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ShopX transforms agentic shopping by seamlessly translating complex intents into item-space actions, outperforming traditional retrieval-based systems.
Training updates that improve performance in LLMs can actually degrade inference quality鈥攗nless you use the new Monotonic Inference Policy Update framework.
Achieving a 4x faster training time and up to 6.4x cost reduction for RL post-training of DiTs by effectively utilizing idle spot GPUs.
An open-source ecosystem for agentic learning, complete with a trained agent and novel policy optimization, promises to accelerate research by providing a standardized, scalable platform.
