📷 This is the code repository for the paper: AutoCAP: Towards Automatic Cross-lingual Alignment Planning for Zero-shot Chain-of-Thought. ACL 2024 Findings.[PDF]

Environment installation command:

pip install -r requirements.txt

First modify the output path /temperature in manage_res_request.py:

INPUT_DIR = "mgsm/input"
OUTPUT_DIR = "auto-clsp-exp/mgsm/l6-01-tp02-tp02"
TEMPERATURE_1 = 0.2
TEMPERATURE_2 = 0.2

【OPENAI KEY modification request.py】

--request_url [end url]
--api_key [api key]

Run the following command to request Automatic Language Selection Prompting and Automatic Weight Allocation Prompting.

python manage_res_request.py

Modify SELECTION_PATH to f'{OUTPUT_DIR}/output-2' from the previous stage:

【OPENAI KEY modification tool.py】

openai.api_key [api key]
openai.api_base [end url]

Run the following command to request Automatic Language Selection Prompting and Automatic Weight Allocation Prompting.

python metric4auto.py

Please create Github issues here or email Yongheng Zhang or Qiguang Chen or Libo Qin if you have any questions or suggestions.

@inproceedings{zhang-etal-2024-autocap,
    title = "{A}uto{CAP}: Towards Automatic Cross-lingual Alignment Planning for Zero-shot Chain-of-Thought",
    author = "Zhang, Yongheng  and
      Chen, Qiguang  and
      Li, Min  and
      Che, Wanxiang  and
      Qin, Libo",
    booktitle = "Findings of the Association for Computational Linguistics ACL 2024",
    month = aug,
    year = "2024",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.findings-acl.546",
    doi = "10.18653/v1/2024.findings-acl.546",
    pages = "9191--9200",
}