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Current AI agents struggle with long-horizon professional tasks, achieving only 30% success in complex GUI workflows, revealing critical gaps in their capabilities.
Normalizing flows enable stable actor-critic learning for complex stochastic control problems with jumps, opening the door to more realistic financial and economic models.
Llama-3 fine-tuned on a new dataset of counseling interactions smokes GPT-4o and Claude-3.5-Sonnet at evaluating and explaining effective responses to client resistance.
Achieve state-of-the-art collaborative perception accuracy, communication efficiency, and resilience to packet loss by directly communicating quantized point cloud indices instead of intermediate features.
