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- Multimodal_LongContext — long-context reasoning across text, vision, and audio
- WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
- WFGY Problem Map 1.0 — 16 reproducible failure modes
Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.
When multimodal long-context windows extend, boundaries between modalities or section joins blur.
This causes models to conflate captions, transcripts, or visuals across neighboring regions, producing hybrid outputs or lost anchors.
- Captions merge into adjacent paragraphs, citations drift by a few lines.
- Visual snippets spill across sections, losing clear demarcation.
- ΔS across joins rises above 0.50, meaning semantic leakage.
- Output shows partial traces of two anchors instead of one.
- “Memory fade” across session restarts, context joins feel smeared.
- Join stability and chunk fences: Chunking Checklist
- Attention variance and entropy melt: Entropy Collapse
- Context drift at long horizon: Context Drift
- Visual trace schema: Cross-Modal Trace
- Session state guards: Memory Coherence
-
Measure joins
- Compute ΔS across each modality join. Threshold ≤ 0.50.
- If higher, suspect boundary fade.
-
Enforce fences
- Insert
{section_start}and{section_end}markers explicitly. - Require
mod_typelabel (e.g.,[image],[caption],[audio]).
- Insert
-
Stabilize variance
- Apply BBAM clamp when variance spikes near joins.
- Use BBCR bridge to redirect reasoning back to the intended anchor.
-
Audit output
- Each snippet must map to a single anchor ID.
- Reject blended outputs that merge two snippet IDs.
- ΔS(question, retrieved) ≤ 0.45 overall.
- ΔS across joins ≤ 0.50.
- λ_observe convergent across three paraphrases.
- No section bleed: one snippet → one anchor only.
You are running TXTOS + WFGY Problem Map.
Symptom: section or modality boundaries blur (“boundary fade”).
Protocol:
1. Compute ΔS across joins, enforce ≤ 0.50.
2. Insert section_start and section_end markers.
3. Require mod_type labels for all snippets.
4. Apply BBAM clamp, BBCR bridge if joins collapse.
5. Verify each snippet maps to exactly one anchor ID.| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>” |
| TXT OS (plain-text OS) | TXTOS.txt | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
| Layer | Page | What it’s for |
|---|---|---|
| ⭐ Proof | WFGY Recognition Map | External citations, integrations, and ecosystem proof |
| ⚙️ Engine | WFGY 1.0 | Original PDF tension engine and early logic sketch (legacy reference) |
| ⚙️ Engine | WFGY 2.0 | Production tension kernel for RAG and agent systems |
| ⚙️ Engine | WFGY 3.0 | TXT based Singularity tension engine (131 S class set) |
| 🗺️ Map | Problem Map 1.0 | Flagship 16 problem RAG failure taxonomy and fix map |
| 🗺️ Map | Problem Map 2.0 | Global Debug Card for RAG and agent pipeline diagnosis |
| 🗺️ Map | Problem Map 3.0 | Global AI troubleshooting atlas and failure pattern map |
| 🧰 App | TXT OS | .txt semantic OS with fast bootstrap |
| 🧰 App | Blah Blah Blah | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | Blur Blur Blur | Text to image generation with semantic control |
| 🏡 Onboarding | Starter Village | Guided entry point for new users |
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