许可证: mit
库名称: transformers
流水线标签: 文本生成
标签:
代码库对应:
ThinkEdit-deepseek-llama3-8b
(我们还发布了ThinkEdit-deepseek-qwen-1.5b和ThinkEdit-deepseek-qwen-14b版本)
作者: 孙崇恩, 严戈, 翁翠薇
论文: ThinkEdit: 通过可解释权重编辑缓解推理模型中的过度简短思维
代码: https://github.com/Trustworthy-ML-Lab/ThinkEdit
简介
增强推理能力的模型有时会因生成过于简短、抽象的思维链(CoT)推理而失败,影响其准确性。
ThinkEdit是一种轻量级的权重编辑方法,能够:
- 识别约2%的"简短推理"注意力头
- 仅编辑约0.1%的总参数
- 从其输出中移除"简短推理"方向
- 提升性能,特别是在推理痕迹较短的案例上
完整性能结果
1. 总体准确率
模型 |
GSM8K |
MMLU小学数学 |
MATH-1级 |
MATH-5级 |
MATH-500 |
deepseek-qwen-14b |
90.80 ± 0.36 |
95.08 ± 0.65 |
96.32 ± 0.35 |
90.25 ± 0.72 |
91.48 ± 0.55 |
ThinkEdit-deepseek-qwen-14b |
93.50 ± 0.31 |
96.53 ± 0.54 |
96.50 ± 0.46 |
91.15 ± 0.59 |
91.78 ± 0.58 |
deepseek-llama3-8b |
82.26 ± 0.91 |
96.01 ± 0.62 |
93.46 ± 0.84 |
85.49 ± 0.83 |
87.26 ± 1.16 |
ThinkEdit-deepseek-llama3-8b |
88.97 ± 0.78 |
96.08 ± 0.86 |
94.12 ± 0.47 |
85.91 ± 0.48 |
87.60 ± 0.81 |
deepseek-qwen-1.5b |
79.15 ± 1.08 |
68.52 ± 1.56 |
93.00 ± 0.33 |
75.48 ± 0.90 |
82.22 ± 1.29 |
ThinkEdit-deepseek-qwen-1.5b |
83.34 ± 0.79 |
86.24 ± 1.12 |
93.89 ± 0.76 |
74.94 ± 0.85 |
82.74 ± 0.77 |
2. 简短推理案例准确率(前5%/10%/20%)
模型 |
GSM8K |
MMLU小学数学 |
MATH-1级 |
MATH-5级 |
MATH-500 |
deepseek-qwen-14b |
96.31 / 95.65 / 92.93 |
93.89 / 96.22 / 95.60 |
99.52 / 99.30 / 97.70 |
89.39 / 94.32 / 96.25 |
86.40 / 91.40 / 93.50 |
ThinkEdit-deepseek-qwen-14b |
96.62 / 96.03 / 96.12 |
96.11 / 96.22 / 96.27 |
100.00 / 99.77 / 98.85 |
95.76 / 97.65 / 98.07 |
89.60 / 92.60 / 94.70 |
deepseek-llama3-8b |
88.92 / 87.18 / 85.82 |
97.22 / 96.49 / 96.80 |
97.14 / 94.88 / 94.83 |
78.64 / 88.79 / 93.41 |
82.00 / 81.40 / 88.30 |
ThinkEdit-deepseek-llama3-8b |
97.08 / 95.27 / 93.95 |
97.78 / 98.65 / 97.87 |
100.00 / 99.30 / 98.62 |
95.61 / 96.89 / 97.12 |
92.80 / 93.60 / 94.40 |
deepseek-qwen-1.5b |
88.46 / 87.48 / 85.02 |
62.78 / 62.16 / 60.53 |
97.62 / 95.12 / 93.91 |
91.52 / 95.00 / 95.72 |
82.40 / 89.80 / 93.40 |
ThinkEdit-deepseek-qwen-1.5b |
92.46 / 92.37 / 92.05 |
77.22 / 80.54 / 79.73 |
96.19 / 95.81 / 97.36 |
93.79 / 95.83 / 95.80 |
92.80 / 94.40 / 94.90 |
3. 推理长度(前5%/10%/20%最短回答)
模型 |
GSM8K |
MMLU小学数学 |
MATH-1级 |
MATH-5级 |
MATH-500 |
deepseek-qwen-14b |
76.6 / 86.5 / 99.1 |
65.8 / 72.2 / 80.6 |
93.7 / 114.3 / 188.6 |
628.8 / 858.4 / 1125.9 |
198.7 / 434.3 / 697.0 |
ThinkEdit-deepseek-qwen-14b |
95.4 / 106.3 / 120.2 |
79.1 / 87.1 / 98.7 |
125.1 / 150.2 / 243.4 |
698.5 / 906.6 / 1157.2 |
270.2 / 492.6 / 733.3 |
deepseek-llama3-8b |
73.0 / 83.1 / 96.6 |
371.0 / 438.1 / 518.2 |
80.3 / 97.2 / 130.3 |
617.9 / 854.9 / 1126.5 |
159.5 / 357.5 / 644.5 |
ThinkEdit-deepseek-llama3-8b |
93.2 / 106.9 / 127.4 |
396.5 / 464.2 / 543.2 |
137.4 / 173.3 / 277.1 |
791.2 / 954.8 / 1185.1 |
305.2 / 506.3 / 737.6 |
deepseek-qwen-1.5b |
78.8 / 89.4 / 103.0 |
61.6 / 68.5 / 77.6 |
88.8 / 110.3 / 219.7 |
804.6 / 1017.9 / 1314.0 |
249.7 / 506.5 / 760.7 |
ThinkEdit-deepseek-qwen-1.5b |
97.2 / 109.4 / 126.3 |
75.9 / 85.0 / 99.5 |
127.9 / 174.1 / 416.4 |
818.0 / 984.5 / 1214.3 |
435.0 / 612.9 / 800.6 |
使用方法
ThinkEdit模型的使用方法与原始deepseek-distilled模型完全相同。
引用
@misc{sun2025thinkedit,
title={ThinkEdit: 通过可解释权重编辑缓解推理模型中的过度简短思维},
author={孙崇恩 and 严戈 and 翁翠薇},
year={2025},
eprint={2503.22048},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2503.22048},
}