most citedFake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities

5 citations · 5 across the 2 of their papers we have counts for

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cs.CL2026

MemEmo: Evaluating Emotion in Memory Systems of Agents

Peng Liu, Zhen Tao, Jihao Zhao +5

Memory systems address the challenge of context loss in Large Language Model during prolonged interactions. However, compared to human cognition, the efficacy of these systems in p…

cs.CL2024

Unveiling Large Language Models Generated Texts: A Multi-Level Fine-Grained Detection Framework

Zhen Tao, Zhiyu Li, Runyu Chen +2

Large language models (LLMs) have transformed human writing by enhancing grammar correction, content expansion, and stylistic refinement. However, their widespread use raises conce…

cs.CL2024

Towards Reliable Detection of LLM-Generated Texts: A Comprehensive Evaluation Framework with CUDRT

Zhen Tao, Yanfang Chen, Dinghao Xi +2

The increasing prevalence of large language models (LLMs) has significantly advanced text generation, but the human-like quality of LLM outputs presents major challenges in reliabl…

cs.CL20245 cited

Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities

Xiaomin Yu, Yezhaohui Wang, Yanfang Chen +5

In recent years, generative artificial intelligence models, represented by Large Language Models (LLMs) and Diffusion Models (DMs), have revolutionized content production methods.…

cs.CL2024

CAT-LLM: Style-enhanced Large Language Models with Text Style Definition for Chinese Article-style Transfer

Zhen Tao, Dinghao Xi, Zhiyu Li +2

Text style transfer plays a vital role in online entertainment and social media. However, existing models struggle to handle the complexity of Chinese long texts, such as rhetoric,…