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

Desync Anchor — Guardrails and Fix Pattern

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• Multimodal_LongContext — long-context reasoning across text, vision, and audio
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When multimodal pipelines rely on anchor tokens (timestamps, bounding boxes, snippet IDs) to align across modalities, drift can cause one stream to advance while the others lag. The model then reasons on mismatched anchors, producing hallucinations or misplaced grounding.

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Symptoms

• Video timeline shows t=5s anchor, but captions are aligned to t=4.2s
• OCR snippets cite bounding box A, while speech transcripts cite bounding box B
• Long context replay produces flip-flop alignment across runs
• Answer references correct content but wrong time or position

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Root causes

• Clock skew: audio vs. video vs. text not normalized before indexing
• Buffer flush misalignments: truncated chunks shift anchors mid-window
• Asynchronous retrieval: one retriever returns stale anchor metadata
• Join collisions: overlapping chunks share same anchor ID

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Open these first

• Entropy Collapse
• Context Drift
• Retrieval Traceability
• Data Contracts

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Fix in 60 seconds

1. Normalize clocks

   • Round timestamps to fixed interval (e.g. 100ms).
   • Ensure OCR/page anchors share same epoch.

2. Fence joins

   • Enforce {anchor_id, start, end} triplet.
   • Forbid overlapping anchor_id across modalities.

3. Stabilize variance

   • Apply BBAM clamp when ΔS(anchor_i, anchor_j) > 0.55
   • If collapse detected, re-anchor with BBCR bridge.

4. Trace every step

   • Require all outputs to cite {anchor_id, modality, confidence}.
   • Drop responses with missing or conflicting anchors.

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Acceptance targets

• ΔS(anchor alignment) ≤ 0.45
• λ remains convergent across 3 runs with shuffled seeds
• Coverage ≥ 0.70 with consistent anchor IDs across modalities

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Explore More

Module	Description	Link
WFGY Core	Canonical framework entry point	View
Problem Map	Diagnostic map and navigation hub	View
Tension Universe Experiments	MVP experiment field	View
Recognition	Where WFGY is referenced or adopted	View
AI Guide	Anti-hallucination reading protocol for tools	View

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