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Typed Decision Models: An Early Evidence Audit and Evaluation Checklist — arXiv:2609.32160

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.32160
License (as archived): CC0-1.0
Archived: 2026-10-07T20:59:53.413Z
SHA-256 of the archived text: 3322485ecf481586185edff1f955747d09fc52995658b194de781b279c69c7a7
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How to cite

Typed Decision Models: An Early Evidence Audit and Evaluation Checklist — arXiv:2609.32160 — arXiv (en), https://arxiv.org/abs/2609.32160 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_99acf36dfd6c (Metraipolis archive dc_99acf36dfd6c, sha256 3322485ecf481586185edff1f955747d09fc52995658b194de781b279c69c7a7)

BibTeX

@misc{dc99acf36dfd6c,
  title = {Typed Decision Models: An Early Evidence Audit and Evaluation Checklist — arXiv:2609.32160},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.32160},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_99acf36dfd6c; sha256 3322485ecf481586185edff1f955747d09fc52995658b194de781b279c69c7a7},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.32160. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Typed decision models (TDMs) return probability distributions over caller-defined options without generating text. TypeSafe released Jev, a commercial typed decision model, on 15 September 2026, and a small body of evaluation and replication work appeared within days. We review 28 papers posted between 19 and 24 September and relate their findings to earlier work on label-probability classification, constrained decoding, reranking, calibration, and model cascades. In this early literature, the typed readout itself has not shown an independent accuracy advantage over comparable label-probability readouts. Jev's clearest gains are in latency and cost, while accuracy gaps remain on harder tasks. In practical deployments, confidence is often used to decide when to defer to a stronger model or a human. We use recurring weaknesses in these studies to derive a 14-item evaluation checklist for future TDM work. Because the evidence covers only the first nine days after the release of one hosted model, the review should be read as an early evidence map rather than a settled assessment of the model class.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-29 in cs.AI).
Categorie arXiv: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI); Machine Learning (cs.LG).
Pagina del lavoro: https://arxiv.org/abs/2609.32160 — 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 2026-10-07T20:29:02.236Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-09-29?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).