Self-Training-LLM reconciliation

Type: agentic-system-analyses/types/agentic-system-reconciliation-report.md

Reconciliation

Boundary and dependencies

The members share the builder boundary and its Source register. SRC-1 supplies implementation and attributed doctrine/design, not observed operation or causal evidence. Runtime declares stage routes, model components and downstream parameter authority. Memory adds retained objects and annotations. Epistemic separates content transformation, checking, selection and adaptation. Workflow traces a conditional DPO experiment using runtime records and declares no new records. No correction answers or declined objections were supplied. The previous reconciliation was read as a prior output, not as evidence for current connections. No target source files were read for this reconciliation.

Identity comparisons

No whole-record identity requiring an Amendment is established. The following comparisons rule out supersession; intersecting content and containment do not make whole referents identical.

• Documents and questions. MEM-OBJ-topic-docu identifies a particular title-to-document cache. EPI-OBJ-document follows selected article content across dataset, cache, records and prompts. Neither whole referent replaces the other. MEM-OBJ-questions identifies persisted question records with documents and metadata; EPI-OBJ-instruction follows question text into prompts. MEM-OBJ-test has a separate held-out producer and comparison-answer consumer. These are not interchangeable objects. EPI-RTE-document-transform is an explicitly declared part of RT-RTE-data-generation, not another identity for that stage or its inputs.
• Answer families. MEM-OBJ-answer-content contains reference and raw sampled text-bearing fields. EPI-OBJ-gold-answer and EPI-OBJ-raw-answer separate conditioning and preference roles. The gold family also overlaps MEM-OBJ-context-answer, which has a separate file and document-embedding SFT consumer. The memory container names its different fields and consumers; the epistemic gold container states the different producer premises. These valid containers can remain alongside their parts: separation does not make their findings false, so no split supersession follows.
• Scores and evaluation products. EPI-OBJ-score-result groups numeric scores, memberships and judge categories while explicitly separating evaluator domains. MEM-OBJ-answer-scores, MEM-OBJ-judge-cache and MEM-OBJ-results distinguish stored training-selection fields, cached comparison categories and terminal aggregates. The epistemic container does not assert one combined factuality score or replace those parts. MEM-OBJ-responses is comparison input rather than judgment; MEM-OBJ-known is a persisted question/document subset rather than a factual certificate. No identity or necessary split supersession is established.
• Selection and parameters. EPI-OBJ-preference identifies chosen/rejected designations and formatted training inputs, not all retained answers or the resulting RT-CMP-causal-model. EPI-RTE-preference-selection is explicitly part of RT-RTE-model-training. EPI-RTE-answer-cleaning and EPI-RTE-score-evidence are explicitly parts of RT-RTE-data-generation. These subroutes do not replace their stage containers. RT-BAP-checkpoint-consumption identifies downstream parameter authority, not another component or training route.
• Other components and claims. MEM-CMP-topic-embedder has a distinct source-native model identity and topic-vector role from runtime's generation, NLI and judge components. MEM-OBJ-topic-caches inventories alternative helper parts, not the active document cache. EPI-CLM-semantic-clustering concerns a clustering criterion; RT-CLM-knowledge-filtering concerns context-conditioned consistency and knowledge scoring. Their shared scorer context does not establish identity. Workflow's annotations add delivery conditions to runtime records without competing declarations.

Integration dispositions and independent convergence

Reference-choice scope now agrees. RT-RTE-model-training and EPI-RTE-preference-selection both limit reference-as-chosen enforcement to the single-preference pair and the first multiple-preference pair. Runtime retains the later-pair constructor using g[0] from selected gold samples and the training-driver extend passage. Epistemic now explicitly carries that exception in its route fields, ledger and bounded conclusion. The prior reconciliation's dependent-finding disagreement is therefore not present in these pinned members. The workflow account scopes its override to the single-preference SelfCheckGPT branch; memory's training annotation defers forced reference choice to runtime. These accounts do not establish an all-pairs reference identity guarantee, and none treats preferred-role assignment as factual acceptance.

Dataset continuity remains conditional. Memory's integration issues retain generation's _qf output suffix and training's unchanged dataset path, with the two source assignments. This qualifies the handoff from RT-RTE-data-generation to RT-RTE-model-training: matching flag labels do not establish exact file lineage. The workflow account requires compatible files and usable prerequisites rather than asserting unchanged-wrapper continuity. This is an additional lineage condition, not a conflicting stage identity.

Reuse need not preserve the candidate population. MEM-OBJ-answer-content retains exact-instruction remapping that omits unmatched records. Memory's integration issues additionally state that an empty successful mapping can set map_success. These findings supplement RT-RTE-data-generation and constrain what can reach EPI-RTE-preference-selection. No supplied report asserts complete question preservation through remapping.

Alternative branches remain qualified. EPI-RTE-score-evidence retains early access to all_hallu_scores and the different output fields of alternative scorers. Its account reads runtime's scorer inventory as available branches, not successful DPO execution for every method. MEM-OBJ-topic-caches separately identifies inactive helper wiring, unresolved FAISS use and embedding alignment limits. These are different alternative families; neither uncertainty negates the scoped SelfCheckGPT/predefined-topic implementation account or establishes exercised alternatives.

Selection and trainer input have different authority. MEM-OBJ-answer-scores, EPI-RTE-preference-selection and the workflow training annotation converge on the prompt/chosen/rejected formatter. Scores govern selection but do not become additional DPO input columns; documents and score reasons are not delivered through that formatter. RT-RTE-model-training separately retains the nonpositive-threshold bypass of the question-filtered subset. Numerical admission, parameter updating, factual warrant and improved future capacity remain distinct findings.

Delivered responses do not attest served weights. RT-RTE-response-generation, MEM-OBJ-responses and the workflow response annotation distinguish direct checkpoint loading from independently configured TGI serving. The epistemic ledger preserves this same limit. A DPO output filename does not establish exercise of RT-BAP-checkpoint-consumption; wired capacity, actual model identity and observed dependence remain separate.

Evaluation does not decide checkpoint succession. RT-RTE-pairwise-evaluation, MEM-OBJ-judge-cache, MEM-OBJ-results and the workflow evaluation annotation connect two-order judging, cache reuse, failed-comparison omission and aggregate reporting. Epistemic bounds the license to document-relative model comparisons. The reports do not wire the results into trainer veto, automatic checkpoint promotion or rollback. Omission limits the denominator; zero counted results lacks a division guard. Cached categories do not establish renewed warrant after provider or system-prompt changes, and placeholder hallucination zeros are not measurements. The wired, operator-mediated parameter-update pathway is not an observed or successful self-improvement cycle.

Disagreement disposition

No unresolved cross-report disagreement is established by the supplied members. The previous reference-choice conflict no longer describes the current epistemic record. No analyst answers were supplied, so this disposition rests on the records themselves rather than an inferred correction history.

The mismatch between EPI-CLM-semantic-clustering and EPI-RTE-score-evidence remains an internal doctrine-versus-implementation comparison: bidirectional-entailment wording versus a noncontradiction mask that admits neutrality. It is not a disagreement between analysts. Missing generated artifacts, exact weight identities, provider behavior and causal evidence are shared limitations, not conflicts or grounds to strengthen statuses. The accounts retain implementation wiring separately from uninspected operation and benefit.