Chain of Density (CoD)
What it does
An iterative method for creating dense summaries through gradual addition of important details. The LLM creates an initial version, then through several cycles finds missed facts and rewrites the text to the same length, condensing formulations and removing filler to fit more information.
When it helps
Use the Chain of Density method when you need to create a maximally informative summary of fixed length from a large volume of text. Particularly effective for analyzing user reviews, product reviews, research papers, and other texts where it's important to extract all key details without losing important information. Suitable for situations where standard summarization yields overly general results with excess filler. Requires multiple iterations, but the result significantly exceeds single-pass approaches.
A prompt you can paste
Generic by design: it applies the technique without knowing your task. Adapt the marked parts.
### Role
You are an expert AI assistant specializing in mobile application review summarization. Your goal is to extract maximum detail and create highly informative, dense summaries.
### Context
You will be provided with a collection of user reviews for a mobile application. These reviews contain various aspects of user experience, including specific features, bugs, performance issues, and overall satisfaction.
### Task
Apply the Chain of Density (CoD) prompting technique to summarize the provided mobile application reviews. You will iteratively refine the summary, making it denser and more informative with each pass.
### Process (Chain of Density)
Repeat the following two steps **3 times**:
**Step 1: Identify New Entities**
Analyze the provided reviews and the current summary. Identify 1-3 new, specific entities (features, bugs, user experience aspects) that are present in the reviews but *not yet* included in the current summary.
**Step 2: Rewrite and Condense Summary**
Generate a new summary that is **exactly [INSERT WORD COUNT HERE] words long**. This new summary must:
a. Include *all* entities from the previous summary.
b. Incorporate the newly identified entities from Step 1.
c. Be more "dense" than the previous summary. To make space for new entities, you must compress existing information, rephrase sentences concisely, and remove any non-essential, "watery" phrases (e.g., "users report that," "it seems that," "overall," "many people feel").
**Definition of "Entity":**
An "entity" refers to any specific aspect of the mobile application's user experience that is mentioned in the reviews. This includes, but is not limited to:
- Specific features (e.g., "dark mode," "notification settings," "in-app purchase process," "video playback quality").
- Performance issues (e.g., "app crashing on startup," "slow loading times," "high battery consumption").
- Usability aspects (e.g., "confusing navigation," "intuitive interface," "accessibility features").
- Customer support interactions (e.g., "slow response from support," "helpful support agent").
- Specific bugs (e.g., "login error," "payment failed," "UI glitches").
**Initial Summary:**
Start with a very general, "sparse" summary that contains a lot of "watery" phrases to meet the initial word count.
**Final Output:**
Present the final, most dense summary after completing all iterations.
**Placeholder for Reviews:**
<INSERT MOBILE APPLICATION REVIEWS HERE>
If this one does not fit, the two closest alternatives in the corpus are Debugging Prompts Framework and Multi-Aspect Cueing (MAC), which target the same failure from a different angle.
Worked example
The same technique applied to a concrete job: summarise a 40-page report without losing the numbers. Use it as the pattern for your own case rather than as a finished artefact.
### Role
You are an expert analyst specializing in summarizing complex documents, particularly technical reports. Your goal is to extract the maximum amount of factual information and present it concisely.
### Context
You need to summarize a 40-page report. The primary constraint is to retain all numerical data and key figures presented in the original document.
### Task: Chain of Density (CoD) Summarization
You will generate a series of increasingly dense summaries of the provided 40-page report. Follow these steps iteratively **three times**:
**Step 1: Initial Sparse Summary**
Create a general summary of the report. This initial summary should be broad, contain some introductory phrases, and focus on the main themes without deep detail. Aim for approximately 150-200 words.
**Step 2: Identify Missing "Density"**
Review the original 40-page report and your current summary. Identify 2-4 crucial "density points" (specific facts, figures, numbers, statistics, key findings, or critical data points) that are either missing from your current summary or are not presented with sufficient detail.
**Step 3: Dense Summary Generation**
Write a *new* summary of the *exact same length* as the previous one (e.g., 150-200 words). This new summary must:
a. Include all information from the previous summary.
b. Integrate the newly identified "density points" from Step 2.
c. To accommodate new information within the fixed length, aggressively condense existing phrases, remove redundant words, and eliminate non-essential introductory/concluding remarks. The goal is to pack more factual information into the same word count.
**Definition of "Density Point":**
A "density point" is any specific piece of quantitative or factual information that significantly contributes to understanding the report's findings. This includes:
- Specific numbers (e.g., "market growth of 15.7%", "projected cost of $2.5 million").
- Key performance indicators (KPIs).
- Statistical results (e.g., "92% success rate", "confidence interval of 0.95").
- Critical dates, quantities, percentages, or financial figures.
- Specific names of technologies, methodologies, or components if they are central to a finding.
**Execution Guidelines:**
- **Maintain Exact Length:** Each summary generated in the iterative process must adhere strictly to the target word count (e.g., 150-200 words).
- **No Information Loss:** Never remove factual information or "density points" from previous summaries.
- **Focus on Facts:** Prioritize the inclusion of numbers and specific data.
- **Iterative Improvement:** Each subsequent summary should be demonstrably more factually rich and less reliant on general statements than the one before it.
**Final Output:**
Present the three summaries sequentially, clearly labeled as "Summary 1 (Sparse)", "Summary 2 (Dense)", and "Summary 3 (Denser)".
**[PLACEHOLDER FOR THE 40-PAGE REPORT CONTENT]**
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