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A novel closed-loop framework enables multi-robot systems to achieve robust manipulation by integrating LLMs with real-time feedback mechanisms.
StreamPPG achieves real-time rPPG estimation with state-of-the-art accuracy by leveraging privileged information, overcoming the latency barriers of traditional methods.
Achieving full-stack fidelity in live simulations without sacrificing performance could revolutionize how we evaluate distributed systems before deployment.
LLMs can now autonomously validate their own bug reports with 1.3x higher accuracy and 9.8x lower false positives, thanks to a novel multi-agent framework that synthesizes, executes, and scrutinizes proof-of-concept tests.
