7 citations · 11 across the 19 of their papers we have counts for
5 papers · 1 filter
Structured Probabilistic Coding
Dou Hu, Lingwei Wei, Yaxin Liu +2
This paper presents a new supervised representation learning framework, namely structured probabilistic coding (SPC), to learn compact and informative representations from input re…
Are Large Language Models Good Fact Checkers: A Preliminary Study
Han Cao, Lingwei Wei, Mengyang Chen +2
Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as supe…
Explore the Potential of LLMs in Misinformation Detection: An Empirical Study
Mengyang Chen, Lingwei Wei, Han Cao +2
Large Language Models (LLMs) have garnered significant attention for their powerful ability in natural language understanding and reasoning. In this paper, we present a comprehensi…
MiLe Loss: a New Entropy-Weighed Loss for Mitigating the Bias of Learning Difficulties in Large Language Models
Zhenpeng Su, Xing Wu, Xue Bai +5
Generative language models are usually pretrained on large text corpus via predicting the next token (i.e., sub-word/word/phrase) given the previous ones. Recent works have demonst…
HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison Corpus
Zhenpeng Su, Xing Wu, Wei Zhou +2
ChatGPT has garnered significant interest due to its impressive performance; however, there is growing concern about its potential risks, particularly in the detection of AI-genera…