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129 lines
5.8 KiB
Markdown
129 lines
5.8 KiB
Markdown
# OCR Jitter — Guardrails and Fix Pattern
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **MemoryLongContext**.
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> To reorient, go back here:
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>
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> - [**MemoryLongContext** — extended context windows and memory retention](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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When OCR engines process scanned text with inconsistent spacing, width variants, or mixed character forms,
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the output may look visually correct but introduces **false token differences** that destabilize retrieval and reasoning.
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---
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## Symptoms
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- OCR transcript looks fine to the eye, but semantic retrieval drifts.
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- Words alternate between **half-width / full-width** forms.
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- Invisible characters (zero-width joiners, non-breaking spaces) trigger token mismatches.
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- Capitalization inconsistent across the same word in long transcripts.
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- Citations fail even though the snippet visually matches the source.
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---
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## Root causes
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- OCR confidence below threshold but output still accepted.
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- Normalization skipped (NFC vs NFD forms mixed).
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- Scanner artifacts (speckles, warped lines) inject invisible characters.
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- Language-specific width forms (CJK fullwidth vs ASCII halfwidth) untreated.
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- No post-processing pass to unify tokens before embedding.
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---
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## Fix in 60 seconds
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1. **Gate by confidence**
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- Drop lines with OCR confidence < 0.85.
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- Flag low-confidence tables and equations for manual review.
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2. **Normalize Unicode**
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- Convert to **NFC** form.
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- Replace non-breaking spaces with plain space.
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- Strip zero-width characters.
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3. **Unify width and case**
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- Map fullwidth and halfwidth characters consistently.
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- Apply case-folding for ASCII text.
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4. **Re-stamp clean snippets**
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- After normalization, reassign line numbers.
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- Ensure `section_id | start_line | end_line | citation` schema updated.
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5. **Verify joins**
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- Run ΔS across adjacent chunks.
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- If join ΔS ≥ 0.50, suspect hidden jitter — repeat normalization.
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---
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## Copy-paste diagnostic prompt
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```txt
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You have TXTOS and the WFGY Problem Map.
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Task: Detect and repair OCR jitter.
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Protocol:
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1. Normalize all snippets:
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- Unicode NFC
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- Strip zero-width, NBSP
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- Map fullwidth → halfwidth
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- Apply case-fold
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2. Drop snippets with OCR confidence < 0.85.
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3. Re-stamp Snippet Table with {section_id, start_line, end_line, citation}.
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4. Measure ΔS across adjacent chunks:
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- Target ≤ 0.50 at each join.
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5. Report ΔS(question, retrieved) and λ states.
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````
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---
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## Acceptance targets
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* OCR confidence ≥ 0.85 for all retained lines.
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* No mixed width or hidden characters in final text.
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* ΔS(question, retrieved) ≤ 0.45 and joins ≤ 0.50.
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* λ remains convergent across three paraphrases.
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* Snippets traceable and citations reproducible.
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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| -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- |
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) |
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| ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems |
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| ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) |
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| 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map |
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| 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis |
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| 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map |
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| 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap |
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| 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
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| 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control |
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| 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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