16 citations · 71 across the 10 of their papers we have counts for
5 papers · 1 filter
Systematic Rectification of Language Models via Dead-end Analysis
Meng Cao, Mehdi Fatemi, Jackie Chi Kit Cheung +1
With adversarial or otherwise normal prompts, existing large language models (LLM) can be pushed to generate toxic discourses. One way to reduce the risk of LLMs generating undesir…
Learning with Rejection for Abstractive Text Summarization
Meng Cao, Yue Dong, Jingyi He +1
State-of-the-art abstractive summarization systems frequently hallucinate content that is not supported by the source document, mainly due to noise in the training dataset. Existin…
Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization
Meng Cao, Yue Dong, Jackie Chi Kit Cheung
State-of-the-art abstractive summarization systems often generate \emph{hallucinations}; i.e., content that is not directly inferable from the source text. Despite being assumed in…
Factual Error Correction for Abstractive Summarization Models
Meng Cao, Yue Dong, Jiapeng Wu +1
Neural abstractive summarization systems have achieved promising progress, thanks to the availability of large-scale datasets and models pre-trained with self-supervised methods. H…
Referring Expression Generation Using Entity Profiles
Meng Cao, Jackie Chi Kit Cheung
Referring Expression Generation (REG) is the task of generating contextually appropriate references to entities. A limitation of existing REG systems is that they rely on entity-sp…