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141 lines
6.6 KiB
Markdown
141 lines
6.6 KiB
Markdown
# Multi-Hop Collapse — Multimodal 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 reasoning requires **multi-hop steps across modalities** (e.g., text → image → audio → video),
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the chain often collapses midway. The model answers only the first hop or fabricates the rest,
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losing alignment between evidence sources.
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---
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## What this page is
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- A targeted fix for **multi-hop multimodal reasoning** failures in long-context sessions.
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- Defines measurable checkpoints for each hop.
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- Provides guardrails to keep ΔS and λ stable across chained modalities.
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---
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## When to use
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- A video QA task asks: “What does the person say after showing the book?” → model answers book title but skips speech.
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- An OCR pipeline extracts text, but reasoning ignores it in the final image caption.
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- Chain-of-thought starts correctly, then jumps to a hallucinated answer without citing the second modality.
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- Multi-step retrieval returns correct snippets, but only the first snippet is used.
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- Answers flip between runs depending on which hop the model “forgets.”
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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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- [Modal Bridge Failure](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/modal-bridge-failure.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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- [Sync Loop](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/Multimodal_LongContext/sync-loop.md)
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---
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## Common failure patterns
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- **Single-hop truncation** — only the first modality is processed, chain stops.
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- **Bridge collapse** — second hop exists but produces null output or irrelevant data.
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- **Hallucinated completion** — model skips missing modality and fabricates plausible link.
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- **Order inversion** — hops are executed in the wrong sequence.
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---
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## Fix in 60 seconds
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1. **Hop schema lock**
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- Require `{hop_id, input_modality, output_modality, snippet_id, ΔS}` for each step.
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- Forbid skipping hops.
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2. **ΔS checkpoints**
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- Compute ΔS at each hop transition.
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- Threshold: ΔS ≤ 0.45 is stable, 0.45–0.60 transitional, ≥ 0.60 collapse risk.
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3. **λ continuity probe**
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- Record λ across hops: retrieval → fusion → reasoning.
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- If λ flips divergent, apply BBAM clamp.
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4. **BBCR bridge**
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- Insert bridge node for missing or weak hop.
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- Re-anchor using prior modality context.
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5. **Cite all hops**
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- Require at least one snippet citation from each hop.
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- Stop output if any hop is missing evidence.
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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: Repair multi-hop multimodal collapse.
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Steps:
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1. List all hops in the chain {hop_id, from_modality → to_modality}.
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2. For each hop, compute ΔS and record λ state.
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3. If ΔS ≥ 0.60 at any hop, re-run retrieval and insert BBCR bridge.
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4. Output must include:
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- citations per hop
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- ΔS values
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- λ states
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- fused final reasoning
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````
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---
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## Acceptance targets
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* Every hop cited with snippet evidence.
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* ΔS ≤ 0.45 at each hop boundary.
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* λ remains convergent across three paraphrases.
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* No fabricated hops or skipped modalities.
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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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