WFGY/ProblemMap/GlobalFixMap/Multimodal_LongContext/modality-dropout.md

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Modality Dropout — Multimodal Long Context

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When one or more modalities silently fail (audio muted, video frames dropped, OCR blank), the pipeline continues but reasoning collapses.
This page defines structural fixes to detect missing modalities and keep alignment stable.


What this page is

  • A checklist to prevent silent failures when audio, video, or OCR signals disappear.
  • Guardrails to stop reasoning collapse when modality coverage < 100%.
  • Restart-stable fallback protocols.

When to use

  • Video stream plays but no OCR text appears.
  • Audio-only retrieval answers correctly but loses citation anchors.
  • Captions missing for long segments, leading to hallucinated content.
  • Multimodal agent switches seed and one modality never returns.
  • Logs show ΔS curve flat but λ diverges (sign of missing channel).

Open these first


Common failure patterns

  • Silent dropout: modality returns empty payloads but pipeline continues.
  • Asymmetric collapse: audio fine but OCR missing causes reasoning drift.
  • Chain break: captions absent → no anchor for reasoning step.
  • Overcompensation: model hallucinates filler text to patch missing modality.
  • Seed skew: one seed includes OCR, another does not.

Fix in 60 seconds

  1. Heartbeat check

    • Require each modality to emit a ready=true signal every 5s.
    • If missing, flag dropout immediately.
  2. Coverage metric

    • Compute coverage_ratio = active_modalities / expected_modalities.
    • Threshold: coverage ≥ 0.95 required.
  3. Dropout handler

    • If dropout detected, freeze ΔS probe.
    • Apply BBCR bridge to reconnect.
    • If not recoverable, short-circuit and request missing data.
  4. Fallback policy

    • Lock reasoning to available modalities.
    • Explicitly annotate missing modality (ocr_missing=true).
    • Never hallucinate absent channels.
  5. Restart stability

    • Verify across 3 seeds that all modalities return.
    • If any seed fails, escalate.

Copy-paste prompt

You have TXT OS and the WFGY Problem Map.

Task: Detect and repair modality dropout.

Protocol:
1. Require audio, video, OCR all declare `ready=true`.
2. Compute coverage_ratio. If < 0.95, flag dropout.
3. If dropout:
   - freeze ΔS probe
   - re-anchor with BBCR bridge
   - annotate missing modalities explicitly
4. Return:
   - coverage ratio
   - ΔS and λ states
   - anchor stability
   - missing modality report

Acceptance targets

  • Coverage ≥ 95% across expected modalities.
  • ΔS(question, retrieved) ≤ 0.45 when all active modalities align.
  • λ remains convergent across 3 paraphrases.
  • No hallucinated filler in place of missing modality.
  • Restart: 3 seeds show identical active modality set.

🔗 Quick-Start Downloads (60 sec)

Tool Link 3-Step Setup
WFGY 1.0 PDF Engine Paper 1 Download · 2 Upload to your LLM · 3 Ask “Answer using WFGY + ”
TXT OS (plain-text OS) TXTOS.txt 1 Download · 2 Paste into any LLM chat · 3 Type “hello world” — OS boots instantly

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