Self-Training-LLM memory profile

Type: agentic-system-analyses/types/agentic-system-memory-profile.md

Comparison rationale

Boundary, coverage and evidence

This profile classifies the accepted records, not an executed experiment. The retained inventory comes from MEM-OBJ-topic-docu, MEM-OBJ-questions, MEM-OBJ-context-answer, MEM-OBJ-test, MEM-OBJ-answer-content, MEM-OBJ-answer-scores, MEM-OBJ-known, MEM-OBJ-responses, MEM-OBJ-judge-cache, MEM-OBJ-results, MEM-OBJ-topic-caches and RT-CMP-causal-model. Shipped static directions are not accumulated memory. External provider weights and trainer internals are excluded dependencies, not inspected retained objects of this workflow.

Local lifecycle wiring supports wired findings without showing operation or benefit. Exposed topic helpers retain afforded findings because their active workflow caller and some dependencies are unresolved. The predefined-topic witness does not upgrade the helper alternatives. File storage is known even where file provenance or complete payload form is not. The provider wrapper is not equated with its readable answer text.

Update force is not downstream instruction

RT-RTE-model-training and EPI-RTE-preference-selection establish learning authority for retained examples at optimization. Stored scores separately rank and admit examples; a called threshold can enforce exclusion, but a nonpositive unknown threshold bypasses the filtered subset. The reference override covers the single pair and first multiple-preference pair, not subsequent gold-sample pairs. These bounds qualify selection authority rather than eliminating it.

RT-BAP-checkpoint-consumption establishes numerical generation force through later weights, not a standing prose instruction or a demonstrated gain in capacity. The controlled authority vocabulary does not automatically classify every numerical effect. DPO formatting drops document and score metadata; a downstream checkpoint is not a rationale-retrieval interface. An aggregate report's possible human reader likewise cannot be assigned authority without a recorded consumer.

Local transformations and uncertain origins

MEM-OBJ-answer-scores supports evolve for replacing scores on retained records. MEM-OBJ-known and MEM-OBJ-results support reduced representations of retained answer records and outcome categories, hence consolidate. They do not establish synthesize. EPI-RTE-answer-cleaning establishes deletion at candidate processing, not by itself curation over already-retained memory. EPI-OBJ-gold-answer retains indeterminate semantic relations of opaque generated content; failure to prove entailment is not proof of a new claim. Initial duplicate checks do not establish dedup over retained memory, and configured save limits do not by themselves establish an inspected decay implementation.

Authored model text, extracted cleaned text or judge labels, imported source content and compiled numerical products name different derivation edges. Known local transformations do not authenticate preexisting files or inherited parameters. The generation/training _qf path mismatch and alternate-generator exact-instruction remapping keep actual dataset continuity conditional; neither defeats the inspectable local update path.

Requested access and qualifying trace-fed change

RT-RTE-data-generation, RT-RTE-response-generation and RT-RTE-pairwise-evaluation describe requested loading and selection. Exact prompt-key cache reuse fulfills a comparison request. Similarity inside an explicitly requested helper return is also not unsolicited supply. These pull chains establish no push signal. Reports remain included retained artifacts without an established later consumer; that uncertainty prevents declaring the entire inventory pull-only or its signal axis inapplicable.

The generated-answer/feedback-to-parameters-to-later-inference chain supports trace_learning yes at wired basis. It does not establish observed learning benefit, session-log extraction, tool-trace learning, event-stream learning or trajectory learning. The accepted source account identifies model-produced datasets and derived scores, but lacks the original trace structure needed to choose one of those four source categories. Imported Wikipedia and static examples do not supply that missing origin. No negative trace-learning finding is invented for an opaque alternative.

Reconciliation and source-read log

The supplied reconciliation establishes no supersessions. Container/part overlaps therefore remain canonical in their declaring members: this profile uses the memory inventory for retained file parts and runtime for stage/parameter routes, with epistemic records for local transformations and selection limits. It does not count overlapping containers as additional mechanisms or treat absent workflow declarations as missing operation evidence.

No target source files were read for this profile. All classifications and uncertainty limits derive from the supplied accepted records; no records, quotations or execution evidence were added.