaviors in text summarization9
This paper provides a dataset covering 50 individuals' gaze behaviors collected by a high-accurate eye tracking device when they are reading 100 articles and composing the corresponding summaries for each article, and provides sample use cases of the dataset.
- An Automatic Classification and Clustering Algorithm for Online Learning Goals Based on Cognitive Thinking9
To improve the learning effect of online learning, an online learning target automatic classification and clustering analysis algorithm based on cognitive thinking was proposed and was applied to a multi-dimensional learning community.
- Enhanced YOLOv8 for industrial polymer films: a semi-supervised framework for micron-scale defect detection6
The improved YOLOv8 algorithm is proposed, meeting the stringent requirements for high-precision small-target defect detection on polymer material film in industrial production and maintaining defect detection rates exceeding 95.0% across validation data of varying image sizes.
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- NanoNet: Parameter-Efficient Learning with Label-Scarce Supervision for Lightweight Text Mining Model–
NanoNet is proposed, a novel framework for lightweight text mining that implements parameter-efficient learning with limited supervision that employs online knowledge distillation to generate multiple small models and enhances their performance through mutual learning regularization.
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- Development of addition-cured ambient vulcanization silicone rubber–
The improvement of mechanical properties, platinum catalyst and application of addition-cured ambient vulcanization silicone rubber were reviewed and the application developments in the field of medicine, electricity and electron, aerospace were introduced.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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