Merge branch 'main' into patch-2

README.md

@@ -202,6 +202,10 @@ template, verbalizer, training paradigms, etc.
 22. **Black-Box Tuning for Language-Model-as-a-Service.** ICML 2022. ![](https://img.shields.io/badge/Black--Box_Tuning-blue) ![](https://img.shields.io/badge/Derivative--free_optimization-red)
 
     *Tianxiang Sun, Yunfan Shao, Hong Qian, Xuanjing Huang, Xipeng Qiu* [[pdf](https://arxiv.org/abs/2201.03514)], [[project](/~https://github.com/txsun1997/Black-Box-Tuning)], 2022.1
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+23. **Black-box Prompt Learning for Pre-trained Language Models.** Preprint. ![](https://img.shields.io/badge/-Black--Box%20Prompt%20Learning%20-blue) ![](https://img.shields.io/badge/Derivative--free_optimization-red)
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+    *Shizhe Diao, Xuechun Li, Yong Lin, Zhichao Huang, Tong Zhang* [[pdf](https://arxiv.org/abs/2201.08531)], 2022.1   
 
 ### Analysis
 This section contains the analysis of prompt learning methods, including but not limited to why does prompt learning work, various properties of prompt learning methods, limilation of prompt learning methods.
@@ -440,11 +444,16 @@ This section contains the prompt learning methods designed for various NLP task.
 31. **Learning to Compose Soft Prompts for Compositional Zero-Shot Learning.** Preprint 2022. ![](https://img.shields.io/badge/CSP-blue) ![](https://img.shields.io/badge/Continous_Template-red)
 
       *Nihal V. Nayak\*, Peilin Yu\*, Stephen H. Bach* [[pdf](https://arxiv.org/abs/2204.03574)], [[project](/~https://github.com/BatsResearch/csp)]
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 32. **Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning.**  Preprint. ![](https://img.shields.io/badge/RetroPrompt-blue)  ![](https://img.shields.io/badge/Continuous_Template-red)
 
       *Xiang Chen, Lei Li, Ningyu Zhang, Xiaozhuan Liang, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen.* [[pdf](https://arxiv.org/abs/2205.14704)], 2022.5
 
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+33. **Exploring Length Generalization in Large Language Models.** Preprint 2022. ![](https://img.shields.io/badge/Continuous_Template-red)
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+      *Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur* [[pdf](https://arxiv.org/abs/2207.04901)]
 
 
 ## Contribution