A framework elicits discriminative MRF statistics from an LLM and closes the model via maximum entropy to enable zero-shot active feature acquisition, outperforming baselines on IBD patient data especially for hardest cases.
Classification with costly features using deep reinforcement learning.Proceedings of the AAAI Conference on Artificial Intelligence, 33(01): 3959–3966, 2019
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Zero-Shot Active Feature Acquisition via LLM-Elicitation
A framework elicits discriminative MRF statistics from an LLM and closes the model via maximum entropy to enable zero-shot active feature acquisition, outperforming baselines on IBD patient data especially for hardest cases.