Papers with general-purpose language model

2 papers
Synthetic Propaganda Embeddings To Train A Linear Projection (D19-50)

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Challenge: Using contextualized token embeddings, we can extract features of propaganda from contextualized embeddnings without fine-tuning the large parameters of the base model.
Approach: They propose a method for detecting fine-grained categories of propaganda in text by generating synthetically generated embeddings from pre-trained language models.
Outcome: The proposed method is used in the first shared task in fine-grained propaganda detection at NLP4IF as Team Stalin.
Re3: Generating Longer Stories With Recursive Reprompting and Revision (2022.emnlp-main)

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Challenge: Recent work has generated short stories of several pages in length, but they are much shorter than typical short stories meant for human consumption.
Approach: They propose a framework to generate long-range plot coherence and relevance by prompting a general-purpose language model and a language model.
Outcome: The proposed framework generates stories of 2000-2500 words, compared to similar-length stories generated directly from the same model.

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