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Model: nics-efc/MARSHAL-Kuhn-Poker-Qwen3-4B Source: Original Platform
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README.md
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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tags:
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- reinforcement-learning
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- multi-agent
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- self-play
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- reasoning
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base_model:
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- Qwen/Qwen3-4B
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---
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<div align="center">
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<img src="https://thu-nics.github.io/MARSHAL/static/images/header.jpg" width="100%" alt="MARSHAL Header">
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</div>
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<div align="center">
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<img src="https://thu-nics.github.io/MARSHAL/static/images/logo_with_name.png" width="200" alt="MARSHAL Logo">
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# MARSHAL: Incentivizing Multi-Agent Reasoning via Self-Play with Strategic LLMs
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### 🎉 Accepted by ICLR 2026
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://www.python.org/downloads/release/python-390/)
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[](https://arxiv.org/abs/2510.15414)
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[**🌐 Project Page**](https://thu-nics.github.io/MARSHAL/) | [**📝 Paper**](https://arxiv.org/abs/2510.15414) | [**💻 Code**](https://github.com/thu-nics/MARSHAL)
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</div>
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---
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## 🤗 Model Description
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This is the **Kuhn Poker specialist model** of the **MARSHAL** framework, initialized from **Qwen3-4B**. It has been trained via self-play on **Kuhn Poker**.
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## 📖 Overview
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We introduce **MARSHAL**, an end-to-end reinforcement learning framework designed to incentivize **M**ulti-**A**gent **R**easoning through **S**elf-play wit**H** str**A**tegic **L**LMs in a diverse range of competitive and cooperative games.
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MARSHAL addresses the challenge of credit assignment in multi-agent multi-turn self-play through two core mechanisms:
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1. **Turn-level Advantage Estimator:** Enables fine-grained credit assignment, allowing the model to accurately attribute long-term outcomes to individual actions and provide learning signals across multiple turns.
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2. **Agent-specific Advantage Normalization:** Stabilizes the training
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process by calibrating advantage estimates relative to the performance of each agent.
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### 🔥 Key Results
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By leveraging self-play across strategic games, MARSHAL (based on Qwen3-4B) demonstrates notable generalization capabilities:
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- **Strategic Games:** Achieves up to **28.7%** performance improvement on held-out games.
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- **Reasoning Benchmarks:** When integrated into leading multi-agent systems (MASs), MARSHAL yields consistent gains of up to
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- **+10.0%** on AIME
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- **+7.6%** on GPQA-Diamond
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- **+3.5%** on average across all tested benchmarks.
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### 🎮 Featured Games
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- **Competitive, perfect-information:** Tic-Tac-Toe, Connect Four.
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- **Competitive, imperfect-information:** Kuhn Poker, Leduc Hold'em.
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- **Cooperative, imperfect-information:** Mini Hanabi, Simple Hanabi.
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---
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## 🚀 Method
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<div align="center">
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<img src="https://thu-nics.github.io/MARSHAL/static/images/method_overview.svg" width="100%" alt="Overview of MARSHAL">
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</div>
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> **Figure 1: Overview of MARSHAL.**
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> **Left:** Generating player trajectories via self-play in strategic games.
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> **Middle:** Naive advantage estimation (e.g., GRPO) often fails in multi-turn settings.
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> **Right:** MARSHAL's advantage estimation ensures accurate credit assignment for multi-turn, multi-agent interactions.
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## 📊 Results
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<div align="center">
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<img src="https://thu-nics.github.io/MARSHAL/static/images/results_overview.svg" width="100%" alt="Evaluation results">
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</div>
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> **Figure 2: Performance Comparison.**
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> Evaluation of MARSHAL against baselines on strategic games and reasoning benchmarks. MARSHAL not only masters strategic games but also generalizes effectively to complex reasoning tasks within multi-agent frameworks like MAD and AutoGen.
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---
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## 🖊️ Citation
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If you find our work helpful, please cite:
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```bibtex
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@misc{yuan2025marshal,
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title={MARSHAL: Incentivizing Multi-Agent Reasoning via Self-Play with Strategic LLMs},
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author={Huining Yuan and Zelai Xu and Zheyue Tan and Xiangmin Yi and Mo Guang and Kaiwen Long and Haojia Hui and Boxun Li and Xinlei Chen and Bo Zhao and Xiao-Ping Zhang and Chao Yu and Yu Wang},
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year={2025},
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eprint={2510.15414},
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archivePrefix={arXiv},
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primaryClass={cs.AI},
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url={[https://arxiv.org/abs/2510.15414](https://arxiv.org/abs/2510.15414)},
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}
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|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151665": {
|
||||
"content": "<tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151666": {
|
||||
"content": "</tool_response>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151667": {
|
||||
"content": "<think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151668": {
|
||||
"content": "</think>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n {%- if message.content is string %}\n {%- set content = message.content %}\n {%- else %}\n {%- set content = '' %}\n {%- endif %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in content %}\n {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n {%- if enable_thinking is defined and enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- endif %}\n{%- endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user