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School of Computer Science, State Key Laboratory of Multimedia Information Processing, Nanjing University, Peking University, University, Hong Kong University of Science and Technology
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Decentralized robotics data can yield stronger manipulation policies than centralized training: slotting locally trained client LoRAs directly into a server MoE beats centralized PEFT on real hardware by 12.23% while slashing communication by 87%.
Confidence miscalibration in medical AI can be mitigated, leading to both higher diagnostic accuracy and improved trust in clinical applications.
Achieving a 30x speedup in inference without sacrificing action performance, Efficient-WAM redefines efficiency in embodied control models.