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Recursive belief updates in AgentOPSD reveal pivotal decision points, leading to a 89.1% success rate on complex RL tasks.
Fine-tuning a general grounding model on a newly constructed dataset boosts medical localization accuracy from 10.64 to 85.59, showcasing the power of domain-specific supervision.
SkillRise achieves up to 8.5 percentage points better performance than leading methods by effectively reusing transferable skills across related tasks.
InkShield reduces the risk of handwriting forgery by over 90% while keeping the original style visually intact.
MASTE achieves zero-shot Aspect Sentiment Triplet Extraction with a multi-agent approach that outperforms traditional LLM methods, even without labeled data.
