Jiang Liu

Ophthalmic VQA models can be made more accurate and transparent by explicitly grounding them in spatially-localized lesion evidence, a crucial step towards clinical interpretability.

Ruyi2.5 achieves comparable performance to Qwen3-VL on general multimodal benchmarks while significantly outperforming it in privacy-constrained surveillance, demonstrating the effectiveness of its edge-cloud architecture.

You can now get illustrative visual references from surveillance systems in sensitive environments without exposing raw images, thanks to a novel privacy-preserving perception framework.

Stop trading off fidelity for visual quality in super-resolution: a new network learns to directly optimize for human-preferred aesthetics.

A new unified LVLM, OmniCT, bridges the gap between slice-level detail and volumetric understanding in CT scans, outperforming existing methods by a significant margin.