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Mem-0-mn-RMBench

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  1. .gitattributes +44 -0
  2. README.md +94 -0
  3. eval_results/battery_try/_result.txt +7 -0
  4. eval_results/blocks_ranking_try/_result.txt +7 -0
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  6. eval_results/blocks_ranking_try/episode24.mp4 +3 -0
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  17. eval_results/blocks_ranking_try/episode83.mp4 +3 -0
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  19. eval_results/cover_blocks/_result.txt +7 -0
  20. eval_results/cover_blocks/episode1.mp4 +3 -0
  21. eval_results/cover_blocks/episode13.mp4 +3 -0
  22. eval_results/cover_blocks/episode16.mp4 +3 -0
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  49. eval_results/cover_blocks/episode98.mp4 +3 -0
  50. eval_results/press_button/_result.txt +7 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ ---
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+
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+ # Mem-0 Execution Module — Mn tasks (RMBench / RoboTwin 2.0)
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+
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+ **Per-task Mem-0 execution-module checkpoints** for four RMBench **Mn** tasks:
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+ `battery_try`, `blocks_ranking_try`, `cover_blocks`, `press_button`.
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+ Each task has its **own** executor — trained only on that task's 50-episode
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+ `demo_clean` dataset — and its **own** normalization stats (unlike the
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+ [`m1_mix` release](https://huggingface.co/qiuly/Mem-0-m1mix-RMBench), which used one
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+ joint checkpoint for all five M1 tasks).
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+
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+ - **Backbone:** Qwen3-VL-2B-Instruct (fine-tuned; weights bundled in each checkpoint)
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+ - **Action head:** DiT-B flow-matching policy (16-D action)
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+ - **Memory:** MemoryBank (instant + anchor memory fusion across the episode)
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+ - **Aux head:** subtask-end classifier
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+ - ≈ 2.67 B params per checkpoint; 30,000 training steps per task
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+
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+ ## Results
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+
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+ `task_config = demo_clean`, `instruction_type = unseen`, 100 episodes per task.
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+ `action_horizon` is the per-task inference-time setting used for these numbers.
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+
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+ | Task | action_horizon | Success Rate | Reward |
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+ |--------------------|:--------------:|:------------:|:------:|
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+ | battery_try | 15 | **0.21** | 0.00 |
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+ | blocks_ranking_try | 15 | **0.15** | 0.00 |
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+ | cover_blocks | 8 | **0.76** | 0.82 |
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+ | press_button | 30 | **0.02** | 0.00 |
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+ | **Average** | — | **0.285** | — |
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+
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+ Rollout videos (100 per task) and raw score files are under `eval_results/`
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+ (see `eval_results/results.md`).
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+
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+ ## Contents
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+
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+ ```
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+ mn_submit/
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+ ├── README.md
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+ ├── checkpoints/
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+ │ └── <task>/final_step30000.pt (+ .sha256) # one full ckpt per task, ~15.3 GB each
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+ ├── norm_stats/
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+ │ └── <task>/norm_stats.json # per-task min-max state/action stats
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+ └── eval_results/
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+ ├── results.md # scores + per-task action_horizon
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+ ├── success_rate.png
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+ └── <task>/ # _result.txt, episode*.mp4 (×100)
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+ ```
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+
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+ ## Checkpoints
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+
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+ Each `checkpoints/<task>/final_step30000.pt` is a **single, unsplit** full training
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+ checkpoint (~15.3 GB): `model_state_dict` + `optimizer_state_dict` +
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+ `scheduler_state_dict`, `global_step` 30000. Verify integrity with the `.sha256`
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+ file next to it:
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+
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+ ```bash
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+ sha256sum -c final_step30000.pt.sha256
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+ ```
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+
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+ The `model_state_dict` is self-contained — it already includes the fine-tuned
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+ Qwen3-VL-2B backbone weights. Optional inference-only slimming (~15.3 GB → ~6 GB):
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+
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+ ```python
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+ import torch
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+ ck = torch.load("final_step30000.pt", map_location="cpu", weights_only=False)
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+ torch.save({"model_state_dict": ck["model_state_dict"], "global_step": ck["global_step"]},
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+ "final_step30000_inference.pt")
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+ ```
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+
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+ ## Base VLM
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+
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+ Model instantiation requires the official `Qwen/Qwen3-VL-2B-Instruct` directory
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+ (architecture + tokenizer/processor; Apache-2.0). Its weights are overwritten by the
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+ checkpoint at load time, but the directory must exist locally:
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+
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+ ```bash
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+ huggingface-cli download Qwen/Qwen3-VL-2B-Instruct \
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+ --local-dir policy/Mem-0/checkpoints/Qwen3-VL-2B-Instruct
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+ ```
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+
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+ ## Normalization
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+
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+ State and action are min-max normalized to `[-1, 1]` using the per-task stats in
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+ `norm_stats/<task>/norm_stats.json`. Always pair a checkpoint with **its own task's**
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+ stats at inference; predicted actions are denormalized with the same file.
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+
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+ ## License & attribution
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+
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+ Base VLM **Qwen3-VL-2B-Instruct** is © the Qwen team, licensed **Apache-2.0**; the
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+ checkpoints embed fine-tuned Qwen weights, so that license applies to the
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+ corresponding components. RMBench / RoboTwin and the Mem-0 policy code are governed
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+ by their respective upstream licenses.
eval_results/battery_try/_result.txt ADDED
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+ Timestamp: 2026-07-04 12:48:49
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+
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+ Instruction Type: unseen
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+
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+ Success Rate: 0.21
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+
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+ Reward: 0.0
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+ Instruction Type: unseen
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+
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+ Success Rate: 0.15
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+
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+ Reward: 0.0
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+ Instruction Type: unseen
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+ Success Rate: 0.76
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+ Reward: 0.8199999999999998
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