WFGY/ProblemMap/GlobalFixMap/Multimodal_LongContext/anchor-misalignment.md

Anchor Misalignment — Multimodal Long Context

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• Multimodal_LongContext — long-context reasoning across text, vision, and audio
• WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
• WFGY Problem Map 1.0 — 16 reproducible failure modes

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When anchor points (timestamps, keyframes, caption markers, OCR segment IDs) drift apart across modalities, all subsequent alignment collapses.
Even a single anchor slip can poison the entire session, because every later segment is shifted by the wrong baseline.

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What this page is

• A dedicated fix guide for anchor-level desync across video, audio, captions, OCR, and embeddings.
• Methods to detect anchor error at its origin before it cascades.
• Recipes to reset, rebuild, and lock anchors in multimodal pipelines.

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When to use

• Audio and captions line up at start, but after 15–20 minutes captions appear seconds late.
• OCR anchors (page numbers, frame IDs) mismatch video frames.
• Retrieval starts citing correct facts with wrong time/visual context.
• Small anchor errors propagate into large ΔS drift across session.
• λ remains divergent despite repeated local corrections.

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Open these first

• Alignment Drift
• Desync Amplification
• Cross-Modal Bootstrap
• Time Sync Failure

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Common failure patterns

• Frame anchor slip — a single dropped frame shifts the reference timeline permanently.
• OCR anchor mismatch — OCR labels a wrong page/frame, all later mappings are offset.
• Caption anchor skew — captions drift due to variable network delay or ASR buffering.
• Compound anchor drift — multiple small anchor errors amplify into total collapse.
• Phantom anchor — stale or ghost anchors remain after modality restart.

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Fix in 60 seconds

1. Anchor consistency check

   • Hash anchors per modality (frame ID, timestamp, line number).
   • Compare every N=30s. Flag divergence >200ms.

2. Reset to gold anchors

   • Define a single trusted source (e.g., video frame count).
   • Rebuild captions/OCR anchors against gold source.

3. Sliding window correction

   • Use overlapping 30–60s windows.
   • Realign anchors locally and re-stitch.

4. BBCR + BBAM bridge

   • Bridge desynced anchors with BBCR.
   • Clamp λ variance with BBAM until convergence.

5. Anchor fencing

   • Forbid cross-window reuse if anchor IDs mismatch.
   • Drop corrupted anchors rather than propagate.

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Copy-paste prompt

You have TXT OS and the WFGY Problem Map.

Task: Detect and repair anchor misalignment in multimodal input.

Protocol:
1. Hash anchors (timestamps, frame IDs, OCR IDs) every 30s.
2. Compare across modalities.
   - If drift >200ms, reset against gold anchor (video timeline).
3. Rebuild windows with local realignment.
4. Apply BBCR bridge and BBAM clamp if λ stays divergent.
5. Output:
   - anchor hashes
   - drift points
   - corrections applied
   - ΔS and λ states

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Acceptance targets

• All modalities reference the same anchor baseline.
• Drift ≤ 200ms across 30–60s windows.
• ΔS(question, retrieved) ≤ 0.45 after correction.
• λ convergent across 3 paraphrases.
• No phantom anchors polluting later windows.

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Tool	Link	3-Step Setup
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