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20202026
most citedA Comprehensive Survey on Data Augmentation

20 citations · 103 across the 37 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL2025★ 1 cited

SciTopic: Enhancing Topic Discovery in Scientific Literature through Advanced LLM

Pengjiang Li, Zaitian Wang, Xinhao Zhang +4

Topic discovery in scientific literature provides valuable insights for researchers to identify emerging trends and explore new avenues for investigation, facilitating easier scien…

cs.CL2025★ 9 cited

Diversity-oriented Data Augmentation with Large Language Models

Zaitian Wang, Jinghan Zhang, Xinhao Zhang +3

Data augmentation is an essential technique in natural language processing (NLP) for enriching training datasets by generating diverse samples. This process is crucial for improvin…

cs.CL2023

Resolving the Imbalance Issue in Hierarchical Disciplinary Topic Inference via LLM-based Data Augmentation

Xunxin Cai, Meng Xiao, Zhiyuan Ning +1

In addressing the imbalanced issue of data within the realm of Natural Language Processing, text data augmentation methods have emerged as pivotal solutions. This data imbalance is…

cs.CL2023

NEEDED: Introducing Hierarchical Transformer to Eye Diseases Diagnosis

Xu Ye, Meng Xiao, Zhiyuan Ning +4

With the development of natural language processing techniques(NLP), automatic diagnosis of eye diseases using ophthalmology electronic medical records (OEMR) has become possible.…

cs.CL2022

Hierarchical MixUp Multi-label Classification with Imbalanced Interdisciplinary Research Proposals

Meng Xiao, Min Wu, Ziyue Qiao +4

Funding agencies are largely relied on a topic matching between domain experts and research proposals to assign proposal reviewers. As proposals are increasingly interdisciplinary,…