Qi Yang

Pretrained visual encoders are a temporary crutch: encoder-free multimodal architectures close the performance gap with encoder-based systems at roughly $10^{22}$ FLOPs, well within current frontier pretraining budgets.

Depth integration in audio-visual segmentation leads to over 10% performance gains, revealing a critical yet overlooked modality in multimodal perception.

Evolving Meta-Skills enables automatic Multi-Agent Systems to achieve superior performance without sacrificing experience retention or scalability.

A 440MB multilingual translation model now rivals commercial APIs, opening the door for performant on-device translation.