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# this is .py for store constants
DATA_DIR="./data/data.json"
MODEL_INFO = ["Model Name", "Language Model"]
AVG_INFO = ["Avg. All"]
ME_INFO=["Method Name", "Language Model"]
# KE 固定信息
KE_Data_INFO = ["FewNERD", "FewRel", "InstructIE-en", "MAVEN","WikiEvents"]
KE_TASK_INFO = ["Avg. All", "FewNERD", "FewRel", "InstructIE-en", "MAVEN","WikiEvents"]
KE_CSV_DIR = "./ke_files/result-kgc.csv"
DATA_COLUMN_NAMES =["locality","labels","concept","text"]
KE_TABLE_INTRODUCTION = """In the table below, we summarize each task performance of all the models. We use F1 score(%) as the primary evaluation metric for each tasks.
"""
RESULT_COLUMN_NAMES= ["DataSet","Metric","Metric","ICE","AdaLoRA","MEND","ROME","MEMIT","FT-L","FT"]
DATA_STRUCT="""
Datasets ZsRE Wikirecent Wikicounterfact WikiBio
Train 10,000 570 1455 592
Test 1230 1266 885 1392
"""
TITLE = """# KnowEdit: a dataset for knowledge editing"""
BACKGROUND="""
Large Language Models (LLMs) have shown extraordinary capabilities in understanding and generating text that closely mirrors human communication. However, a primary limitation lies in the significant computational demands during training, arising from their extensive parameterization.There is an increasing interest in efficient, lightweight methods for onthe-fly model modifications. To this end, recent years have seen a burgeoning in the techniques of knowledge editing for LLMs, which aim to efficiently modify LLMs’ behaviors within specific domains while preserving overall performance across various inputs.
"""
LEADERBORAD_INTRODUCTION = """
This is the dataset for knowledge editing. It contains six tasks: ZsRE, Wiki<sub>recent</sub>, Wiki<sub>counterfact</sub>, WikiBio, ConvSent and Sanitation. This repo shows the former 4 tasks and you can get the data for ConvSent and Sanitation from their original papers.
"""
DATA_SCHEMA =""" {
"subject": xxx,
"target_new": xxx,
"prompt": xxx,
"portability":{
"Logical_Generalization": [],
...
}
"locality":{
"Relation_Specificity": [],
...
}
}"""
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
CITATION_BUTTON_TEXT = r"""@article{tan2023evaluation,
title={Evaluation of ChatGPT as a question answering system for answering complex questions},
author={Yiming Tan and Dehai Min and Yu Li and Wenbo Li and Nan Hu and Yongrui Chen and Guilin Qi},
journal={arXiv preprint arXiv:2303.07992},
year={2023}
}
@article{gui2023InstructIE,
author = {Honghao Gui and Jintian Zhang and Hongbin Ye and Ningyu Zhang},
title = {InstructIE: {A} Chinese Instruction-based Information Extraction Dataset},
journal = {arXiv preprint arXiv:2303.07992},
year = {2023}
}
@article{yao2023edit,
author = {Yunzhi Yao and Peng Wang and Bozhong Tian and Siyuan Cheng and Zhoubo Li and Shumin Deng and Huajun Chen and Ningyu Zhang},
title = {Editing Large Language Models: Problems, Methods, and Opportunities},
journal = {arXiv preprint arXiv:2305.13172},
year = {2023}
}
"""
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