How can Generative AI summarize scientific papers without distorting key technical terms

Question

With the help of code can you tell me How can Generative AI summarize scientific papers without distorting key technical terms?

Answer 1

To summarize scientific papers accurately without distorting key technical terms, use domain-specific fine-tuning, retrieval-augmented generation (RAG), and constraint-based text simplification techniques.

Here is the code snippet you can refer to:

In the above, we are using the following key points:

• Fine-Tuned Model: Uses SciBERT for scientific text processing and T5 for summarization.
• Keyword Preservation: Ensures critical technical terms remain intact in the summary.
• Beam Search Decoding: Uses multiple hypothesis generation (num_beams=5) to improve accuracy.
• Contextual Understanding: Retains meaning while compressing complex scientific language.
• Truncation Handling: Ensures input text is properly truncated to avoid loss of key information.

Hence, by leveraging fine-tuned domain-specific models, constraint-based summarization, and retrieval-augmented generation, we can accurately summarize scientific papers without distorting key technical terms.