What's the difference between extractive and abstractive summarization?

Extractive selects and combines key sentences from the original text verbatim. Abstractive generates new sentences that capture the core meaning, often more concise but with higher risk of inaccuracies.

How do I summarize texts longer than the context window?

Use map-reduce: split the text into chunks, summarize each chunk separately, then summarize all partial summaries into a final one. Alternatively, use models with larger context windows (100K+ tokens).

How can I evaluate summary quality?

Use metrics like ROUGE (word overlap), BERTScore (semantic similarity), or LLM-as-judge. For production, combine automated metrics with periodic human evaluation on a sample.

Can I control summary length and style?

Yes. Specify target length (e.g., 'in 3 sentences'), format (bullet points, paragraph), audience level (executive, technical), and focus areas in your prompt.

ApplicationNew

Summarization

Condensing information

The Problem: Long documents take forever to read, and you often just need the key points. How can AI condense information without losing what matters?

The Solution: Your Executive Summary Writer

Summarization uses LLMs to condense long texts into shorter versions while preserving the most important information. Imagine a 200-word paragraph about quarterly revenue — summarized to one sentence: "Q3 revenue grew 18% YoY driven by enterprise contracts." The key insight survives, but 95% of the words are gone. For very long texts, consider the context window limit and use prompt chaining to process them in parts.

Think of it like writing a book summary:

1. Read entire text: Process the full document to understand context and structure
2. Identify key facts and arguments: Find the main claims, evidence, conclusions, and data points
3. Choose summary style: Extractive (key sentences verbatim) vs abstractive (rephrased in new words)
4. Compress while preserving meaning: Rewrite concisely — remove redundancy, keep critical details intact
5. Verify nothing critical was lost: Compare summary against original — are all key points represented?

For documents longer than the context window, use a map-reduce strategy: summarize each chunk separately (map), then summarize the summaries (reduce). This scales to book-length texts.

Where Is This Used?

News Digests: Condensing articles into bullet points
Meeting Notes: Summarizing transcripts
Research: Quick overviews of papers or reports
Legal/Medical: Summarizing complex documents

Fun Fact: You can control summary style with prompts: "summarize for a 5-year-old" vs "summarize for a domain expert" produce very different results! Specifying audience and purpose dramatically changes output.

Try It Yourself!

Use the interactive example below to summarize texts with different styles and lengths to see how AI adapts its output.

Round 1/6 — Tech News Article

Original Text~150 words

Artificial intelligence continues to transform the technology landscape in 2024. Major tech companies have invested billions in AI research and development, leading to significant breakthroughs in natural language processing and computer vision. OpenAI's latest models demonstrate unprecedented capabilities in reasoning and code generation. Meanwhile, concerns about AI safety and regulation have prompted governments worldwide to consider new legislation. The European Union has already passed the AI Act, establishing strict guidelines for high-risk AI applications. Industry experts predict that AI will create more jobs than it displaces, though the transition will require significant workforce retraining efforts. The integration of AI into everyday products, from smartphones to household appliances, is expected to accelerate in the coming years.

Summary — what type is this?

AI investment is driving major advances in NLP and computer vision in 2024. While the EU implements AI regulations, experts believe AI will ultimately create more jobs than it eliminates, though retraining will be essential.

Key Insight

• Extractive — copies exact phrases from the original. Fast and factual, but may lose context between sentences.
• Abstractive — rephrases in new words, like a human retelling. Natural, but may subtly distort meaning.
• Key Points — structured bullet list for quick scanning. Best for meeting notes and decision summaries.

Try it yourself

Interactive demo of this technique

Technique Comparison

Demo Mode

Pre-recorded responses

TaskBeginnerWriting

Summarize an article about the impact of remote work on productivity

Without technique

Prompt

Briefly summarize: "A Stanford study of 16,000 employees showed remote workers are 13% more productive than office workers. However, a 2024 meta-analysis (Nature Human Behaviour) found that fully remote work reduces productivity by 10-20% due to communication losses. Hybrid format (3 days office + 2 days home) showed best results: +5% productivity and -35% turnover. Microsoft internally confirmed this data: hybrid teams close tasks 8% faster."

Response

The article discusses how remote work can be both beneficial and harmful. On one hand, it increases productivity; on the other, it can decrease it. Hybrid format seems to be the golden mean. Many companies have already adopted this format.

