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20172023
most citedDo Language Models Plagiarize?

49 citations · 125 across the 16 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.CL2023★ 5 cited

TOPFORMER: Topology-Aware Authorship Attribution of Deepfake Texts with Diverse Writing Styles

Adaku Uchendu, Thai Le, Dongwon Lee

Recent advances in Large Language Models (LLMs) have enabled the generation of open-ended high-quality texts, that are non-trivial to distinguish from human-written texts. We refer…

cs.SI2023★ 23 cited

Social network modeling and applications, a tutorial

Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi

Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…

cs.CL2023★ 3 cited

Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts?

Adaku Uchendu, Jooyoung Lee, Hua Shen +3

Advances in Large Language Models (e.g., GPT-4, LLaMA) have improved the generation of coherent sentences resembling human writing on a large scale, resulting in the creation of so…

cs.LG2023★ 4 cited

NoisyHate: Mining Online Human-Written Perturbations for Realistic Robustness Benchmarking of Content Moderation Models

Yiran Ye, Thai Le, Dongwon Lee

Online texts with toxic content are a clear threat to the users on social media in particular and society in general. Although many platforms have adopted various measures (e.g., m…

cs.CL2023

CRYPTEXT: Database and Interactive Toolkit of Human-Written Text Perturbations in the Wild

Thai Le, Ye Yiran, Yifan Hu +1

User-generated textual contents on the Internet are often noisy, erroneous, and not in correct forms in grammar. In fact, some online users choose to express their opinions online…