NRR-Phi: Text-to-State Mapping for Ambiguity Preservation in LLM Inference

NRR-Phi defines text-to-state mapping for ambiguity-preserving inference in LLM systems. The focus is preventing premature commitment in LLM decoding when inputs carry competing interpretations, then deciding defer vs commit with explicit conditions. Instead of forcing a single parse too early, the pipeline keeps multiple candidates in state form so later context can resolve them without unnecessary backtracking. This repository contains reproducibility code, operator-validation assets, and public-track manuscript mapping for the NRR series. It targets measurable handling of lexical, structural, and epistemic ambiguity and the reduction of semantic collapse in practical inference workflows. The intent is implementation clarity: explicit extraction stages, auditable artifacts, and clear limits on what the mapping does not claim to solve.

Quick links

• arXiv: 2601.19933
• Positioning (NRR vs related approaches)
• Search Keywords and Weekly Rank Log

EN/JA query terms

• early commitment = 早期確定
• ambiguity-preserving inference = 曖昧性保持推論

Part of the Non-Resolution Reasoning (NRR) research program.

NRR Series Hub (Start here)

For the cross-paper map and current series links, start here:

• NRR Series Hub

Version mapping source of truth: VERSION_MAP.md

NRR is not an anti-LLM framework. NRR does not replace standard LLM use. NRR optimizes when to commit and when to defer, under explicit conditions. Series numbering policy: paper3 is permanently skipped and never reused.

DOI

Repository Structure

nrr-phi/
├── src/
│   ├── __init__.py
│   ├── state.py
│   ├── phi_mapping.py
│   └── conflict_detection.py
├── data/
│   ├── rule_based_data.json
│   └── operator_validation_states.json
├── results/
│   ├── rule_based_output.json
│   └── operator_validation_results.json
├── experiments/
│   ├── rule_based_experiment.py
│   └── run_operator_validation.py
├── prompts/
├── notebooks/
├── manuscript/
│   ├── current/
│   │   ├── paper2_nrr-phi_v38.tex
│   │   ├── figure1.png ... figure5.png
│   │   └── checksums_sha256.txt
│   └── archive/
│       ├── public-v25/
│       ├── local-v37/
│       └── local-v36/
├── scripts/
│   └── verify_versions.sh
├── VERSION_MAP.md
├── reproducibility.md
├── requirements.txt
├── README.md
└── LICENSE

Manuscript Artifacts

Published baseline and local archive mapping is maintained in VERSION_MAP.md.

• Current public arXiv line: 2601.19933v4
• Current public source snapshot in repo: manuscript/current/paper2_nrr-phi_v38.tex
• Archived public baseline snapshot: manuscript/archive/public-v25/paper2_nrr-phi_v25.tex
• Archived local draft snapshot: manuscript/archive/local-v37/paper2_nrr-phi_v37.tex

Version Verification

./scripts/verify_versions.sh

Stable review-package entrypoints:

• bash scripts/build_current_manuscript.sh
• bash scripts/verify_current_package.sh
• bash scripts/run_primary_checks.sh

Quick Start

pip install -r requirements.txt
python3 experiments/rule_based_experiment.py > results/rule_based_output.json
python3 experiments/run_operator_validation.py \
  --data data/operator_validation_states.json \
  --output results/operator_validation_rerun_summary.json

Reproducibility

See reproducibility.md for environment, fixed settings, commands, and artifact mapping.

Related Repositories

• NRR-Core
• NRR-IME
• NRR-Transfer

Collaboration Style

I support written technical Q&A, concept clarification, and small evaluation design.

Typical flow:

1. you send questions and context,
2. I return a structured technical response,
3. if needed, I provide an English-ready version for external sharing.

Scope: research interpretation and evaluation planning.
Out of scope: production integration, implementation outsourcing, ongoing operations, and SLA/deadline commitments.
Contact: kei.saito.research@gmail.com

License

CC BY 4.0. See LICENSE.