6 citations · 22 across the 11 of their papers we have counts for
9 papers · 1 filter
When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection
Lang Gao, Xuhui Li, Chenxi Wang +7
Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this ability also heightens the risk of…
Pastiche Novel Generation Creating: Fan Fiction You Love in Your Favorite Author's Style
Xueran Han, Yuhan Liu, Mingzhe Li +5
Great novels create immersive worlds with rich character arcs, well-structured plots, and nuanced writing styles. However, current novel generation methods often rely on brief, sim…
Flexible and Adaptable Summarization via Expertise Separation
Xiuying Chen, Mingzhe Li, Shen Gao +5
A proficient summarization model should exhibit both flexibility -- the capacity to handle a range of in-domain summarization tasks, and adaptability -- the competence to acquire n…
Decouple knowledge from parameters for plug-and-play language modeling
Xin Cheng, Yankai Lin, Xiuying Chen +2
Pre-trained language models(PLM) have made impressive results in various NLP tasks. It has been revealed that one of the key factors to their success is the parameters of these mod…
Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory
Xin Cheng, Di Luo, Xiuying Chen +3
With direct access to human-written reference as memory, retrieval-augmented generation has achieved much progress in a wide range of text generation tasks. Since better memory wou…
How does Truth Evolve into Fake News? An Empirical Study of Fake News Evolution
Mingfei Guo, Xiuying Chen, Juntao Li +2
Automatically identifying fake news from the Internet is a challenging problem in deception detection tasks. Online news is modified constantly during its propagation, e.g., malici…