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phanviethoang1512
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Model Details
Model Provider
phanviethoang1512
Model Tree
Qwen/Qwen3-8B
Input Modalities
Output Modalities
Supported Functionality
Mean task score of the five Qwen3-8B agents from the paper across eight UserRL environments, three of them held out from training (IntentionGym, TelepathyGym, SearchGym), under nine evaluation user models that were not used in training.
| Agent | Training user | Objective | Mean score |
|---|---|---|---|
| Base | none | SFT | 18.49 |
| UserRL | GPT-5.5 | GRPO | 26.10 |
| InfoPO (this model) | MIMESIS-9B | InfoPO | 26.65 |
| UserRL+ | MIMESIS-9B | GRPO | 29.54 |
| CSD | MIMESIS-9B | GRPO + CSD | 31.09 |
InfoPO and CSD use the same training user, so they differ in their optimization objectives rather than in simulator choice. Each score is the mean over the nine evaluation users; per-user and per-environment scores are in Appendix D of the paper.
RL starts from the Base checkpoint, Qwen3-8B after a supervised warm start, and trains on five UserRL environments: TravelGym, TurtleGym, FunctionGym, TauGym and PersuadeGym. The full configuration is in Appendix D of the paper, and the training scripts are in the agent directory of the code release.
The model loads like Qwen3-8B. To evaluate it in the eight environments, install the agent code, serve a user model as described there, and run from the agent directory:
bash
bash scripts/run_eval.sh phanviethoang1512/Qwen3-8B-InfoPO-Agent infopobibtex
@article{phan2026mimesis, title = {{MIMESIS}: Learning User Simulators as Training Environments for Interactive Agents}, author = {Phan, Hoang and Huynh, Dat and Zhmoginov, Andrey and Zeng, Qi and Mu, Wancen and Cao, Yue and Bi, Shengjie and He, Yun and Oh, Changdae and Lei, Deren}, journal = {arXiv preprint arXiv:2610.09484}, year = {2026}}@article{phan2026mimesis, title = {{MIMESIS}: Learning User Simulators as Training Environments for Interactive Agents}, author = {Phan, Hoang and Huynh, Dat and Zhmoginov, Andrey and Zeng, Qi and Mu, Wancen and Cao, Yue and Bi, Shengjie and He, Yun and Oh, Changdae and Lei, Deren}, journal = {arXiv preprint arXiv:2610.09484}, year = {2026}}