SenseNova-SI-800K: Multimodal Training Data for Spatial Intelligence

SenseNova-SI-800K is a dataset created by SenseNova to address deficiencies in spatial intelligence for multimodal foundation models. It is built upon established models like Qwen3-VL and InternVL3 and was last updated on December 23, 2025. The dataset is hosted on Hugging Face and is categorized as containing between 100K and 1M entries.

Use Cases

• Fine-tuning visual-language models for spatial reasoning tasks based on the dataset's focus on spatial intelligence.
• Benchmarking the spatial understanding capabilities of multimodal AI models.
• Training models for visual question answering tasks that require spatial awareness.

Strengths

• Dataset is explicitly designed to address a known research gap in spatial intelligence for multimodal AI.
• Built upon established and recognized foundation models like Qwen3-VL and InternVL3.
• Last update timestamp is recent (2025-12-23).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The full description is truncated, requiring a visit to the dataset page for complete details.

Provenance

Source

SenseNova

Collection Method

Built upon established multimodal foundation models; specific gathering method is not detailed in the provided description.

Time Range

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Freshness

Last updated 2025-12-23 15:33:26

Geography

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