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127 lines
6.3 KiB
Markdown
127 lines
6.3 KiB
Markdown
# Modality Swap — Multimodal Long Context
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When inputs from different modalities are accidentally swapped or misrouted (e.g., OCR output fed into caption pipeline, audio transcript aligned as video metadata), the entire reasoning chain collapses.
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This is one of the hardest multimodal errors to debug because every modality appears syntactically correct, but the semantic anchors belong to the wrong channel.
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---
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## What this page is
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- A focused repair guide for **cross-modality swap failures**.
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- How to detect modality swaps early with structural probes.
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- Guardrails to prevent silent misrouting across long-context pipelines.
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---
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## When to use
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- Captions look valid textually but describe a different video segment.
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- OCR transcript shows inside the "caption" stream, while actual captions disappear.
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- Audio embeddings drift sharply while ΔS remains low inside the wrong modality.
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- Model answers flip between describing visuals vs. reading text.
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- Citations remain “correct” but belong to the wrong modality (e.g., frame vs. page).
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---
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## Open these first
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- [Cross-Modal Trace](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/cross-modal-trace.md)
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- [Anchor Misalignment](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/anchor-misalignment.md)
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- [Phantom Visuals](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/phantom-visuals.md)
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- [Multimodal Fusion Break](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/multimodal-fusion-break.md)
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---
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## Common failure patterns
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- **OCR → Caption swap** — OCR text injected as subtitle stream.
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- **Audio → Metadata swap** — ASR transcript stored as document metadata.
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- **Caption → OCR swap** — time-stamped captions parsed into wrong page references.
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- **Silent multimodal swap** — all channels populated, but semantically wrong modality.
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- **Chained swap amplification** — one early swap causes fusion to fail downstream.
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---
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## Fix in 60 seconds
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1. **Fingerprint each modality**
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- Compute embedding signatures separately for OCR, audio, caption, and visual frames.
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- Verify signatures match expected modality domain.
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2. **Cross-modality consistency check**
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- Compare OCR tokens vs. caption words vs. audio transcript.
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- If overlap >50%, suspect swap.
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3. **Re-map against anchor modality**
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- Use video timeline or gold reference as ground truth.
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- Re-align swapped data to the correct channel.
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4. **Apply BBPF + BBCR**
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- Use BBPF (pathfinder) to re-thread the swapped modality.
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- Use BBCR bridge to anchor swapped stream back into context.
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5. **Fence schema**
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- Enforce explicit modality tags `{OCR|Caption|Audio|Visual}` in contracts.
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- Forbid ingestion without modality ID.
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---
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## Copy-paste prompt
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```txt
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You have TXT OS and the WFGY Problem Map.
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Task: Detect and correct modality swap in multimodal data.
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Steps:
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1. Fingerprint each modality stream.
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2. Compare OCR vs Caption vs Audio for abnormal overlap.
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3. If swap detected:
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- Re-map data back to correct modality based on anchors.
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- Apply BBPF + BBCR to stabilize reasoning.
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4. Output:
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- modality checks
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- suspected swaps
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- corrected alignment
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- ΔS and λ states
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````
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---
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## Acceptance targets
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* No cross-modality overlap >20% except at validated joins.
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* ΔS(question, retrieved) ≤ 0.45 after swap repair.
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* λ convergent across paraphrases.
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* Explicit modality tags enforced in every schema contract.
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* Zero “silent swaps” propagate beyond first ingestion stage.
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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| -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- |
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) |
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| ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems |
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| ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) |
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| 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map |
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| 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis |
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| 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map |
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| 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap |
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| 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
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| 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control |
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| 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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