Summary of Finesure: Fine-grained Summarization Evaluation Using Llms, by Hwanjun Song et al.
FineSurE: Fine-grained Summarization Evaluation using LLMs
by Hwanjun Song, Hang Su, Igor Shalyminov, Jason Cai, Saab Mansour
First submitted to arxiv on: 1 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Automated evaluation of text summarization is crucial for benchmarking and model development. Recent methods like ROUGE and LLM-based metrics have limitations, including not correlating well with human judgment or only assessing summaries at the sentence level. To address these limitations, we propose FineSurE, a fine-grained evaluator specifically designed for summarization using large language models (LLMs). FineSurE assesses faithfulness, completeness, and conciseness, enabling multi-dimensional evaluation. We compare various LLMs as backbones for FineSurE and conduct extensive benchmarking against state-of-the-art methods, showing improved performance on completeness and conciseness dimensions. Our results highlight the importance of fine-grained evaluation in text summarization. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to measure how good a machine learning model is at summarizing text. It’s like grading an essay, but instead of using a human teacher, you use a special computer program to do it. Current methods aren’t very accurate and can’t tell us everything we want to know about the model’s performance. To fix this problem, researchers created a new tool called FineSurE that can evaluate a model’s ability to summarize text in three ways: faithfulness (is the summary true?), completeness (does the summary include all important points?), and conciseness (is the summary too long?). They tested different versions of FineSurE using various computer models and found it improved their performance. This new tool will help create better summarization models for future use. |
Keywords
» Artificial intelligence » Machine learning » Rouge » Summarization
