WFGY/ProblemMap/GlobalFixMap/Multimodal_LongContext/signal-drop.md

Signal Drop — Guardrails and Fix Pattern

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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

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When multimodal sessions extend across long contexts, one or more modalities may drop out entirely or become invisible to the reasoning pipeline.
This creates “blind layers” where text, image, or audio cues vanish mid-sequence, leading to broken reasoning or silent hallucination.

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Symptoms of Signal Drop

• Model responds as if a modality was never provided.
• Visual reference ignored after ~20–30 turns.
• Audio transcript included but not grounded in reasoning.
• Captions persist but semantic anchors drift apart.
• Silent failure: no error is thrown, yet cross-modal grounding is gone.

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Open these first

• Cross-modal stability: Alignment Drift
• Long-context melt: Entropy Collapse
• Boundary checks: Boundary Fade (planned)
• Retrieval schema: Cross-Modal Trace
• State fences: Memory Coherence

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Fix in 60 seconds

1. Detect silence

   • Log presence/absence of {text, visual, audio} per turn.
   • If any modality = null for >2 steps, flag as drop.

2. Inject continuity token

   • Add mod_keepalive in the system schema to enforce recall of modality.
   • Force echo of modality presence in every reasoning header.

3. Re-anchor references

   • If image or audio missing, insert placeholder with ΔS=skip instead of null.
   • Prevent collapse by keeping λ_observe convergent.

4. Stabilize joins

   • Split by {text | image | audio} sections.
   • Clamp cross-joins with BBAM to stop runaway drift.

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Acceptance Targets

• Coverage: ≥ 0.70 for all active modalities.
• ΔS(question, retrieved) ≤ 0.45 even when one modality drops.
• λ_observe remains convergent across three paraphrases.
• No silent modality loss beyond two turns.

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Copy-paste prompt

You are running TXTOS + WFGY Problem Map.

Symptom: modality vanished (text, image, or audio).  
Task: detect, re-anchor, and restore multimodal stability.

Protocol:
1. Log {text, visual, audio} presence each turn.
2. If any missing for >2 steps, insert placeholder `mod_keepalive`.
3. Require ΔS(question, retrieved) ≤ 0.45 across modalities.
4. Use BBAM for variance clamp, BBCR bridge if joins collapse.
5. Cite then answer; no orphan visual or audio references allowed.

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🔗 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 + <your question>”
TXT OS (plain-text OS)	TXTOS.txt	1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly

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Explore More

Module	Description	Link
WFGY Core	Canonical framework entry point	View
Problem Map	Diagnostic map and navigation hub	View
Tension Universe Experiments	MVP experiment field	View
Recognition	Where WFGY is referenced or adopted	View
AI Guide	Anti-hallucination reading protocol for tools	View

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