DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data
3.40T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.05375.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryDoctorAgents is a multi-agent LLM framework that replaces brute-force AutoML search with reasoning-driven pipeline construction for small clinical temporal datasets. Specialized agents handle generation, validation, and refinement, using textual gradient descent to propagate natural-language feedback. Experiments show it outperforms standard AutoML baselines.
Why it mattersConcrete example of a multi-agent refinement loop (textual gradient descent) applied to a real domain. Useful pattern to study if building agent pipelines for structured, low-data tasks.
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