Summary of Utilizing Gpt to Enhance Text Summarization: a Strategy to Minimize Hallucinations, by Hassan Shakil et al.
Utilizing GPT to Enhance Text Summarization: A Strategy to Minimize Hallucinations
by Hassan Shakil, Zeydy Ortiz, Grant C. Forbes
First submitted to arxiv on: 7 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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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 A novel AI research paper combines DistilBERT, T5 models to generate accurate summaries, tackling common problem of hallucinations through GPT-based refining process. The study evaluates and refines summaries using traditional and novel metrics, demonstrating significant improvements in reducing hallucinatory content and increasing factual integrity. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI-generated summaries can be improved by combining DistilBERT and T5 models. This research shows how a new approach, involving GPT-based refining, can reduce mistakes and make summaries more accurate. The study compares unrefined and refined summaries using different measures, revealing better results for the refined ones. |
Keywords
» Artificial intelligence » Gpt » T5
