feat: implement rate-resilient multi-modal claims verification model … - #5
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…and package final output
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…view (#5) * research(prior-art): hosted-VLM claim verification landscape + recommendations Prior-art pass (researcher agent) across threads T0-T7: broad damage/evidence verification, VLM damage assessment, perception-before-judgment, structured output enforcement, image prompt-injection, cross-image identity, small-set eval methodology, hosted VLM landscape. Maps recommendations to design.md section 8 open decisions + the escalation menu; lists 10 eval hypotheses. Scoped to our constraints (small data; minimal-setup reproducibility; provider/language open). Refs cbeaulieu-gt/hackerrank-orchestrate-june26-prv#3. Also appends transcript log entries for the dispatch + research turn. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * research(probe-sets): small labeled defect probe set for offline VLM grading Follow-up scan to the prior-art pass: where to source images with known defect labels for dev-time perception calibration + provider selection (not label validation; not a runtime dependency). Cars covered by an MIT HuggingFace drop-in (DrBimmer/car-parts-and-damage-dataset); package only coarse public labels (Roboflow IoT Project); laptop, authenticity, and cross-image identity have no usable public set -> small self-built proposals. Bottom line: ~60-90 min to assemble ~150 labeled probe images. Refs cbeaulieu-gt/hackerrank-orchestrate-june26-prv#4. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
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…and package final output