If you are searching for new ways to improve ChatGPT summaries of text documents, you might be interested in new method for generating dense summaries using ChatGPT-4. This new ChatGPT prompt is a collaborative effort from Salesforce AI, MIT, Columbia University, and Biomedical Informatics, and is based on the concept of Chain of Density prompting.
The idea of Chain of Density prompting is a method that aims to generate more concise and information-rich summaries by chaining together a series of prompts that guide the model to focus on the most important aspects of the text. This method is a departure from the traditional zero-shot or vanilla prompt, which often results in summaries that are either too broad or too narrow in scope.
“Selecting the “right” amount of information to include in a summary is a difficult task. A good summary should be detailed and entity-centric without being overly dense and hard to follow. To better understand this tradeoff, we solicit increasingly dense GPT-4 summaries with what we refer to as a “Chain of Density” (CoD) prompt. Specifically, GPT-4 generates an initial entitysparse summary before iteratively incorporating missing salient entities without increasing the length. Summaries generated by CoD are more abstractive, exhibit more fusion, and have less of a lead bias than GPT-4 summaries generated by a vanilla prompt.”
Improve ChatGPT-4 summarization
The Chain of Density prompting method was put to the test in a series of experiments. The goal was to assess its effectiveness in generating dense summaries and to compare its performance with the zero-shot or vanilla ChatGPT prompts. The testing process was apparently rigorous, involving a variety of texts and scenarios to ensure a comprehensive evaluation of the method’s capabilities. Read the official paper or watch the video below kindly created by All About AI to learn more about this new method of creating summaries using ChatGPT prompts. The Chain of Density prompt is included at the bottom of this article if you would like to try it out.
Other articles you may find of interest on the subject of refining your AI prompts for the best results :
- How to write AI prompts using the chain of thought principle (COT
- How to fine tune your ChatGPT prompts?
- How to create the perfect ChatGPT prompts
- How to write prompts for Stable Diffusion SDXL AI art generator
- 100 Midjourney Ai art textures and materials prompts
- 10 AI prompts to help you improve your writing
- 6 ChatGPT prompt secrets to improve your writing
- How to get the best results using ChatGPT prompts
Chain of Density ChatGPT prompt
The results of the testing were quite revealing. The Chain of Density prompting method demonstrated a significant improvement in the generation of dense summaries compared to the zero-shot or vanilla prompt. The summaries produced were more concise, contained more relevant information, and were generally more accurate in capturing the essence of the original text. These results suggest that the Chain of Density prompting method could be a valuable tool in the field of AI language models.
However, it’s important to note that while the results were promising, they are not definitive. The Chain of Density prompting method is still in its early stages, and further testing and refinement are needed to fully understand its potential and limitations. Nevertheless, the initial impressions of the method are positive, and it represents a promising step forward in the field of AI language models.
The researchers behind the Chain of Density prompting method have extended an invitation to others in the field to try the method and read the related paper. This open invitation is a testament to the collaborative spirit that drives advancements in the field of AI. It’s an opportunity for others to build upon the work that has been done, to test the method in new contexts, and to contribute to the ongoing development of this innovative approach.
The Chain of Density prompting method represents a significant advancement in the generation of dense summaries using ChatGPT-4. Its superior performance compared to the zero-shot or vanilla prompt, as demonstrated in the testing, suggests that it could be a valuable tool in the field of AI language models. However, it’s important to remember that this method is still in its early stages, and further testing and refinement are needed. The invitation to try the method and read the related paper is an exciting opportunity for others in the field to contribute to this important work.
Improve ChatGPT summaries
Here is the prompt for you to try for yourself to see the results it can produce :
Article: {Insert article}
You will generate increasingly concise entity-dense summaries of the above article. Repeat the following 2 steps 5 times.
Step 1: Identify 1-3 informative entities (delimited) from the article which are missing from the previously generated summary.
Step 2: Write a new denser summary of identical length which covers every entity and detail from the previous summary plus the missing entities.
A missing entity is:
- Relevant: to the main stories.
- Specific: descriptive yet concise (5 words or fewer).
- Novel: not in the previous summary.
- Faithful: present in the article.
- Anywhere: located in the article.
Guidelines: - The first summary should be long (4-5 sentences, ~80 words), yet highly non-specific, containing little information beyond the entities marked as missing. Use overly verbose language and fillers (e.g., “this article discusses”) to reach ~80 words.
- Make every word count. Rewrite the previous summary to improve flow and make space for additional entities.
- Make space with fusion, compression, and removal of uninformative phrases like “the article discusses”.
- The summaries should become highly dense and concise, yet self-contained, e.g., easily understood without the article.
- Missing entities can appear anywhere in the new summary.
- Never drop entities from the previous summary. If space cannot be made, add fewer new entities.
Remember: Use the exact same number of words for each summary.
Latest Geeky Gadgets Deals
Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.