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README.md
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🌟 **ARES** — Adaptive Multimodal Reasoning Framework
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Two-stage adaptive reasoning: cold-start + entropy-shaped RL.
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🔑 Highlights
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Balanced reasoning across easy & hard tasks via token-level entropy shaping.
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SOTA efficiency–accuracy tradeoffs on diverse multimodal and textual benchmarks.
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📚 Training Pipeline
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1. **Adaptive Cold-Start** — curate difficulty-aware reasoning traces
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2. **Entropy-Shaped RL (AEPO)** — trigger exploration via high-window entropy, hierarchical rewards
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📂 Resources
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- **Paper**: ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy Shaping :contentReference[oaicite:0]{index=0}
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- **Code**: [GitHub – shawn0728/ARES](https://github.com/shawn0728/ARES) :contentReference[oaicite:1]{index=1}
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📌 Citation
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```
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@misc{chen2025aresmultimodaladaptivereasoning,
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title={ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy Shaping},
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author={Shuang Chen and Yue Guo and Yimeng Ye and Shijue Huang and Wenbo Hu and Haoxi Li and Manyuan Zhang and Jiayu Chen and Song Guo and Nanyun Peng},
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year={2025},
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eprint={2510.08457},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2510.08457},
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}
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```
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---
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Give **ARES** a shot and tell us what reasoning challenges it helps you solve! 🚀
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