Llm-based nlg evaluation: Current status and challenges
Evaluating natural language generation (NLG) is a vital but challenging problem in artificial
intelligence. Traditional evaluation metrics mainly capturing content (eg n-gram) overlap …
intelligence. Traditional evaluation metrics mainly capturing content (eg n-gram) overlap …
A comprehensive survey on process-oriented automatic text summarization with exploration of llm-based methods
H Jin, Y Zhang, D Meng, J Wang, J Tan - arXiv preprint arXiv:2403.02901, 2024 - arxiv.org
Automatic Text Summarization (ATS), utilizing Natural Language Processing (NLP)
algorithms, aims to create concise and accurate summaries, thereby significantly reducing …
algorithms, aims to create concise and accurate summaries, thereby significantly reducing …
Leveraging large language models for nlg evaluation: A survey
In the rapidly evolving domain of Natural Language Generation (NLG) evaluation,
introducing Large Language Models (LLMs) has opened new avenues for assessing …
introducing Large Language Models (LLMs) has opened new avenues for assessing …
SATS: simplification aware text summarization of scientific documents
Simplifying summaries of scholarly publications has been a popular method for conveying
scientific discoveries to a broader audience. While text summarization aims to shorten long …
scientific discoveries to a broader audience. While text summarization aims to shorten long …
Language Models can Evaluate Themselves via Probability Discrepancy
In this paper, we initiate our discussion by demonstrating how Large Language Models
(LLMs), when tasked with responding to queries, display a more even probability distribution …
(LLMs), when tasked with responding to queries, display a more even probability distribution …
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models
Text summarization research has undergone several significant transformations with the
advent of deep neural networks, pre-trained language models (PLMs), and recent large …
advent of deep neural networks, pre-trained language models (PLMs), and recent large …