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140 lines
6.5 KiB
Markdown
140 lines
6.5 KiB
Markdown
# Caption 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 captions or annotations break down under long windows, multimodal pipelines lose alignment and factual grounding.
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This page focuses on stabilizing caption integrity for images, videos, and diagrams in extended sessions.
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---
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## What this page is
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- A diagnostic page for caption degradation in multimodal contexts.
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- Structural guardrails to keep captions aligned with visual evidence.
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- Acceptance targets for ΔS and λ across captions and snippets.
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---
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## When to use
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- Image captions are accurate at the start but drift after 20k+ tokens.
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- Captions compress multiple regions into one vague statement.
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- Video scene captions skip events or merge distinct frames.
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- Diagram labels appear but reasoning no longer references them correctly.
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- Captions look fluent but introduce objects not in the frame.
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---
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## Open these first
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- [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)
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- [Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.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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- [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)
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---
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## Common failure patterns
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- **Vague compression**: distinct objects collapsed into one generic caption.
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- **Temporal merge**: video events blended into a single description.
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- **Phantom detail**: captions include invented objects or properties.
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- **Citation loss**: captions lack bounding boxes or region ids.
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- **Context slip**: captions reference prior images instead of the current one.
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---
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## Fix in 60 seconds
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1. **Stamp captions with anchors**
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- Add `{region_id | bbox | frame_time}` to each caption.
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- Require ΔS(caption, region) ≤ 0.45.
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2. **Enforce one-to-one mapping**
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- Each object/region must have a unique caption line.
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- Forbid merges without explicit evidence.
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3. **Normalize caption schema**
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- Require `{subject | attribute | action}` fields.
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- Disallow free-form hallucinations.
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4. **Clamp entropy**
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- Apply BBAM when variance rises across caption tokens.
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- Apply BBCR bridge if captions diverge from visual anchors.
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5. **Trace joins**
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- Log {region_id, caption_id, ΔS, λ_state}.
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- Fail if any caption has no visual 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 captions across long multimodal contexts.
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Steps:
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1. Print each caption with {region_id | bbox | frame_time}.
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2. Require cite-then-caption, forbid phantom objects.
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3. Compute ΔS(caption, region). If ≥ 0.60, propose fix with data-contracts or chunking-checklist.
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4. Apply BBAM if entropy rises. Apply BBCR if λ diverges.
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5. Return: {Caption Table, Alignment Log, Final Answer}.
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````
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---
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## Acceptance targets
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* ΔS(caption ↔ region) ≤ 0.45
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* Each caption tied to a valid region\_id or frame\_time
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* λ remains convergent across three paraphrases
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* No phantom objects or invented attributes
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* Captions maintain one-to-one mapping with objects
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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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