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diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..599cdad20256b7ec58ccc225f8c263e53bd5cc14
--- /dev/null
+++ b/README.md
@@ -0,0 +1,94 @@
+---
+license: apache-2.0
+---
+
+# Mem-0 Execution Module — Mn tasks (RMBench / RoboTwin 2.0)
+
+**Per-task Mem-0 execution-module checkpoints** for four RMBench **Mn** tasks:
+`battery_try`, `blocks_ranking_try`, `cover_blocks`, `press_button`.
+Each task has its **own** executor — trained only on that task's 50-episode
+`demo_clean` dataset — and its **own** normalization stats (unlike the
+[`m1_mix` release](https://huggingface.co/qiuly/Mem-0-m1mix-RMBench), which used one
+joint checkpoint for all five M1 tasks).
+
+- **Backbone:** Qwen3-VL-2B-Instruct (fine-tuned; weights bundled in each checkpoint)
+- **Action head:** DiT-B flow-matching policy (16-D action)
+- **Memory:** MemoryBank (instant + anchor memory fusion across the episode)
+- **Aux head:** subtask-end classifier
+- ≈ 2.67 B params per checkpoint; 30,000 training steps per task
+
+## Results
+
+`task_config = demo_clean`, `instruction_type = unseen`, 100 episodes per task.
+`action_horizon` is the per-task inference-time setting used for these numbers.
+
+| Task               | action_horizon | Success Rate | Reward |
+|--------------------|:--------------:|:------------:|:------:|
+| battery_try        | 15             | **0.21**     | 0.00   |
+| blocks_ranking_try | 15             | **0.15**     | 0.00   |
+| cover_blocks       | 8              | **0.76**     | 0.82   |
+| press_button       | 30             | **0.02**     | 0.00   |
+| **Average**        | —              | **0.285**    | —      |
+
+Rollout videos (100 per task) and raw score files are under `eval_results/`
+(see `eval_results/results.md`).
+
+## Contents
+
+```
+mn_submit/
+├── README.md
+├── checkpoints/
+│   └── <task>/final_step30000.pt (+ .sha256)     # one full ckpt per task, ~15.3 GB each
+├── norm_stats/
+│   └── <task>/norm_stats.json                    # per-task min-max state/action stats
+└── eval_results/
+    ├── results.md                                # scores + per-task action_horizon
+    ├── success_rate.png
+    └── <task>/                                   # _result.txt, episode*.mp4 (×100)
+```
+
+## Checkpoints
+
+Each `checkpoints/<task>/final_step30000.pt` is a **single, unsplit** full training
+checkpoint (~15.3 GB): `model_state_dict` + `optimizer_state_dict` +
+`scheduler_state_dict`, `global_step` 30000. Verify integrity with the `.sha256`
+file next to it:
+
+```bash
+sha256sum -c final_step30000.pt.sha256
+```
+
+The `model_state_dict` is self-contained — it already includes the fine-tuned
+Qwen3-VL-2B backbone weights. Optional inference-only slimming (~15.3 GB → ~6 GB):
+
+```python
+import torch
+ck = torch.load("final_step30000.pt", map_location="cpu", weights_only=False)
+torch.save({"model_state_dict": ck["model_state_dict"], "global_step": ck["global_step"]},
+           "final_step30000_inference.pt")
+```
+
+## Base VLM
+
+Model instantiation requires the official `Qwen/Qwen3-VL-2B-Instruct` directory
+(architecture + tokenizer/processor; Apache-2.0). Its weights are overwritten by the
+checkpoint at load time, but the directory must exist locally:
+
+```bash
+huggingface-cli download Qwen/Qwen3-VL-2B-Instruct \
+    --local-dir policy/Mem-0/checkpoints/Qwen3-VL-2B-Instruct
+```
+
+## Normalization
+
+State and action are min-max normalized to `[-1, 1]` using the per-task stats in
+`norm_stats/<task>/norm_stats.json`. Always pair a checkpoint with **its own task's**
+stats at inference; predicted actions are denormalized with the same file.
+
+## License & attribution
+
+Base VLM **Qwen3-VL-2B-Instruct** is © the Qwen team, licensed **Apache-2.0**; the
+checkpoints embed fine-tuned Qwen weights, so that license applies to the
+corresponding components. RMBench / RoboTwin and the Mem-0 policy code are governed
+by their respective upstream licenses.
diff --git a/eval_results/battery_try/_result.txt b/eval_results/battery_try/_result.txt
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--- /dev/null
+++ b/eval_results/battery_try/_result.txt
@@ -0,0 +1,7 @@
+Timestamp: 2026-07-04 12:48:49
+
+Instruction Type: unseen
+
+Success Rate: 0.21
+
+Reward: 0.0
diff --git a/eval_results/blocks_ranking_try/_result.txt b/eval_results/blocks_ranking_try/_result.txt
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--- /dev/null
+++ b/eval_results/blocks_ranking_try/_result.txt
@@ -0,0 +1,7 @@
+Timestamp: 2026-07-07 09:06:03
+
+Instruction Type: unseen
+
+Success Rate: 0.15
+
+Reward: 0.0
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+
+Instruction Type: unseen
+
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+
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diff --git a/eval_results/press_button/_result.txt b/eval_results/press_button/_result.txt
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+Timestamp: 2026-07-10 14:24:34
+
+Instruction Type: unseen
+
+Success Rate: 0.02
+
+Reward: 0.0
diff --git a/eval_results/results.md b/eval_results/results.md
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+# Mn Evaluation Results
+
+`task_config = demo_clean`, `instruction_type = unseen`, 100 episodes per task.
+Each task is evaluated with its own separately trained execution-module checkpoint
+and its own normalization stats.
+
+| Task               | action_horizon | Success Rate | Reward |
+|--------------------|:--------------:|:------------:|:------:|
+| battery_try        | 15             | **0.21**     | 0.00   |
+| blocks_ranking_try | 15             | **0.15**     | 0.00   |
+| cover_blocks       | 8              | **0.76**     | 0.82   |
+| press_button       | 30             | **0.02**     | 0.00   |
+| **Average**        | —              | **0.285**    | —      |
+
+## Action horizon
+
+Per-task inference-time `action_horizon` settings:
+
+- `battery_try` — **15**
+- `blocks_ranking_try` — **15**
+- `cover_blocks` — **8**
+- `press_button` — **30**
+
+All results above were produced with these values.
+
+## Files
+
+- `<task>/episode0.mp4 … episode99.mp4` — full rollout videos (100 per task)
+- `<task>/_result.txt` — raw score file for that run