DaoyuanLi2816 · Sep 9, 2026 · Sep 9, 2026
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -6,7 +6,7 @@ All notable changes to miniVERL are recorded here. The format follows
 
 ## [Unreleased]
 
-## [0.14.0] - 2026-09-08
+## [0.14.0] - 2026-09-09
 
 ### Installed local RL workflows
 

diff --git a/CITATION.cff b/CITATION.cff
@@ -3,7 +3,7 @@ title: "miniVERL: Run verl experiment semantics on one GPU"
 message: "If you use miniVERL in your work, please cite it as below."
 type: software
 version: 0.14.0
-date-released: 2026-09-08
+date-released: 2026-09-09
 license: Apache-2.0
 repository-code: "https://github.com/DaoyuanLi2816/mini-verl"
 url: "https://github.com/DaoyuanLi2816/mini-verl"

diff --git a/PROJECT_STATE.md b/PROJECT_STATE.md
@@ -4,40 +4,38 @@ Current maintainer handoff for **miniVERL** (`mini-verl` package, `miniverl`
 CLI). `release-state.yaml` is the canonical version source; this page indexes
 current product and evidence state rather than repeating release history.
 
-Last updated: 2026-09-08.
+Last updated: 2026-09-09.
 
-Canonical release state: releasing `v0.14.0`.
+Canonical release state: stable `v0.14.0` (`60afc63da1257e3e22aa6056607a63a90d4d90f1`), development `0.14.1.dev0`.
 
 ## Release state
 
-- Active work: `v0.14.0-p0-productization`, based on verified main `cdc608f`.
-  The next release focuses on upstream configuration coverage, packaged PPO/GRPO
-  walkthroughs, run inspection and system-level recovery. Implementation is
-  settled; release metadata is finalized for exact-candidate qualification.
+- v0.14.0 productization is published: upstream configuration coverage,
+  packaged PPO/GRPO walkthroughs, strict run inspection and system-level recovery.
 - Upstream drift check: GitHub's latest stable release is still `v0.9.0`
   (published 2026-08-14); existing compiler targets remain appropriate.
 - Implemented: v3 prompt-minibatch units and explicit physical lowerings;
   six upstream scripts/seven resolved cases with complete field accounting;
   installed PPO/GRPO templates and adaptation ledgers; strict run inspection;
   PPO value/behavior identity guards and checkpoint-bound log recovery.
-- Development rehearsal: both wheel-installed workflows completed on RTX 4080;
-  PPO 4 actor/4 critic updates and GRPO 2 actor updates, with exact tensor resume
-  and inspected handoff. This dirty-tree rehearsal is not release evidence.
-- Pending: final exact-commit qualification, publication and state sync.
-- Local regression: 2,655 non-GPU/non-network tests passed at 83% branch
+- Exact-release qualification run `34318236880` passed on attempt 1, followed
+  by non-publishing gate `34325442958` and OIDC release `34328973021`.
+  PPO 4 actor/4 critic updates and GRPO 2 actor updates passed exact tensor
+  replay and inspected handoff from the installed candidate wheel.
+- Local regression: 2,656 non-GPU/non-network tests passed at 83% branch
   coverage; 10 RTX 4080 GPU and 16 network tests passed. Four pinned upstream
   conformance tests and four-viewport documentation browser checks passed.
 
-- Stable release: `v0.13.0` at
-  `8e7bc3b5ff1145ae502cca893b7fffca3e12b6a8`.
-- Release candidate line: `0.14.0`.
+- Stable release: `v0.14.0` at
+  `60afc63da1257e3e22aa6056607a63a90d4d90f1`.
+- Current development line: `0.14.1.dev0`.
 - Stable docs: <https://daoyuanli2816.github.io/mini-verl/>.
 - Development docs: <https://daoyuanli2816.github.io/mini-verl/dev/>.
 - Historical build log: [v0.1-v0.9 archive](docs/history/project-state-v0.1-v0.9.md).
 
