Fix #2364: [Bug] MIN_ADAPTIVE_BASELINE floor untuned for v2.0.7 normalized backprop reward - #2367
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adaptiveBaseline(poolMean) is documented as adaptive between MIN_ADAPTIVE_BASELINE (0.2) and V7_NEUTRAL_BASELINE (0.5), but the post-v2.0.7 normalized-credit backprop rewrite left per-trace V values in a ~0.02-0.5 band. Since typical poolMean sits at ~0.01-0.06 (well below 0.2), Math.max(0.2, poolMean) pinned the baseline at a stale 0.2 for effectively every pool, capping computeGain output and skewing shrinkTowardBaseline against low-without-count candidate policies. Policy/skill promotion stalled fleet-wide. Retune MIN_ADAPTIVE_BASELINE to 0.005, matching the v2.0.7 minTraceValue floor in core/config/defaults.ts. The adaptive branch of adaptiveBaseline is now reachable across the full observed V distribution; the constant only kicks in for degenerate near-zero pools. - gain.ts: constant 0.2 -> 0.005, docstring rewritten to reference v2.0.7 backprop distribution and the issue's regression history - README.md: replace stale "V_with ~ 0.7-0.85" description with the v2.0.7 0.02-0.5 range, cross-link MIN_ADAPTIVE_BASELINE + minTraceValue - gain.test.ts: two new regression cases (adaptive branch reachable at typical poolMean 0.03; MIN_ADAPTIVE_BASELINE <= minTraceValue) Refs: MemTensor#2364
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🤖 Open Code ReviewTarget: PR #2367 ✅ OpenCodeReview: Review complete: 0 finding(s) across 1 selected item(s). Generated by cloud-assistant via Open Code Review. |
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✅ Automated Test Results: PASSEDAll tests passed (83/83 executed, 5 skipped). memos_github_open_source/smoke: 1/1, memos_local_plugin/unit: 11/11, memos_python_core/changed-repo-python: 71 passed, 5 skipped. Duration: 15s [advisory, non-gating] AI-generated tests on branch test/auto-gen-df2d3cfc906de175-20260915054146: 39/39 passed — these do NOT affect the PR verdict; review the branch manually. Branch: |
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Description
Retunes MIN_ADAPTIVE_BASELINE in apps/memos-local-plugin/core/memory/l2/gain.ts from 0.2 to 0.005, restoring the adaptive-baseline behavior that adaptiveBaseline() has always documented. Root cause: the v2.0.7 reward-backprop rewrite moved per-trace V values into a ~0.02–0.5 band (typical poolMean ~0.01–0.06), but the 0.2 floor was left over from the pre-v2.0.7 reward scale. Since Math.max(0.2, poolMean) pinned every real pool at 0.2, the adaptive branch became dead code — computeGain output was capped and shrinkTowardBaseline systematically penalized low-without-count candidate policies, stalling policy/skill promotion fleet-wide.
The retuned constant (0.005) matches the v2.0.7 minTraceValue floor already documented in core/config/defaults.ts, so poolMean values across the entire observed distribution now reach the adaptive branch. The MIN_ADAPTIVE_BASELINE guard only triggers for degenerate near-zero pools, which is the original design intent.
Verification: two new regression cases in tests/unit/memory/l2/gain.test.ts assert (a) the adaptive branch is reachable at typical v2.0.7 poolMean 0.03 and (b) MIN_ADAPTIVE_BASELINE ≤ config.minTraceValue. Full apps/memos-local-plugin unit suite green (1552 tests, 0 failures) and tsc --noEmit passes clean. gain.ts docstring plus the neighboring L2 README were updated to describe the v2.0.7 distribution and cross-link the shared floor with minTraceValue.
Files touched (3): apps/memos-local-plugin/core/memory/l2/gain.ts, apps/memos-local-plugin/core/memory/l2/README.md, apps/memos-local-plugin/tests/unit/memory/l2/gain.test.ts. Fix is minimal, reversible, and does not require a data migration — the change only affects gain computation for new promotion decisions. Refs #2364.
Related Issue (Required): Fixes #2364
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How Has This Been Tested?
Not run; documentation-only change.
Checklist
@WeiminLee please review this PR.
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