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91 lines
3.9 KiB
Markdown
91 lines
3.9 KiB
Markdown
# 📒 Multimodal Reasoning Problem Map
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Standard RAG pipelines stumble when a single prompt spans **text, images, code, and audio**.
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Captions drift, code comments misalign, transcripts add noise.
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WFGY tags each modality in the Semantic Tree and keeps their ΔS tension synchronized.
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---
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## 🤔 Typical Multimodal Failures
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| Modality Clash | What Goes Wrong |
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|----------------|-----------------|
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| Text ↔ Image | Caption describes wrong object or misses nuance |
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| Code ↔ Docstring | Implementation diverges from comment intent |
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| Audio Transcript | OCR / ASR noise melts context |
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| Mixed Prompt | LLM fuses channels into fractured output |
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---
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## 🛡️ WFGY Cross‑Modal Fixes
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| Clash | Module | Remedy | Status |
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|-------|--------|--------|--------|
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| Text ↔ Image | Cross‑modal ΔS + **BBMC** | Aligns caption vector to image embedding; rejects high tension | ✅ Stable |
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| Code ↔ Docstring | Tree Twin Nodes | Parallel nodes: `Code_Node` & `Doc_Node` diffed by residue | ✅ Stable |
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| Audio Noise | Entropy filter (**BBAM**) | Drops low‑confidence transcript tokens | ✅ Stable |
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| Mixed Prompt | **BBPF** multi‑channel fork | Splits channels, processes separately, merges when ΔS < 0.4 | 🛠 In progress |
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---
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## ✍️ Quick Demo — Image + Code + Text
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```txt
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Prompt:
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"Here is an image of a red cube and the Python code that renders it.
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Explain how the RGBA values map to the cube faces."
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WFGY steps:
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1. Tag Image_Node (mod=image) ΔS baseline
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2. Tag Code_Node (mod=code) ΔS vs. Image_Node
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3. Fork text explanation path (mod=text)
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4. BBMC checks residue between Code ↔ Image
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5. Output: coherent mapping of RGBA to cube faces, no modality drift
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````
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---
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## 🛠 Module Cheat‑Sheet
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| Module | Role |
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| ------------------ | --------------------------------------------------------- |
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| **Cross‑modal ΔS** | Measures tension between embeddings of different channels |
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| **BBMC** | Cleans semantic residue across modalities |
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| **BBAM** | Filters ASR/OCR noise |
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| **BBPF** | Forks/merges per‑modality paths |
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| **Semantic Tree** | Stores `mod:` tag on every node |
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---
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## 📊 Implementation Status
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| Feature | State |
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| ------------------------ | ---------- |
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| Cross‑modal ΔS calc | ✅ Stable |
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| Twin Code/Text nodes | ✅ Stable |
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| Audio noise filter | ✅ Stable |
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| Multi‑channel BBPF merge | 🛠 Alpha |
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| GUI modality viewer | 🔜 Planned |
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---
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## 📝 Tips & Limits
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* Prefix snippets with `![image]`, \`\`\`python, or `[audio]` to auto‑tag nodes.
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* For heavy video transcripts, enable `noise_gate = 0.2` in BBAM.
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* Post tricky multimodal prompts in **Discussions**—each case trains the merge logic.
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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://zenodo.org/records/15630969) | 1️⃣ Download · 2️⃣ Upload to LLM · 3️⃣ Ask “Explain using WFGY + \<your multimodal prompt>” |
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| **TXT OS (plain‑text OS)** | [TXTOS.txt](https://zenodo.org/records/15788557) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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> Kept your image+code+text prompt aligned? ⭐ the repo to accelerate the multi‑channel merge module.
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> ↩︎ [Back to Problem Index](../README.md)
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