 ## Current product boundary
 
-Release `0.14.0` has a closed typed profile compiler: it retains v1/v2 and adds
+Development `0.14.1.dev0` has a closed typed profile compiler: it retains v1/v2 and adds
 `verl-rl-v0.9-single-gpu-v3`, a typed resolved RL subset of official verl
 `v0.9.0` at commit `483b8a009ba3a97563edee3a19887e4862b8094a`.
 It compiles PPO/GAE into phased one-GPU actor, critic, reference and reward
@@ -83,6 +81,8 @@ v0.8 environment/PPO artifact bridge is migration-only.
 
 | Evidence | Status |
 | --- | --- |
+| Installed PPO product workflow | Qwen3-0.6B, 8 trajectories, 4 actor/4 critic updates, 2.7266 GiB peak reserved, 15.688 s reported train duration; exact tensor replay and handoff passed |
+| Installed GRPO product workflow | Qwen3-0.6B, 8 trajectories, 2 actor updates, 1.502 GiB peak reserved, 8.923 s reported train duration; exact tensor replay and handoff passed |
 | Qwen3-0.6B/1.7B developer workload | 32 prompts, 8 current-policy updates, 3.1914 GiB peak reserved on one RTX 4080; matched interruption/resume was byte-identical |
 | Qwen3 sampled-k1 PG | 32 prompts, 8 updates, exact interruption/resume, 3.1914 GiB peak reserved; no quality comparison |
 | SmolLM2-360M/1.7B direct GKD | 32 prompts, 8 updates, 1.4961 GiB peak reserved; exact resume, PEFT reload and materialized export passed |
@@ -96,11 +96,11 @@ calculator schema-v2 source stays at SHA-256
 
 ## Maintainer entry points
 
-- [Current local runtime](docs/verl-opd-runtime.md)
+- [Installed PPO/GRPO workflow](docs/local-rl-workflow.md)
 - [Single-GPU verl RL](docs/verl-rl-runtime.md)
-- [Current scale-out contract](docs/verl-opd-scaleout.md)
+- [Current scale-out contract](docs/verl-rl-runtime.md#scale-out-handoff)
 - [Compatibility policy](docs/compatibility.md)
 - [Measured workload](docs/verl-opd-reference-workload.md)
 - [Limitations](docs/limitations.md)
-- Active roadmap: [issue #39](https://github.com/DaoyuanLi2816/mini-verl/issues/39)
-  and [issue #64](https://github.com/DaoyuanLi2816/mini-verl/issues/64)
+- Active research roadmap: [issue #39](https://github.com/DaoyuanLi2816/mini-verl/issues/39).
+  Additional compiler lowerings are indexed by the [upstream corpus](docs/verl-compatibility-corpus.md).
diff --git a/PYPI.md b/PYPI.md
@@ -1,5 +1,5 @@
 <p align="center">
-  <img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.14.0/docs/banner.svg" alt="miniVERL — lower verl experiment semantics onto one CUDA GPU" width="880">
+  <img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/main/docs/banner.svg" alt="miniVERL — lower verl experiment semantics onto one CUDA GPU" width="880">
 </p>
 
 <div align="center">
@@ -8,15 +8,15 @@
 [![Build](https://github.com/DaoyuanLi2816/mini-verl/actions/workflows/build.yml/badge.svg)](https://github.com/DaoyuanLi2816/mini-verl/actions/workflows/build.yml)
 [![PyPI](https://img.shields.io/pypi/v/miniverl.svg)](https://pypi.org/project/miniverl/)
 [![Python](https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue)](https://www.python.org)
-[![License](https://img.shields.io/badge/license-Apache--2.0-blue)](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/LICENSE)
+[![License](https://img.shields.io/badge/license-Apache--2.0-blue)](https://github.com/DaoyuanLi2816/mini-verl/blob/main/LICENSE)
 
