🧭 Quick Return to Map
You are in a sub-page of Multimodal_LongContext.
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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 spatial information from different modalities (text, image, video, 3D layout) is fused incorrectly,
the model builds a distorted scene map. This results in answers that are locally fluent but spatially wrong.
- A repair map for spatial mis-fusion across long multimodal windows.
- Structural checks that keep anchors aligned in 2D/3D space.
- Copy-paste prompts to enforce spatial traceability in multimodal RAG.
- Text says "object A is left of object B" but visual encoder aligns them oppositely.
- Bounding boxes overlap or merge, losing spatial independence.
- 3D → 2D projection mismatch: captions reference an object that isn’t in frame.
- Video QA drifts: same entity appears in different spots across time.
- Answers mention correct objects but wrong spatial relations (left/right, inside/outside, above/below).
- Axis flip — left/right or up/down swapped.
- Projection drift — 3D object references collapse to wrong 2D bounding box.
- Overlap collapse — two entities share the same spatial slot.
- Cross-modal mismatch — text anchor doesn’t correspond to visual bounding box.
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Spatial schema lock
- Represent anchors as
{id, coords(x,y,z), frame_id}. - Reject answers missing explicit spatial schema.
- Represent anchors as
-
ΔS probe across modalities
- Compute ΔS(text_anchor, visual_anchor).
- If ΔS ≥ 0.60, suspect fusion error.
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Spatial IoU check
- Enforce IoU ≥ 0.7 for same anchor across modalities.
- If < 0.7, assign new anchor ID.
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Stabilize with BBCR
- Bridge text ↔ visual mismatch with constraint re-anchoring.
- Clamp variance with BBAM.
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Trace audit
- Log
{anchor_id, modality, coords, IoU}. - Require cite-then-answer with explicit anchor IDs.
- Log
You have TXT OS and the WFGY Problem Map.
Task: Detect and repair spatial fusion errors across modalities.
Steps:
1. Verify each anchor has {id, coords(x,y,z), frame_id}.
2. Compute IoU across modalities. If IoU < 0.7, treat as mismatch.
3. Probe ΔS across text and visual anchors.
4. Apply BBCR if drift detected, else assign new ID.
5. Return:
- stable anchors
- mismatched anchors
- ΔS values and λ states
- corrected spatial map- 100% anchors represented with explicit
{id, coords, frame_id}. - Cross-modal IoU ≥ 0.7 after fix.
- ΔS(text, visual) ≤ 0.45.
- λ remains convergent across paraphrases.
- No axis flip errors across test prompts.
| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + ” |
| 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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