Xin Zhang

Forget hours-long simulations: EnergAIzer slashes GPU power estimation time to seconds while maintaining accuracy, by exploiting structured patterns in AI kernel optimizations.

Knowing the *perfect* API to use or *exact* location to edit could drastically improve SWE agent performance, but knowing the perfect regression test result? Not so much.

Real-world proactive agents can now infer latent user needs and act on them in real-time, rivaling state-of-the-art models in intent detection while maintaining low latency.

LLM agents become *less* like humans as you crank up the reasoning, unless you explicitly model value activation with a Value Verifier trained on real-world interaction data.

By combining CNNs and State Space Models, DA-Mamba achieves efficient global-local feature alignment for domain adaptive object detection, outperforming prior CNN-only and Transformer-based approaches.