 </div>
 
 <p align="center">
   <a href="https://pypi.org/project/miniverl/"><strong>PyPI</strong></a> ·
   <a href="https://daoyuanli2816.github.io/mini-verl/"><strong>Stable docs</strong></a> ·
   <a href="https://daoyuanli2816.github.io/mini-verl/dev/">Development docs</a> ·
-  <a href="https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/README.zh-CN.md">中文</a>
+  <a href="https://github.com/DaoyuanLi2816/mini-verl/blob/main/README.zh-CN.md">中文</a>
 </p>
 
 **miniVERL runs a validated subset of verl experiment semantics on one NVIDIA
@@ -60,13 +60,13 @@ miniverl export-verl --run runs/local-ppo --target-verl v0.9.0 --out ppo-handoff
 miniverl bridge doctor ppo-handoff --json
 ```
 
-The [five-minute workflow](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/for-verl-users.md) explains each artifact and
+The [five-minute workflow](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/for-verl-users.md) explains each artifact and
 offers the matching GRPO commands. These are small length-reward exercises;
 their reward is directly inspectable in `rewards.jsonl`.
 
 `[train]` supplies the ML stack; `[cuda]` additionally supplies quantization.
 Select PyTorch's CUDA build with the [PyTorch installer](https://pytorch.org/get-started/locally/).
-The [single-GPU guide](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/single-gpu-guide.md) covers memory planning and the
+The [single-GPU guide](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/single-gpu-guide.md) covers memory planning and the
 maintainer-measured RTX 4080 environment.
 
 ## What a run gives you
@@ -85,8 +85,8 @@ maintainer-measured RTX 4080 environment.
 ## How it works
 
 <picture>
-  <source media="(max-width: 640px)" srcset="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.14.0/docs/verl-local-runtime-mobile.svg">
-  <img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/v0.14.0/docs/verl-local-runtime.svg" alt="A resolved verl config compiles into a validated single-GPU plan; actor, critic, reference, teacher and reward roles run in phases and produce portable artifacts plus a readiness report.">
+  <source media="(max-width: 640px)" srcset="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/main/docs/verl-local-runtime-mobile.svg">
+  <img src="https://raw.githubusercontent.com/DaoyuanLi2816/mini-verl/main/docs/verl-local-runtime.svg" alt="A resolved verl config compiles into a validated single-GPU plan; actor, critic, reference, teacher and reward roles run in phases and produce portable artifacts plus a readiness report.">
 </picture>
 
 One GPU is treated as a temporal scheduler for logical roles. RL generates
@@ -100,10 +100,10 @@ the learning signal.
 
 | Goal | First command | Primary artifact | Next step |
 | --- | --- | --- | --- |
-| **Run local RL** | `miniverl import-verl --profile verl-rl-v0.9-single-gpu-v3 --example grpo --out local.yaml` | native recipe + compatibility report | [RL quickstart](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/verl-rl-runtime.md) |
-| **Run local OPD** | `miniverl plan --profile verl-opd-v0.8-single-gpu-v1 --config verl-opd.yaml --out plan.json` | immutable execution plan | [OPD quickstart](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/opd-quickstart.md) |
-| **Fit your GPU** | `miniverl plan --config verl-opd.yaml --probe` | measured placement plan | [Hardware planning](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/hardware-planning.md) |
-| **Hand off artifacts** | `miniverl export-verl --run runs/my-run --target-verl v0.9.0 --out scaleout` | actor, critic, Parquet + config bundle | [Compatibility contract](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/compatibility.md) |
+| **Run local RL** | `miniverl import-verl --profile verl-rl-v0.9-single-gpu-v3 --example grpo --out local.yaml` | native recipe + compatibility report | [RL quickstart](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/verl-rl-runtime.md) |
+| **Run local OPD** | `miniverl plan --profile verl-opd-v0.8-single-gpu-v1 --config verl-opd.yaml --out plan.json` | immutable execution plan | [OPD quickstart](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/opd-quickstart.md) |
+| **Fit your GPU** | `miniverl plan --config verl-opd.yaml --probe` | measured placement plan | [Hardware planning](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/hardware-planning.md) |
