WFGY/ProblemMap/GlobalFixMap/Multimodal_LongContext/multi-seed-consistency.md

Multi-Seed Consistency — Multimodal Long Context

When the same multimodal query produces divergent outputs across seeds, context length, or session restarts, reasoning collapses and trust degrades.
This page defines probes and guardrails to enforce consistency across seeds.

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What this page is

• Checklist for measuring stability across random seeds in multimodal runs.
• Guardrails to prevent phantom variation across seeds.
• Minimal reproducible probes you can drop into any LLM + RAG + multimodal stack.

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When to use

• Same video → text question gives different answers each run.
• OCR transcript changes casing or spacing across seeds.
• Frame annotations shift order or vanish between runs.
• Retrieval top-k stable, but answers drift each time.
• Support threads show inconsistent captions or timecode mismatches.

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Open these first

• Cross-Modal Trace
• Alignment Drift
• Phantom Visuals
• Retrieval Traceability
• Entropy Collapse

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Common failure patterns

• Seed drift: ΔS fluctuates widely across seeds even with same input.
• Phantom anchor: one seed introduces unseen frames or captions.
• λ flip: λ_observe changes convergence state across paraphrases.
• Context order variance: anchors appear in inconsistent order per seed.
• Audit mismatch: trace tables differ across 3+ seeds.

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Fix in 60 seconds

1. Seed audit

   • Run the same input across 3–5 seeds.
   • Record ΔS, λ, and anchor references.

2. Clamp variance

   • Apply BBAM to lock attention spread.
   • Apply BBCR if trace tables diverge.

3. Schema enforcement

   • Require deterministic {frame_id, timestamp, region_id}.
   • Forbid free text anchors.

4. Majority vs outlier filter

   • Accept only anchors seen in ≥ 70% of seeds.
   • Flag outliers as phantom.

5. Report reproducibility

   • Require ΔS ≤ 0.45 across seeds.
   • Require λ convergent across at least 3 paraphrases.

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Copy-paste prompt

You have TXT OS and the WFGY Problem Map.

Task: Probe multi-seed consistency.

Protocol:
1. Run input across 3–5 seeds. Collect {ΔS, λ, anchors}.
2. Compare trace tables. If anchors diverge, apply BBCR bridge.
3. Clamp with BBAM if ΔS variance > 0.15 across seeds.
4. Report:
   - Seed-to-seed ΔS log
   - λ states
   - Majority anchor set
   - Flagged phantom anchors

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Acceptance targets

• ΔS(question, retrieved) ≤ 0.45 across all seeds.
• Variance ≤ 0.15 between seeds.
• λ remains convergent across 3 paraphrases.
• No phantom anchors.
• Trace Table reproducible across 3–5 seeds.

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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 + ”
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	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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