Xiaomi AI Lab Introduces Xiaomi-Lens-0: 4B MLLM Built on Qwen3.5 Sets SOTA on RefCOCO with Native Pixel-Level Mask Decoding
Multimodal LLMs excel at holistic image captioning but struggle with pixel-level spatial grounding due to lack of spatial supervision. Xiaomi AI Lab unveiled Xiaomi-Lens-0 (arXiv:2610.23279), a 4B MLLM based on Qwen3.5 that natively predicts pixel masks. A lightweight decoder integrates patch embeddings, visual latents, and mask-token activations, driving RefCOCO comprehension (REC [email protected]: 94.6% / 92.1% / 92.5%) and segmentation (RES cIoU: 83.4% / 79.9% / 81.1%) past Florence-2 and LISA-7B while preserving a 69.7% MME-RW score.
Key Takeaways
- Xiaomi AI Lab released Xiaomi-Lens-0 (arXiv:2610.23279), a 4B MLLM based on Qwen3.5 that natively generates pixel-level masks
- Outperforms Florence-2 and Grounding-DINO-L on RefCOCO/RefCOCO+/RefCOCOg REC benchmarks with 94.6%, 92.1%, and 92.5% [email protected]
- Achieves 83.4% / 79.9% / 81.1% cIoU on RES segmentation, substantially surpassing 7B models like LISA and GSVA
- Maintains superior general perception, scoring 69.7% on MME-RW-en and outperforming Qwen2.5-VL 7B
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