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141 lines
6.5 KiB
Markdown
141 lines
6.5 KiB
Markdown
# Multimodal Fusion Break — Long Context
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **Multimodal_LongContext**.
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> To reorient, go back here:
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>
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> - [**Multimodal_LongContext** — long-context reasoning across text, vision, and audio](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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When text, image, audio, or video streams drift apart in long windows, the fusion layer collapses and reasoning degrades.
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This page focuses on detecting and repairing multimodal alignment failure.
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---
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## What this page is
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- A structural fix map for cross-modal drift.
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- Helps keep language, vision, and audio in sync across long sessions.
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- Defines measurable acceptance targets for ΔS and λ between modalities.
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---
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## When to use
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- Image or video reference is ignored after 15k–50k tokens.
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- Audio transcript aligns for the first minutes but drifts later.
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- Model hallucinates objects not present in the visual stream.
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- Cross-modal reasoning (e.g., Q&A about a chart) produces flat or wrong answers.
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- Captions or OCR text do not match the actual frames.
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---
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## Open these first
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- [Alignment Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/alignment-drift.md)
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- [Caption Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/caption-collapse.md)
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- [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
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- [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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- [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)
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---
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## Common failure patterns
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- **Late fusion drift**: text reasoning ignores the latest visual input.
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- **Audio-text skew**: transcript desync causes answers to lag behind the clip.
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- **Phantom alignment**: the model cites a visual region that does not exist.
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- **Cross-modal flattening**: distinct modalities are merged into a vague statement.
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- **Sequential decay**: early multimodal anchors remain correct, late anchors collapse.
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---
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## Fix in 60 seconds
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1. **Stamp each modality**
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- Text: `snippet_id, line_no`
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- Vision: `region_id, bbox`
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- Audio: `frame_time, speaker_id`
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2. **Cross-modal ΔS checks**
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- Require ΔS(text, vision) ≤ 0.45
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- Require ΔS(text, audio) ≤ 0.45
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3. **Schema lock**
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- Enforce `{subject | attribute | source_modality}` per entry.
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- Forbid mixing without anchors.
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4. **Clamp variance**
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- If λ flips between modalities, apply BBAM.
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- If collapse persists, insert BBCR bridge nodes.
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5. **Trace fusion table**
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- Log all modalities in one alignment table with ΔS values.
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- Fail fast if any modality lacks anchor.
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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: Stabilize multimodal reasoning across long windows.
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Steps:
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1. Print alignment table {text_id, vision_id, audio_id, ΔS, λ_state}.
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2. Require cite-then-fuse, forbid phantom regions or hallucinated objects.
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3. If ΔS ≥ 0.60 across any pair, propose fix from data-contracts or alignment-drift.
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4. Apply BBAM on drift, BBCR on collapse.
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5. Return {Fusion Table, Anchor Log, Final Answer}.
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````
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---
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## Acceptance targets
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* ΔS across modalities ≤ 0.45
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* λ remains convergent across three paraphrases
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* Every caption / audio frame maps to at least one visual anchor
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* No phantom alignments, no modality ignored
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* Fusion remains stable for >50k tokens
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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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