+| **Hand off artifacts** | `miniverl export-verl --run runs/my-run --target-verl v0.9.0 --out scaleout` | actor, critic, Parquet + config bundle | [Compatibility contract](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/compatibility.md) |
 
 Native recipes also support SFT, DPO and offline KD, plus calculator, JSON
 navigation, read-only SQLite and custom tool environments.
@@ -121,7 +121,7 @@ navigation, read-only SQLite and custom tool environments.
 | Direct GKD / sampled-k1 OPD | supported | pinned verl v0.8 profiles with teacher targets |
 | Ray, FSDP/FSDP2, Megatron, TP/PP/DP > 1 | distributed-only | these change physical scale, not the local objective |
 
-The [upstream compatibility corpus](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/verl-compatibility-corpus.md) resolves
+The [upstream compatibility corpus](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/verl-compatibility-corpus.md) resolves
 real verl examples and records every field's outcome. The v3 profile preserves
 prompt-based minibatch units; v1/v2 remain available for existing recipes.
 
@@ -131,31 +131,31 @@ The published Qwen3-0.6B/1.7B OPD workload consumed 32 distinct prompts and
 completed eight current-policy updates at 3.1914 GiB peak reserved VRAM on an
 RTX 4080. A matched interruption after update four reproduced byte-identical
 trajectories, adapter and optimizer tensors. The SmolLM2-360M/1.7B workload
-completed the same shape at 1.4961 GiB. [System records](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/verl-opd-reference-workload.md)
+completed the same shape at 1.4961 GiB. [System records](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/verl-opd-reference-workload.md)
 contain configs, hashes and phase timings.
 
 Rollout Runtime v2 measured `hf_cached` and managed vLLM across 24 RTX 4080
 cells spanning response length, sampling mode and `n=1/4`. See the
-[runtime report](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/benchmarks/rollout-runtime-v2.md). Evidence for the new
+[runtime report](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/benchmarks/rollout-runtime-v2.md). Evidence for the new
 RL family is published through the exact-wheel release qualification rather
 than presented as a task-quality comparison.
 
 ## Research record
 
 The scientific reports preserve their original outcomes and frozen inputs:
-[calculator protocol](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/benchmarking.md),
-[RecoveryBench](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/recoverybench/recoverybench-v1.md),
-[Alignment Lab](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/alignment-lab/alignment-lab-v1.md), and the
-[External Alignment Gate](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/alignment-external/alignment-external-v1.md).
+[calculator protocol](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/benchmarking.md),
+[RecoveryBench](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/recoverybench/recoverybench-v1.md),
+[Alignment Lab](https://github.com/DaoyuanLi2816/min
8000
i-verl/blob/main/docs/alignment-lab/alignment-lab-v1.md), and the
+[External Alignment Gate](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/alignment-external/alignment-external-v1.md).
 They are scoped studies, separate from runtime qualification.
 
 ## Compatibility boundary
 
 miniVERL targets one local process and one NVIDIA CUDA GPU. The compiler
 distinguishes exact or conformant semantics, local physical lowering,
 distributed-only settings, feasible work not yet implemented, and technically
-unsupported inputs. The [compatibility policy](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/compatibility.md) is the
-complete matrix; [limitations](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/limitations.md) collects architecture,
+unsupported inputs. The [compatibility policy](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/compatibility.md) is the
+complete matrix; [limitations](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/limitations.md) collects architecture,
 measurement, security and generalization boundaries in one place. miniVERL is
 an independent Apache-2.0 project.
 
@@ -168,7 +168,7 @@ python -m pip install -e ".[dev,train]"
 pytest -q -m "not gpu and not network"
 ```
 
