From Sampled Evidence to Radiology Reports: Objectives, Constraints, and Realization

Key points

• We study these questions through a framework that separates the decision signal, scoring objective, and feasible decision set, followed by text realization.1
• On MIMIC-CXR and IU-Xray, controlled comparisons across 13 generator configurations per benchmark under grouped development/test evaluation reveal three findings.1
• Diagnostics connect the IU macro-oriented assertion increase to near-zero label thresholds and show that limited candidate coverage coexists with selection headroom.1
• Change decomposition reveals that realization can remove incorrect assertions while losing correct findings, so target fidelity and reference accuracy need not improve together.1

Sources (1)

• [1]From Sampled Evidence to Radiology Reports: Objectives, Constraints, and Realization
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 12, 07:19 PM

  Sampling multiple reports creates an inference problem: how should sampled evidence be converted into a final decision, and does a better structured decision yield a better report?

  We study these questions through a framework that separates the decision signal, scoring objective, and feasible decision set, followed by text realization.

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