|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: |
|
|
- OpenGVLab/InternVL3-8B |
|
|
--- |
|
|
|
|
|
[EN](README.md) | **中文** |
|
|
|
|
|
# SenseNova-SI: 探索空间智能在多模态基础模型上尺度效应 |
|
|
|
|
|
<a href="https://github.com/OpenSenseNova/SenseNova-SI" target="_blank"> |
|
|
<img alt="Code" src="https://img.shields.io/badge/SenseNova_SI-Code-100000?style=flat-square&logo=github&logoColor=white" height="20" /> |
|
|
</a> |
|
|
<a href="https://arxiv.org/abs/2511.13719" target="_blank"> |
|
|
<img alt="arXiv" src="https://img.shields.io/badge/arXiv-SenseNova_SI-red?logo=arxiv" height="20" /> |
|
|
</a> |
|
|
<a href="https://github.com/EvolvingLMMs-Lab/EASI" target="_blank"> |
|
|
<img alt="Code" src="https://img.shields.io/badge/EASI-Code-100000?style=flat-square&logo=github&logoColor=white" height="20" /> |
|
|
</a> |
|
|
<a href="https://huggingface.co/spaces/lmms-lab-si/EASI-Leaderboard" target="_blank"> |
|
|
<img alt="Leaderboard" src="https://img.shields.io/badge/%F0%9F%A4%97%20_EASI-Leaderboard-ffc107?color=ffc107&logoColor=white" height="20" /> |
|
|
</a> |
|
|
|
|
|
## 概览 |
|
|
尽管多模态基础模型已取得显著进展，但在空间智能方面仍存在明显不足。 |
|
|
本研究基于成熟的多模态基础，包括视觉理解模型（如Qwen3-VL、InternVL3）和统一理解生成模型（如Bagel），从尺度效应（Scaling）的视角构建了**SenseNova-SI系列模型**。 |
|
|
我们采用系统化方法构建了包含800万样本的SenseNova-SI-8M数据集，通过严格的空间能力分类体系培养高性能、高鲁棒性的空间能力。 |
|
|
该系列模型在多项空间智能基准测试中取得突破性表现，同时保持强大的通用多模态理解能力。 |
|
|
本研究进一步分析了数据规模的影响，揭示了多样化数据训练带来的涌现泛化能力，探讨了过拟合与语言捷径的风险，提出了空间思维链推理的初步研究，并验证了下游应用潜力。 |
|
|
SenseNova-SI是一个持续迭代的项目，所有新训练的多模态空间智能基础模型均将陆续开源，以推动空间智能领域的研究发展。 |
|
|
*后续 SenseNova-SI 将与更大规模的内部模型进行集成。* |
|
|
|
|
|
## 发布信息 |
|
|
目前，我们基于流行的开源基础模型构建 SenseNova-SI，以最大化与现有研究流程的兼容性。 |
|
|
在本次发布中，我们推出 |
|
|
[**SenseNova-SI-1.2-InternVL3-8B**](https://huggingface.co/sensenova/SenseNova-SI-1.2-InternVL3-8B), |
|
|
[**SenseNova-SI-1.1-Qwen2.5-VL-3B**](https://huggingface.co/sensenova/SenseNova-SI-1.1-Qwen2.5-VL-3B), |
|
|
[**SenseNova-SI-1.1-Qwen2.5-VL-7B**](https://huggingface.co/sensenova/SenseNova-SI-1.1-Qwen2.5-VL-7B), |
|
|
与[**SenseNova-SI-1.1-Qwen3-VL-8B**](https://huggingface.co/sensenova/SenseNova-SI-1.1-Qwen3-VL-8B)， |
|
|
其中**SenseNova-SI-1.2-InternVL3-8B**在八个近期发布的空间智能基准测试（**VSI**、**MMSI**、**MindCube**、**ViewSpatial**、**SITE**、**BLINK**、**3DSRBench**、**EmbSpatial-Bench**）上， |
|
|
在同等模型规模下均取得了开源模型的最新最优性能（state-of-the-art）。 |
|
|
|
|
|
<table> |
|
|
<thead> |
|
|
<tr> |
|
|
<th>Model</th> |
|
|
<th>VSI</th> |
|
|
<th>MMSI</th> |
|
|
<th>MindCube-Tiny</th> |
|
|
<th>ViewSpatial</th> |
|
|
<th>SITE</th> |
|
|
<th>BLINK</th> |
|
|
<th>3DSRBench</th> |
|
|
<th>EmbSpatial-Bench</th> |
|
|
</tr> |
|
|
</thead> |
|
|
<tbody> |
|
|
<tr style="background:#F2F0EF;font-weight:700;text-align:center;"> |
|
|
<td colspan="9"><em>Open-source Models (~2B)</em></td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>InternVL3-2B</td><td>32.9</td><td>26.5</td><td>37.5</td><td>32.5</td><td>30.0</td><td>50.8</td><td>47.7</td><td>60.1</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>Qwen3-VL-2B-Instruct</td><td>50.3</td><td>28.9</td><td>34.5</td><td>36.9</td><td>35.6</td><td>53.2</td><td>47.5</td><td>70.1</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>MindCube-3B-RawQA-SFT</td><td>17.2</td><td>1.7</td><td>51.7</td><td>24.1</td><td>6.3</