The emergence of ChatGPT has recently garnered significant attention from the
computational linguistics community. To demonstrate its capabilities as a keyphrase …

Given the exponential growth in the number of documents on the web in recent years, there
is an increasing demand for accurate models to extract keyphrases from such documents …

Keyphrase extraction aims to provide readers with high-level information about the central
ideas or important topics described in a given source text. Recent advances in embedding …

Over-generation errors occur when a keyphrase extraction model correctly determines a
candidate keyphrase as a keyphrase because it contains a word that frequently appears in …

Zero-shot keyphrase extraction aims to build a keyphrase extractor without training by
human-annotated data, which is challenging due to the limited human intervention involved …

Keyphrase Extraction (KE) aims to identify a concise set of words or phrases that effectively
summarizes the core ideas of a document. Recent embedding-based models have achieved …

Keyphrase extraction aims to automatically extract salient phrases representing the critical
information in the source document. Identifying salient phrases is challenging because there …

Pre-trained large language models can perform natural language processing downstream
tasks by conditioning on human-designed prompts. However, a prompt-based approach …

Abstract In Unsupervised Keyphrase Extraction (UKE) tasks, candidate phrases are ranked
based on their similarity to the document embedding. However, This method assumes that …