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Affiliation:, The Hong Kong University of Science and Technology, Huawei
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RideSkill revolutionizes ride-sharing by enabling real-time adaptive dispatch without the overhead of constant LLM calls, enhancing both efficiency and scalability.
Independent policy composition in multi-agent systems can lead to worse outcomes than any individual policy in the library, challenging conventional wisdom in reinforcement learning.
Normalizing dual-encoder networks not only clarifies their interpretability but also reveals hidden structure in learned representations, challenging existing assumptions in the field.
Aggregating rewards in the advantage while keeping likelihood ratios per-agent can significantly enhance cooperative multi-agent learning performance.
Automating stage lighting control across diverse venues is now possible without expert demonstrations, thanks to a novel imitation learning approach that decomposes global color distributions into individual light controls.
