Spatial Fusion Error — Multimodal Long Context

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.

What this page is

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.

When to use

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).

Open these first

Common failure patterns

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.

Fix in 60 seconds

Spatial schema lock
- Represent anchors as {id, coords(x,y,z), frame_id}.
- Reject answers missing explicit spatial schema.
ΔS probe across modalities
- Compute ΔS(text_anchor, visual_anchor).
- If ΔS ≥ 0.60, suspect fusion error.
Spatial IoU check
- Enforce IoU ≥ 0.7 for same anchor across modalities.
- If < 0.7, assign new anchor ID.
Stabilize with BBCR
- Bridge text ↔ visual mismatch with constraint re-anchoring.
- Clamp variance with BBAM.
Trace audit
- Log {anchor_id, modality, coords, IoU}.
- Require cite-then-answer with explicit anchor IDs.

Copy-paste prompt

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

Acceptance targets

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.

🔗 Quick-Start Downloads (60 sec)

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

🧭 Explore More

Module	Description	Link
WFGY Core	WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack	View →
Problem Map 1.0	Initial 16-mode diagnostic and symbolic fix framework	View →
Problem Map 2.0	RAG-focused failure tree, modular fixes, and pipelines	View →
Semantic Clinic Index	Expanded failure catalog: prompt injection, memory bugs, logic drift	View →
Semantic Blueprint	Layer-based symbolic reasoning & semantic modulations	View →
Benchmark vs GPT-5	Stress test GPT-5 with full WFGY reasoning suite	View →
🧙‍♂️ Starter Village 🏡	New here? Lost in symbols? Click here and let the wizard guide you through	Start →

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