Wei-Shi Zheng

Generative models can be surprisingly effective for texture filtering when fine-tuned with a two-stage supervised and reinforcement learning approach.

Multi-frame monocular scene flow estimation gets a serious boost with RAFT-MSF++, which uses Geometry-Motion Feature fusion to achieve state-of-the-art results and improved robustness to occlusions.

Forget trajectory forecasting – TacticGen generates *adaptable* football tactics, bridging the gap between predicting what *will* happen and prescribing what *should* happen to win.

Generating coordinated bimanual grasps on diverse objects is now possible thanks to a dataset of nearly 10 million grasps and a model that adapts to object geometry and size.

LLMs can maintain generation quality in long-context scenarios while using significantly less context, simply by adaptively allocating context based on uncertainty.

Achieve 85% zero-shot dexterous grasping success on unseen robot hands by learning a universal policy aligned to hand morphology, blowing away prior work by nearly 60%.

End-to-end autonomous driving can ditch expert demonstrations and still achieve state-of-the-art performance, thanks to a risk-aware world model that learns to predict and avoid hazardous outcomes.

Forget ad-hoc VLA design: here are 12 key ingredients, validated in a unified framework, for building performant Vision-Language-Action models.