Tokens:120/60

Time:450ms

Quality:

With Summarization

With technique

Prompt

Create a structured summary of the article using this template: **Format:** - Key finding (1 sentence) - Key data points (bulleted list with numbers) - Practical recommendation (1-2 sentences) **Rules:** - Preserve all numerical data and sources - Do not add information not present in the text - Maximum 80 words Article: "A Stanford study of 16,000 employees showed remote workers are 13% more productive than office workers. However, a 2024 meta-analysis (Nature Human Behaviour) found that fully remote work reduces productivity by 10-20% due to communication losses. Hybrid format (3 days office + 2 days home) showed best results: +5% productivity and -35% turnover. Microsoft internally confirmed this data: hybrid teams close tasks 8% faster."

Response

Key finding: Hybrid work format outperforms both fully remote and office-based in productivity and retention.

Key data:

Remote: +13% productivity (Stanford, 16,000 employees)
Fully remote: -10-20% due to communication (Nature, 2024)
Hybrid (3+2): +5% productivity, -35% turnover
Microsoft: +8% task completion speed on hybrid

Recommendation: Implement 3/2 hybrid format rather than fully remote.

👁️Template (finding + data + recommendation) sets structure, eliminating watery retelling

🧠Rule "preserve all numbers and sources" forces retention of 13%, Stanford, Nature

✅The 80-word limit forces the model to be concise and highlight what matters

Tokens:190/130

Time:720ms

Quality:

Why this works

Structure template + data preservation rules + word limit turn a vague retelling into an informative summary where all numbers are intact.

1 / 2

Practice Challenges

Create a free account to solve challenges

5 AI-verified challenges for this lesson

Related lessons:Chain Of Thought Question Answering

This lesson is part of a structured LLM course.

My Learning Path

ApplicationNew

Summarization

Condensing information

The Problem: Long documents take forever to read, and you often just need the key points. How can AI condense information without losing what matters?

The Solution: Your Executive Summary Writer

Think of it like writing a book summary:

1. Read entire text: Process the full document to understand context and structure
2. Identify key facts and arguments: Find the main claims, evidence, conclusions, and data points
3. Choose summary style: Extractive (key sentences verbatim) vs abstractive (rephrased in new words)
4. Compress while preserving meaning: Rewrite concisely — remove redundancy, keep critical details intact
5. Verify nothing critical was lost: Compare summary against original — are all key points represented?

For documents longer than the context window, use a map-reduce strategy: summarize each chunk separately (map), then summarize the summaries (reduce). This scales to book-length texts.

Where Is This Used?

News Digests: Condensing articles into bullet points
Meeting Notes: Summarizing transcripts
Research: Quick overviews of papers or reports
Legal/Medical: Summarizing complex documents

Try It Yourself!

Use the interactive example below to summarize texts with different styles and lengths to see how AI adapts its output.

Round 1/6 — Tech News Article

Original Text~150 words

Summary — what type is this?

Key Insight

• Extractive — copies exact phrases from the original. Fast and factual, but may lose context between sentences.
• Abstractive — rephrases in new words, like a human retelling. Natural, but may subtly distort meaning.
• Key Points — structured bullet list for quick scanning. Best for meeting notes and decision summaries.

Try it yourself

Interactive demo of this technique

Technique Comparison

Demo Mode

Pre-recorded responses

TaskBeginnerWriting

Summarize an article about the impact of remote work on productivity

Without technique

Prompt

Response

Tokens:120/60

Time:450ms

Quality:

With Summarization

With technique

Prompt

Response

Key finding: Hybrid work format outperforms both fully remote and office-based in productivity and retention.

Key data:

Remote: +13% productivity (Stanford, 16,000 employees)
Fully remote: -10-20% due to communication (Nature, 2024)
Hybrid (3+2): +5% productivity, -35% turnover
Microsoft: +8% task completion speed on hybrid

Recommendation: Implement 3/2 hybrid format rather than fully remote.

👁️Template (finding + data + recommendation) sets structure, eliminating watery retelling

🧠Rule "preserve all numbers and sources" forces retention of 13%, Stanford, Nature

✅The 80-word limit forces the model to be concise and highlight what matters

Tokens:190/130

Time:720ms

Quality:

Why this works

Structure template + data preservation rules + word limit turn a vague retelling into an informative summary where all numbers are intact.

1 / 2

Practice Challenges

Create a free account to solve challenges

5 AI-verified challenges for this lesson

Related lessons:Chain Of Thought Question Answering

This lesson is part of a structured LLM course.

My Learning Path