# arXiv Update Notes for ZeroProofML v0.4.0

- **Title suggestion:** "ZeroProofML v0.4: Signed Common Meadows for Stable Rational Learning"
- **Abstract hooks:**
  - Replace transreal arithmetic with signed common meadows featuring an absorptive bottom `⊥`.
  - Optional projective training mode with detached renormalization keeps gradients smooth while preserving strict SCM decoding.
  - Coverage-aware loss stack (implicit, margin, sign consistency, rejection) and adaptive sampling for singular regimes.
- **Key results to highlight:**
  - Regression tests show parity with v0.3 on regular inputs while improving stability near poles.
  - Coverage convergence experiments and robotics IK benchmarks with sign-sensitive targets.
- **Artifacts:** point to PyPI package `zeroproofml==0.4.0`, documentation index, and the blog announcement.
- **Next steps:** submit updated PDF to arXiv after final proofing and mirror the abstract on the project landing page.
