## Introducing GPT-4 Summarization with Chain of Density Prompting
- Researchers from institutions like Columbia University have developed a "Chain of Density" (CoD) prompting method for generating GPT-4 summaries with varying information density.
- The CoD method iteratively incorporates missing salient entities from the original text into the previous summary, making it increasingly entity-dense without changing the summary length.
- Human preference studies show that people prefer denser summaries than those generated by standard GPT-4 prompts, with these summaries being almost as dense as human-written ones.
- The research team conducted human and automatic evaluations on 100 CNN DailyMail articles to better understand the trade-off between informativeness (favoring more entities) and clarity (favoring fewer entities).
- The study provides 500 annotated CoD summaries and an additional 5,000 unannotated summaries for evaluation or distillation.
#AI #LLM #GPT #GPT-4
🔗 Learn more: [2309.04269.pdf](https://ppl-ai-file-upload.s3.amazonaws.com/web/direct-files/1019777/d1249c62-2da9-4810-9797-cac455065e49/2309.04269.pdf)
fwenoir / FWEnoir
npub1p5…ffwt7
2023-09-12 06:31:02
Author Public Key
npub1p5gec9d9f9wsc99yzh64sgavk428kwcqvsvs4x3ahyhdvmtmrvuspffwt7Published at
2023-09-12 06:31:02Event JSON
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"content": "## Introducing GPT-4 Summarization with Chain of Density Prompting\n\n- Researchers from institutions like Columbia University have developed a \"Chain of Density\" (CoD) prompting method for generating GPT-4 summaries with varying information density.\n- The CoD method iteratively incorporates missing salient entities from the original text into the previous summary, making it increasingly entity-dense without changing the summary length.\n- Human preference studies show that people prefer denser summaries than those generated by standard GPT-4 prompts, with these summaries being almost as dense as human-written ones.\n- The research team conducted human and automatic evaluations on 100 CNN DailyMail articles to better understand the trade-off between informativeness (favoring more entities) and clarity (favoring fewer entities).\n- The study provides 500 annotated CoD summaries and an additional 5,000 unannotated summaries for evaluation or distillation.\n\n#AI #LLM #GPT #GPT-4\n\n🔗 Learn more: [2309.04269.pdf](https://ppl-ai-file-upload.s3.amazonaws.com/web/direct-files/1019777/d1249c62-2da9-4810-9797-cac455065e49/2309.04269.pdf)\n",
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