"von-read team on AMD AI League Hackathon"

von-read combines exact OCR and evidence-grounded RAG on AMD ROCm. Built solo by Joseph Ayanda with AI assistance. MC2 remains R16. It preserves the selected R12 weights/runtime and changes only the verified input decoder. A paired AMD source test recovered 5/5 authored format probes versus 0/5 previously, while the public development readings stayed unchanged. Its 40.24 GB image passed fresh anonymous delivery and container-interface checks. MC3 is now R61, a source-only hardening layer over the selected R35/R24 Qwen3-VL image. Model weights and the 27 R35 parent filesystem layers are preserved. R61 adds stricter condition/property grounding, premise-safe citation minimization, mixed current/withdrawn record handling, merged DOCX scope, bounded PDF parsing, Python literal authority, and exact-output guards. Fresh paired native evaluation on an AMD MI300X VF used the same pinned production reader/checkpoint and a predeclared 58-question suite: official 10 + stress 12 + transfer 36. R35 scored 34/58; R61 scored 58/58, rescuing 24 cases with zero regressions. Both were 10/10 on the official public MC3 sample. R61 also passed 426/426 software tests on Python 3.12 and 3.14. The exact R61 OCI image is manifest sha256:0205651ae7d2806d3286a22270b5d7e23f1ec3f8ac47ed7352a719feca2e6b07. A fresh anonymous production Docker pull verified 28 layers and 40.302 GB uncompressed. These are native source-path and transport/container checks, not a hidden grader score. Full-container AMD grader self-check remains a separate limitation. Video: https://josephmayo.site/research/von-read/walkthrough.html