CoMM: Coherent Interleaved Image-Text Dataset

CoMM is a high-quality dataset designed to improve the coherence, consistency, and alignment of multimodal content. The dataset was created by author weisuxi and was last updated on 2026-04-24. It sources raw data from diverse origins, focusing on instructional content and visual storytelling.

Use Cases

• Train models for multimodal content alignment based on the described focus on coherence and consistency.
• Benchmark visual storytelling models using the dataset's focus on narrative content.
• Develop instructional AI assistants based on the dataset's inclusion of instructional content.

Strengths

• Designed specifically for high-quality coherence, consistency, and alignment of multimodal content.
• Sources data from diverse origins, which likely contributes to variety.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last updated 2026-04-24 09:12:40; freshness should be verified.

Provenance

Source

huggingface

Collection Method

Sourced from diverse origins, focusing on instructional content and visual storytelling.

Freshness

Last updated 2026-04-24 09:12:40.