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ERIA: An Instruction-Optimized Agent for Clinical EEG Reporting — arXiv:2611.01394

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.01394
License (as archived): CC0-1.0
Archived: 2026-11-03T11:06:17.681Z
SHA-256 of the archived text: 8992cbb9aff48ae4e373205437ec90eef27d48c00ae0ad78a5ecc4b3c20e1203
Stable URL of this page: https://metraipolis.com/documento/dc_2bbbd33ce085

How to cite

ERIA: An Instruction-Optimized Agent for Clinical EEG Reporting — arXiv:2611.01394 — arXiv (en), https://arxiv.org/abs/2611.01394 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_2bbbd33ce085 (Metraipolis archive dc_2bbbd33ce085, sha256 8992cbb9aff48ae4e373205437ec90eef27d48c00ae0ad78a5ecc4b3c20e1203)

BibTeX

@misc{dc2bbbd33ce085,
  title = {ERIA: An Instruction-Optimized Agent for Clinical EEG Reporting — arXiv:2611.01394},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.01394},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_2bbbd33ce085; sha256 8992cbb9aff48ae4e373205437ec90eef27d48c00ae0ad78a5ecc4b3c20e1203},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.01394. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Clinical EEG interpretation requires integrating technical quality, background and behavioral states, interictal and ictal abnormalities, and overall clinical context across long recordings. We introduce ERIA (EEG Reporting and Instruction-Optimized Agent), a locally deployable framework in which a single 27B language-model controller analyzes whole-recording EEGs by orchestrating specialized parametric and signal-processing tools. ERIA combines learned tools for background abnormality, sleep-wake state, seizure-like activity, and interictal epileptiform discharges with deterministic spectral, amplitude, symmetry, montage, and signal-quality analyses. Rather than fine-tuning the controller or using multi-agent orchestration, ERIA keeps the controller weights, specialist tools, and safety constraints fixed and optimizes only its natural-language analysis policy with GEPA (Genetic-Pareto), using feedback from expert-written EEG reports. GEPA improves physician-aligned whole-recording report quality over the raw policy, and the optimized policy transfers to external EEG benchmarks. On CerebraGloss-Bench and BrainBench Foundational Analysis, ERIA remains competitive with the models evaluated in the original benchmarks. These results show that specialist tools and language-level policy optimization can extend the clinical and general EEG capabilities of a single locally executable model while preserving local inference and traceable tool use.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.AI, nuovi lavori del giorno).
Categorie arXiv: Machine Learning (cs.LG) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2611.01394 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-03T10:59:46.010Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).