Longtimescope: Long-Video Data for Multimodal Model Exploration

Longtimescope is a dataset for exploring long-video understanding with large multimodal models, as referenced in the Apollo2 research paper. The dataset was created by the Apollo-LMMs team and was last updated on the Hugging Face platform in January 2026. Its specific size, format, and content details are not provided in the available metadata.

Use Cases

• Benchmarking long-video understanding capabilities of multimodal models based on the dataset's focus.
• Training models for temporal reasoning in videos based on the 'Longtimescope' title and platform tags.
• Exploring the 'long-video frontier' of AI, as mentioned in the associated research citation.

Strengths

• Associated with a specific research paper (Apollo2) published in 2025, providing academic context.
• Last updated on 2026-01-17, indicating recent maintenance on the hosting platform.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count, file formats, and column-level documentation are absent, which may limit suitability assessment.

Provenance

Source

Apollo-LMMs team, hosted on Hugging Face.

Freshness

Last updated 2026-01-17 04:35:44; freshness should be verified.