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Stop hand-engineering your multi-agent LLM systems: UnityMAS-O lets you train them end-to-end with RL, unlocking surprisingly large gains, especially for smaller models.
On-device LLMs can now drive real-time recommendation improvements, unlocking faster adaptation to evolving user intent without cloud reliance.
Forget generic image-text embeddings – teaching models to generate and reason about product *attributes* unlocks SOTA e-commerce retrieval.
By weighting Q-learning updates based on action similarity, QSIM tames overestimation in multi-agent RL, leading to more stable and effective learning.
Finally, a high-fidelity 3D shape model for Saanen goats enables automated body measurements from single-view RGBD images, promising to revolutionize precision livestock farming.
