Storytelling's captivating potential makes it a fascinating research area, with implications for entertainment, education, therapy, and cognitive studies.
Currently, most machine learning models are trained by centralized teams and are rarely updated.
In particular, we hypothesize that the order of the input concepts can affect the PTM's ability to utilize its commonsense knowledge.
ICL incurs substantial computational, memory, and storage costs because it involves processing all of the training examples every time a prediction is made.
Ranked #1 on Few-Shot Text Classification on RAFT
A common method for extractive multi-document news summarization is to re-formulate it as a single-document summarization problem by concatenating all documents as a single meta-document.
Pre-trained language models learn socially harmful biases from their training corpora, and may repeat these biases when used for generation.