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Model: phanviethoang1512/Qwen3-8B-Base-Agent
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3-8B
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+  - agent
+  - multi-turn
+  - reinforcement-learning
+---
+
+# Qwen3-8B-Base-Agent
+
+The Base agent from MIMESIS: Qwen3-8B after a short supervised warm start, before multi-turn reinforcement learning. The RL agents in the collection all start from this checkpoint.
+
+[Paper](https://arxiv.org/abs/2610.09484) · [Code](https://github.com/VietHoang1512/mimesis) · [Project page](https://viethoang1512.github.io/mimesis/) · [Collection](https://huggingface.co/collections/phanviethoang1512/mimesis)
+
+## Results
+
+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 (this model)** | none | SFT | 18.49 |
+| [UserRL](https://huggingface.co/phanviethoang1512/Qwen3-8B-UserRL-Agent) | GPT-5.5 | GRPO | 26.10 |
+| [InfoPO](https://huggingface.co/phanviethoang1512/Qwen3-8B-InfoPO-Agent) | MIMESIS-9B | InfoPO | 26.65 |
+| [UserRL+](https://huggingface.co/phanviethoang1512/Qwen3-8B-UserRL-Plus-Agent) | MIMESIS-9B | GRPO | 29.54 |
+| [CSD](https://huggingface.co/phanviethoang1512/Qwen3-8B-CSD-Agent) | MIMESIS-9B | GRPO + CSD | **31.09** |
+
+Each score is the mean over the nine evaluation users; per-user and per-environment scores are in Appendix D of the paper.
+
+## Training
+
+Full fine-tuning of Qwen3-8B on about 1,000 multi-turn trajectories from the five training environments (TravelGym, TurtleGym, FunctionGym, TauGym and PersuadeGym). The trajectories were generated with GPT-4o playing both the agent and the user, keeping the top-ranked ones in each environment, and each agent turn is reasoning in `<think>` tags followed by one tool call.
+
+## Usage
+
+The model loads like Qwen3-8B. To evaluate it in the eight environments, install the [agent code](https://github.com/VietHoang1512/mimesis/tree/main/agent), serve a user model as described there, and run from the `agent` directory:
+
+```bash
+bash scripts/run_eval.sh phanviethoang1512/Qwen3-8B-Base-Agent base
+```
+
+## Citation
+
+```bibtex
+@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}
+}
+```