Enhancing Coherence In Extractive Summarization With LLMs
Researchers introduce LAMSUM dataset & experiments with LLMs to enhance extractive summarization coherence. They fine-tune models like BERT & GPT-2 to optimize for coherence, improving summary flow & naturalness.
This is a Plain English Papers summary of a research paper called Towards Enhancing Coherence in Extractive Summarization: Dataset and Experiments with LLMs. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview This paper introduces a new dataset and experiments to enhance the coherence of extractive summarization using large language models (LLMs). Extractive summarization is the process of selecting and combining the most important sentences from a document to create a concise summary. The authors argue that curr...