Search:
Match:
2 results

Analysis

The article introduces PharmaShip, a new benchmark dataset for evaluating AI models on Chinese pharmaceutical shipping documents. The benchmark is designed to be entity-centric and supervised by reading order, suggesting a focus on information extraction and understanding the sequential nature of the documents. The use of Chinese documents indicates a focus on a specific language and domain. The source being ArXiv suggests this is a research paper.
Reference

Research#NER🔬 ResearchAnalyzed: Jan 10, 2026 14:19

SEDA: Enhancing Discontinuous NER with Self-Adapted Data Augmentation

Published:Nov 25, 2025 10:06
1 min read
ArXiv

Analysis

The paper introduces SEDA, a novel data augmentation technique specifically designed to improve grid-based discontinuous Named Entity Recognition (NER) models. This targeted approach suggests a potential for significant performance gains in complex NER tasks.
Reference

SEDA is a self-adapted entity-centric data augmentation technique.