Innovator-VL-8B-Instruct

Model Summary

Innovator-VL-8B-Instruct is a multimodal instruction-following large language model designed for scientific understanding and reasoning. The model integrates strong general-purpose vision-language capabilities with enhanced scientific multimodal alignment, while maintaining a fully transparent and reproducible training pipeline.

Unlike approaches that rely on large-scale domain-specific pretraining, Innovator-VL-8B-Instruct achieves competitive scientific performance using high-quality instruction tuning, without additional scientific text continued pretraining.

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Model Architecture

• Vision Encoder: RICE-ViT (region-aware visual representation)
• Projector: PatchMerger for visual token compression
• Language Model: Qwen3-8B-Base
• Model Size: 8B parameters

The model supports native-resolution multi-image inputs and is suitable for complex scientific visual analysis.

Training Overview

• Multimodal Alignment: LLaVA-1.5 (558K)
• Mid-training: LLaVA-OneVision-1.5 (85M)
• Instruction Tuning: High-quality multimodal and scientific instruction data (~46M)

No additional scientific text continued pretraining is applied.

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Intended Use

• Scientific image understanding and question answering
• Multimodal reasoning and analysis
• Interpretation of scientific figures, charts, and experimental results
• General-purpose vision-language instruction following

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Limitations

• The Instruct version does not explicitly optimize long-chain reasoning efficiency.
• For tasks requiring structured or token-efficient reasoning, a dedicated Thinking or RL-aligned model is recommended.

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Citation

@article{innovator-vl,
  title={Innovator-VL: A Multimodal Large Language Model for Scientific Discovery},
  year={2025}
}