-See [CONTRIBUTING.md](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/CONTRIBUTING.md), [CHANGELOG.md](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/CHANGELOG.md),
-[CITATION.cff](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/CITATION.cff), the [guide for verl users](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/docs/for-verl-users.md),
-[SECURITY.md](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/SECURITY.md) and the
-[Apache-2.0 license](https://github.com/DaoyuanLi2816/mini-verl/blob/v0.14.0/LICENSE).
+See [CONTRIBUTING.md](https://github.com/DaoyuanLi2816/mini-verl/blob/main/CONTRIBUTING.md), [CHANGELOG.md](https://github.com/DaoyuanLi2816/mini-verl/blob/main/CHANGELOG.md),
+[CITATION.cff](https://github.com/DaoyuanLi2816/mini-verl/blob/main/CITATION.cff), the [guide for verl users](https://github.com/DaoyuanLi2816/mini-verl/blob/main/docs/for-verl-users.md),
+[SECURITY.md](https://github.com/DaoyuanLi2816/mini-verl/blob/main/SECURITY.md) and the
+[Apache-2.0 license](https://github.com/DaoyuanLi2816/mini-verl/blob/main/LICENSE).
diff --git a/docs/generated/quality.json b/docs/generated/quality.json
@@ -1,18 +1,18 @@
 {
   "schema_version": 2,
   "release": "0.14.0",
-  "status": "candidate",
+  "status": "released",
   "quality_floor": "2,000+ tests and 80%+ branch coverage at v0.14.0",
   "local_validation": {
     "scope": "P0 implementation and CLI compatibility regression on the maintainer workstation",
-    "commit": "39de76ad4399318d4b19e82f7a4f0d90316054c7",
-    "commit_relationship": "implementation commit; release metadata and citation wording follow in the candidate commit",
-    "measured_at": "2026-09-09T05:55:00Z",
+    "commit": "f128c98456929cdc53f9f094f5ecf8a791690aed",
+    "commit_relationship": "final PR head; the squash release commit has the same tree",
+    "measured_at": "2026-09-09T06:05:10Z",
     "platform": "Windows 11",
     "python": "CPython 3.10.11",
     "coverage_mode": "branch",
     "cpu_non_gpu_non_network": {
-      "passed": 2655,
+      "passed": 2656,
       "skipped": 14,
       "deselected": 24,
       "branch_coverage_percent": 83.0,
@@ -24,10 +24,24 @@
     "docs_visual": {"viewports": 4, "rendered_svg_instances": 44}
   },
   "release_validation": {
-    "commit": "pending",
-    "gpu_coverage": "pending exact-release-SHA full qualification",
+    "commit": "60afc63da1257e3e22aa6056607a63a90d4d90f1",
+    "gpu_coverage": "attempt-1 full qualification; installed PPO and GRPO command workflows, exact tensor resume, v0.9 handoff and historical regression matrix passed on one WSL2 RTX 4080",
     "scope": "exact release candidate wheel",
-    "conclusion": "pending",
-    "required": "attempt-1 full RTX 4080 qualification, installed PPO/GRPO workflows, exact-byte release dry run and public artifact verification"
+    "conclusion": "passed",
+    "workflows": {
+      "ci": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/34318072752",
+      "build": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/34318072732",
+      "docs": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/34328973019",
+      "pinned_verl_bridge": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/34318072653",
+      "gpu_full_qualification": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/34318236880",
+      "release_dry_run": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/34325442958",
+      "release": "https://github.com/DaoyuanLi2816/mini-verl/actions/runs/34328973021"
+    },
+    "publication": {
+      "pypi": "https://pypi.org/project/miniverl/0.14.0/",
+      "github_release": "https://github.com/DaoyuanLi2816/mini-verl/releases/tag/v0.14.0",
+      "wheel_sha256": "f44e607acb2b20608ac217891862374743f7dd443d934664dd8c0349250fbf26",
+      "sdist_sha256": "fe9584bb9450a183372151dc1dea463d268a01cc3b6181afb4aaf54046825324"
+    }
   }
 }