/DEEM

🤗 DEEM: Dynamic Experienced Expert Modeling for Stance Detection

This repo includes codes and examples for paper [📖 ArXiv]DEEM: Dynamic Experienced Expert Modeling for Stance Detection.

Our Method

In this paper, different from existing multi-agent works that require detailed descriptions and use fixed experts, we propose a Dynamic Experienced Expert Modeling (DEEM) method which can leverage the generated experienced experts and let LLMs reason in a semi-parametric way, making the experts more generalizable and reliable. Experimental results demonstrate that DEEM consistently achieves the best results on three standard benchmarks, outperforms methods with self-consistency reasoning, and reduces the bias of LLMs.

The model structures are shown in the following figure.

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Comparison with other methods

Method Including Explanations Multi-Roles Verified Experts Reasoning Type
Few-Shot ❌ ❌ - Gen
CoT ✅ ❌ - Gen
Auto-CoT ✅ ❌ - Re+Gen
ExpertPrompt ✅ ❌ ❌ Gen
SPP ✅ ✅ ❌ Gen
DEEM(ours) ✅ ✅ ✅ Re+Gen

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Casestudy

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Reference

📑 If you find our project helpful to your research, please consider citing:

@misc{wang2024deem,
      title={DEEM: Dynamic Experienced Expert Modeling for Stance Detection}, 
      author={Xiaolong Wang and Yile Wang and Sijie Cheng and Peng Li and Yang Liu},
      year={2024},
      eprint={2402.15264},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}