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Explicitly teaching LVLMs to reason step-by-step with reinforcement learning unlocks state-of-the-art performance on multimodal object-entity relation extraction.
Forget opaque LLM-driven memory policies: A-MAC offers transparent, efficient control over LLM agent memory by factoring in utility, confidence, novelty, recency, and content type.
