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Huazhong University of Science and Technology
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MemArbiter closes the Memory-Action Gap, boosting LLM decision-making success rates by over 20% in long-horizon tasks.
LLMs can boost few-shot learning for pathology images, but only if you dynamically adapt the language priors to each image and stochastically integrate multiple "expert" descriptions.
