---
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id: "ab5ce8e8d94643fc642ab8b34ccd1de2759440bacfc14a8fb93ea832c4e9f454"
canonical_url: "https://aidr.today/ab5ce8e8?lang=en"
title: "IntReal: A Real-World Dataset and Benchmark for Multimodal Interleaved Generation"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-10-30T00:00:00.000Z"
category: "Data"
topics: ["llm","data-engineering"]
source_urls: ["https://huggingface.co/papers/2610.38425"]
summary: "IntReal is a real-world dataset and benchmark for multimodal interleaved generation, comprising IntReal-100K with 100K samples across four categories and an evaluation suite assessing model performance across seven dimensions."
---

# IntReal: A Real\-World Dataset and Benchmark for Multimodal Interleaved Generation

> [Open the canonical story](<https://aidr.today/ab5ce8e8?lang=en>)

**Published:** 2026-10-30T00:00:00.000Z
**Category:** Data
**Topics:** llm, data\-engineering

## Summary

IntReal is a real\-world dataset and benchmark for multimodal interleaved generation, comprising IntReal\-100K with 100K samples across four categories and an evaluation suite assessing model performance across seven dimensions\.

## Sources

- [Story source](<https://huggingface.co/papers/2610.38425>)