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README.md
14
README.md
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@ -351,8 +351,8 @@ We tested ReMe on Appworld using qwen3-8b:
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| Method | pass@1 | pass@2 | pass@4 |
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|--------------|-----------|-----------|-----------|
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| without Reme | 0.083 | 0.140 | 0.228 |
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| with Reme | **0.109** | **0.175** | **0.281** |
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| without ReMe | 0.083 | 0.140 | 0.228 |
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| with ReMe | **0.109** | **0.175** | **0.281** |
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Pass@K measures the probability that at least one of the K generated samples successfully completes the task (
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score=1).
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@ -362,7 +362,7 @@ You can find more details on reproducing the experiment in [quickstart.md](cookb
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### 🧊 Frozenlake Experiment
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| Without memory | With memory |
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| without ReMe | with ReMe |
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|:-------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------:|
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| <p align="center"><img src="doc/figure/frozenlake_failure.gif" alt="GIF 1" width="30%"></p> | <p align="center"><img src="doc/figure/frozenlake_success.gif" alt="GIF 2" width="30%"></p> |
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@ -370,8 +370,8 @@ We tested on 100 random frozenlake maps using qwen3-8b:
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| Method | pass rate |
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|--------------|------------------|
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| without Reme | 0.66 |
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| with Reme | 0.72 **(+9.1%)** |
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| without ReMe | 0.66 |
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| with ReMe | 0.72 **(+9.1%)** |
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You can find more details on reproducing the experiment in [quickstart.md](cookbook/frozenlake/quickstart.md).
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@ -381,8 +381,8 @@ We tested ReMe on BFCL-V3 multi-turn-base (randomly split 50train/150val) using
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| Method | pass@1 | pass@2 | pass@4 |
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|--------------|---------------------|---------------------|---------------------|
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| without Reme | 0.2472 | 0.2733 | 0.2922 |
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| with Reme | 0.3061 **(+5.89%)** | 0.3500 **(+7.67%)** | 0.3888 **(+9.66%)** |
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| without ReMe | 0.2472 | 0.2733 | 0.2922 |
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| with ReMe | 0.3061 **(+5.89%)** | 0.3500 **(+7.67%)** | 0.3888 **(+9.66%)** |
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## 📚 Resources
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14
README_ZH.md
14
README_ZH.md
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@ -333,8 +333,8 @@ response = requests.post("http://localhost:8002/retrieve_task_memory", json={
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| 方法 | pass@1 | pass@2 | pass@4 |
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|--------------|-----------|-----------|-----------|
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| without Reme | 0.083 | 0.140 | 0.228 |
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| with Reme | **0.109** | **0.175** | **0.281** |
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| without ReMe | 0.083 | 0.140 | 0.228 |
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| with ReMe | **0.109** | **0.175** | **0.281** |
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Pass@K 衡量的是在生成的 K 个样本中,至少有一个成功完成任务(score=1)的概率。
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当前实验使用的是一个内部的 AppWorld 环境,可能存在轻微差异。
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@ -344,7 +344,7 @@ Pass@K 衡量的是在生成的 K 个样本中,至少有一个成功完成任
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### 🧊 Frozenlake 实验
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| 不使用memory | 使用memory |
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| 不使用ReMe | 使用ReMe |
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|:-------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------:|
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| <p align="center"><img src="doc/figure/frozenlake_failure.gif" alt="GIF 1" width="30%"></p> | <p align="center"><img src="doc/figure/frozenlake_success.gif" alt="GIF 2" width="30%"></p> |
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@ -352,8 +352,8 @@ Pass@K 衡量的是在生成的 K 个样本中,至少有一个成功完成任
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| 方法 | pass rate |
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|--------------|------------------|
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| without Reme | 0.66 |
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| with Reme | 0.72 **(+9.1%)** |
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| without ReMe | 0.66 |
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| with ReMe | 0.72 **(+9.1%)** |
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你可以在 [quickstart.md](cookbook/frozenlake/quickstart.md) 中找到复现实验的更多细节。
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@ -363,8 +363,8 @@ Pass@K 衡量的是在生成的 K 个样本中,至少有一个成功完成任
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| 方法 | pass@1 | pass@2 | pass@4 |
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|--------------|---------------------|---------------------|---------------------|
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| without Reme | 0.2472 | 0.2733 | 0.2922 |
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| with Reme | 0.3061 **(+5.89%)** | 0.3500 **(+7.67%)** | 0.3888 **(+9.66%)** |
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| without ReMe | 0.2472 | 0.2733 | 0.2922 |
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| with ReMe | 0.3061 **(+5.89%)** | 0.3500 **(+7.67%)** | 0.3888 **(+9.66%)** |
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## 📚 相关资源
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