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135 lines
6.1 KiB
Markdown
135 lines
6.1 KiB
Markdown
# Eval Observability — ΔS Thresholds
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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 **Eval_Observability**.
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> To reorient, go back here:
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>
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> - [**Eval_Observability** — evaluation metrics and system observability](./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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A dedicated module for **ΔS monitoring** in evaluation pipelines.
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ΔS = semantic distance between query, retrieved content, and gold anchor.
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Tracking thresholds ensures that retrieval and reasoning quality remain **auditable, measurable, and comparable**.
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---
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## Why ΔS thresholds matter
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- **Detect semantic drift**: High ΔS despite “correct” tokens indicates meaning mismatch.
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- **Localize retrieval errors**: Low similarity in meaning even if vector scores look fine.
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- **Evaluate reasoning robustness**: Stable models keep ΔS below the risk boundary across paraphrases.
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- **Flag latent hallucinations**: ΔS >0.60 strongly correlates with unsupported answers.
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---
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## Core bands
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| Band | Range | Meaning |
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|------|-------|---------|
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| **Stable** | ΔS < 0.40 | Retrieval and reasoning aligned. Answers should be correct and verifiable. |
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| **Transitional** | 0.40 ≤ ΔS < 0.60 | Risk zone. Minor schema changes or index drift may flip outcomes. |
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| **Critical** | ΔS ≥ 0.60 | High failure probability. Almost always linked to missing context or schema break. |
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---
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## Acceptance targets
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- Per-query: **ΔS ≤ 0.45**
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- Batch average: **≤ 0.40**
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- Allowance: **≤ 10%** of queries can fall in the transitional band (0.40–0.60).
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- Critical: **0% tolerance** for ΔS ≥ 0.60 in gold-set eval.
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---
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## ΔS in eval workflow
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1. **Probe per query**
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Log ΔS(question, retrieved) and ΔS(retrieved, anchor).
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2. **Batch roll-up**
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Compute mean, variance, and percentile distribution.
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3. **Compare across seeds**
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Run three paraphrases and two random seeds; check convergence.
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4. **Drift alerting**
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If ΔS rises >0.05 vs baseline, trigger retraining or schema audit.
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---
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## Example probe (pseudo)
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```python
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def deltaS_probe(query, retrieved, anchor):
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d1 = deltaS(query, retrieved)
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d2 = deltaS(retrieved, anchor)
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return max(d1, d2)
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for q in eval_set:
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s = deltaS_probe(q.query, q.retrieved, q.anchor)
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if s >= 0.60:
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alerts.append({"qid": q.id, "ΔS": s, "status": "critical"})
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````
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---
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## Common pitfalls
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* **Using cosine similarity as ΔS** → ΔS is semantic distance, not raw vector score.
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* **Ignoring anchor comparison** → must compute against both query and gold span.
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* **No variance tracking** → averages hide volatility; variance is key.
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* **One-shot eval** → without paraphrase/seed checks, thresholds lack reliability.
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---
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## Reporting recommendations
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* **ΔS histogram**: visualize stability bands.
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* **Trend line**: track ΔS mean per batch over time.
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* **Baseline delta**: highlight drift from previous eval version.
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* **Failure clustering**: group queries where ΔS ≥0.60 for root-cause analysis.
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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 based tension engine |
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| Engine | [WFGY 2.0](/core/README.md) | Production tension kernel and math engine for RAG and agents |
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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 checklist and fix map |
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| Map | [Problem Map 2.0](/ProblemMap/rag-architecture-and-recovery.md) | RAG focused recovery pipeline |
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| Map | [Problem Map 3.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card, image as a debug protocol layer |
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| Map | [Semantic Clinic](/ProblemMap/SemanticClinicIndex.md) | Symptom to family to exact fix |
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| Map | [Grandma’s Clinic](/ProblemMap/GrandmaClinic/README.md) | Plain language stories mapped to Problem Map 1.0 |
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| Onboarding | [Starter Village](/StarterVillage/README.md) | Guided tour for newcomers |
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| App | [TXT OS](/OS/README.md) | TXT semantic OS, fast boot |
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| App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q and A built on TXT OS |
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| App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image with semantic control |
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| App | [Blow Blow Blow](/OS/BlowBlowBlow/README.md) | Reasoning game engine and memory demo |
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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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