> ## Documentation Index
> Fetch the complete documentation index at: https://www.getmaxim.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# ROUGE-Lsum

> Adapts ROUGE-L for multi-sentence texts by computing a summary-level longest common subsequence (LCS) score, suitable for document-level evaluation.

### Input

* **`output`** (str): The generated multi-sentence text
* **`expectedOutput`** (str): The reference multi-sentence text

### Output

* **`Result`** (float): A score between 0 and 1.

## Interpretation

* **Higher scores (closer to 1)**: Stronger document-level structural similarity
* **Lower scores (closer to 0)**: Weak structural similarity across sentences

### How It Works

ROUGE-Lsum computes the LCS for each sentence in the reference against each sentence in the generated text and sums the results, capturing matching subsequences across the entire document.

#### Example (Conceptual)

* Reference has 3 sentences; candidate has 3 sentences
* Compute LCS per sentence pair and sum normalized scores
* Final score reflects overall structural similarity across sentences

<Note>This is a **Similarity** Metric</Note>

## Use Cases

* Evaluating multi-sentence abstractive summaries
* Document-level machine translation assessment