td><td>35.1</td><td>2.8</td><td>37.0</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>SpatialLadder-3B</td><td>44.8</td><td>27.4</td><td>43.4</td><td>39.8</td><td>27.9</td><td>43.0</td><td>42.8</td><td>58.2</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>SpatialMLLM-4B</td><td>46.3</td><td>26.1</td><td>33.4</td><td>34.6</td><td>18.0</td><td>40.5</td><td>36.2</td><td>50.0</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>VST-3B-SFT</td><td>57.9</td><td>30.2</td><td>35.9</td><td>52.8</td><td>35.8</td><td>58.8</td><td>54.1</td><td>69.0</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>Cambrian-S-3B</td><td>57.3</td><td>25.2</td><td>32.5</td><td>39.0</td><td>28.3</td><td>37.7</td><td>50.9</td><td>63.5</td> |
|
|
</tr> |
|
|
<tr style="background:#F2F0EF;font-weight:700;text-align:center;"> |
|
|
<td colspan="9"><em>Open-source Models (~8B)</em></td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>InternVL3-8B</td><td>42.1</td><td>28.0</td><td>41.5</td><td>38.6</td><td>41.1</td><td>53.5</td><td>44.3</td><td>76.4</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>Qwen3-VL-8B-Instruct</td><td>57.9</td><td>31.1</td><td>29.4</td><td>42.2</td><td>45.8</td><td>66.7</td><td>53.9</td><td>77.7</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>BAGEL-7B-MoT</td><td>31.4</td><td>31.0</td><td>34.7</td><td>41.3</td><td>37.0</td><td>63.7</td><td>50.2</td><td>73.1</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>SpaceR-7B</td><td>41.5</td><td>27.4</td><td>37.9</td><td>35.8</td><td>34.2</td><td>49.6</td><td>40.5</td><td>66.9</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>ViLaSR-7B</td><td>44.6</td><td>30.2</td><td>35.1</td><td>35.7</td><td>38.7</td><td>51.4</td><td>46.6</td><td>67.3</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>VST-7B-SFT</td><td>60.6</td><td>32.0</td><td>39.7</td><td>50.5</td><td>39.6</td><td>61.9</td><td>54.6</td><td>73.7</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td>Cambrian-S-7B</td><td>67.5</td><td>25.8</td><td>39.6</td><td>40.9</td><td>33.0</td><td>37.9</td><td>54.8</td><td>72.8</td> |
|
|
</tr> |
|
|
<tr> |
|
|
<td><strong>SenseNova-SI-1.2-InternVL3-8B</strong></td> |
|
|
<td><strong>69.6</strong></td> |
|
|
<td><strong>42.6</strong></td> |
|
|
<td><strong>89.0</strong></td> |
|
|
<td><strong>58.8</strong></td> |
|
|
<td><strong>49.0</strong></td> |
|
|
<td><strong>69.4</strong></td> |
|
|
<td><strong>60.1</strong></td> |
|
|
<td><strong>77.7</strong></td> |
|
|
</tr> |
|
|
<tr style="background:#F2F0EF;color:#6b7280;font-weight:600;text-align:center;"> |
|
|
<td colspan="9"><em>Proprietary Models</em></td> |
|
|
</tr> |
|
|
<tr style="color:#6b7280;"> |
|
|
<td>Gemini-2.5-pro-2025-06</td><td>53.5</td><td>38.0</td><td>57.6</td><td>46.0</td><td>57.0</td><td>73.5</td><td>59.3</td><td>78.9</td> |
|
|
</tr> |
|
|
<tr style="color:#6b7280;"> |
|
|
<td>Grok-4-2025-07-09</td><td>47.9</td><td>37.8</td><td>63.5</td><td>43.2</td><td>47.0</td><td>56.4</td><td>54.9</td><td>75.7</td> |
|
|
</tr> |
|
|
<tr style="color:#6b7280;"> |
|
|
<td>GPT-5-2025-08-07</td><td>55.0</td><td>41.8</td><td>56.3</td><td>45.5</td><td>61.8</td><td>68.0</td><td>60.3</td><td>81.6</td> |
|
|
</tr> |
|
|
</tbody> |
|
|
</table> |
