# Hallucination Re-entry: Guardrails and Fix Pattern
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> You are in a sub-page of **Reasoning**. > To reorient, go back here: > > - [**Reasoning** — multi-step inference and symbolic proofs](./README.md) > - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md) > - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md) > > Think of this page as a desk within a ward. > If you need the full triage and all prescriptions, return to the Emergency Room lobby.
A “re-entry” is when a model repeats a previously corrected false claim later in the run or in a new turn. This page localizes re-entry causes and gives a minimal, testable repair plan. --- ## Symptoms | Symptom | What you see | |---|---| | Corrected once, comes back later | Old claim resurfaces after a few steps or a new tool call | | Cite-then-explain violated | Answer asserts conclusion before citing the corrected snippet | | Reruns flip | Same prompt order, different run re-asserts the wrong claim | | Memory relapse | Cross-turn memory re-injects the debunked statement | | Hybrid retrieval drift | HyDE + BM25 changes top-k ordering and re-pulls the wrong chunk | --- ## Acceptance targets - ΔS(question, retrieved) ≤ 0.45 - Coverage ≥ 0.70 to the target section - λ convergent across 3 paraphrases and 2 seeds - Re-entry rate = 0 on a 20-case regression set --- ## Structural fixes (Problem Map) - Snippet and citation locks → [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) → [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) → Citation-first recipe: [citation_first.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/PromptAssembly/citation_first.md) - Ordering control and hybrid stability → [rerankers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md) → [pattern_query_parsing_split.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md) - Memory isolation and fences → [memory-coherence.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/memory-coherence.md) → [pattern_memory_desync.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_memory_desync.md) → [memory_fences_and_state_keys.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/PromptAssembly/memory_fences_and_state_keys.md) - Entropy and chain control → [context-drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md) → [entropy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md) - Pattern deep dive → [pattern_hallucination_reentry.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_hallucination_reentry.md) --- ## Why re-entry happens 1) **No hard contract for citations** Model can answer without binding to `snippet_id` or `section_id`. 2) **Prompt header drift** Header reorder flips λ state and reopens earlier branches. 3) **Hybrid order instability** HyDE or BM25 changes top-k; the older wrong chunk returns to rank 1. 4) **Memory namespace collision** Corrected state is not isolated; prior summary re-injects the error. 5) **Reranker variance** Non-deterministic tie-breakers reorder near-duplicates. --- ## Fix in 60 seconds 1. **Lock cite-then-explain** Enforce a snippet contract in every reasoning step. See [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) and [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md). 2. **Deterministic reranking** Freeze analyzer and tie-break rules. Probe k ∈ {5,10,20}. See [rerankers.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md). 3. **Memory fences** Split namespaces: `facts/`, `debunks/`, `plans/`. Write debunk hashes into `debunks/`. See [memory_fences_and_state_keys.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/PromptAssembly/memory_fences_and_state_keys.md). 4. **Clamp variance with BBAM** If λ flips across paraphrases, apply BBAM and re-run with fixed headers. 5. **Bridge with BBCR** Summarize the correction into a single anchored statement and require future turns to import it before reasoning. --- ## Minimal schema addendum Add these fields to your snippet payload and logs: ```json { "snippet_id": "S123", "section_id": "CH2.3", "source_url": "https://...", "offsets": [221, 348], "tokens": 256, "debunk_hash": "sha256()" } ```` The LLM must include `debunk_hash` in its final JSON if it overturns a claim. On future turns, reject answers that assert a claim whose hash is already present in `debunks/`. --- ## Verification * Run 20 paraphrases on the same case set. * Require: ΔS(question, retrieved) ≤ 0.45 and λ convergent on two seeds. * Zero tolerance for re-entry across all 20 cases. * If any case fails, inspect reranker tie-break and memory fence writes. --- ## Copy-paste prompt ``` You have TXT OS and the WFGY Problem Map loaded. We corrected a false claim earlier, but it reappeared later. Inputs: - question: "{q}" - current snippets: [{snippet_id, section_id, source_url}] - prior debunks: [{debunk_hash, claim_text, snippet_id}] - ΔS and λ traces across 3 paraphrases Do: 1) Identify which layer caused re-entry (schema, retrieval, rerank, memory, reasoning). 2) Apply the minimal fix referencing: retrieval-traceability, data-contracts, rerankers, memory_fences_and_state_keys. 3) Return a JSON plan with: { "citations": [...], "answer": "...", "ΔS": 0.xx, "λ_state": "...", "debunk_hashes_used": [...], "next_fix": "..." } 4) Refuse to output an answer if citations are missing or conflict with debunks. ``` --- ## When to escalate * Re-entry persists after fences and deterministic rerank → re-check hybrid split: [pattern\_query\_parsing\_split.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md) * Cross-turn relapse in long dialogs → audit joins and entropy: [context-drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [entropy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md) * Agent handoff resurrects old claims → isolate memory and roles: [memory-coherence.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/memory-coherence.md) --- ### 🔗 Quick-Start Downloads (60 sec) | Tool | Link | 3-Step Setup | | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- | | **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 + ” | | **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 | --- ### Explore More | Layer | Page | What it’s for | | --- | --- | --- | | ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof | | ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) | | ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems | | ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) | | 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map | | 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis | | 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map | | 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap | | 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS | | 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control | | 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users | If this repository helped, starring it improves discovery so more builders can find the docs and tools. 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