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Synthetic heart sounds generated by a diffusion model retain classification accuracy but miss critical abnormal acoustic features, highlighting a gap in current generation techniques.
Agricultural VLN agents struggle with instruction mistakes, showing a staggering 57% drop in success rates when faced with realistic errors.
Current AI models for liver fibrosis staging can match expert radiologists in some settings, but real-world clinical deployment is still hampered by data heterogeneity and label imbalance.
Humanoid states, not low-level actions, are the key to unlocking text-driven control, enabling a diffusion model to generate more natural and semantically aligned behaviors.
Forget centralized parameter servers: Totoro$^+$'s decentralized architecture lets you run massive federated learning applications simultaneously on edge networks, scaling gracefully and adapting to network churn.
Stop LLMs from drifting to English when reasoning in other languages: language-adaptive RL can guide them to stay consistent without sacrificing performance.
