The official repository for paper "Finding Support Examples for In-Context Learning" (EMNLP 2023 Findings). Check out our paper for more information.
Download the train_data and test_data from Google Drive, and put them in the current folder.
conda create -n icl_support_examples python=3.8
conda activate icl_support_examples
conda install pytorch=1.7.1 -c pytorch
pip install transformers==4.3.0
pip install fitlog
# dataset=[sst2,sst5,amazon_b,mr,subj,agnews,trec,dbpedia]
CUDA_VISIBLE_DEVICES=0 bash commands/run_[dataset].sh
and then see the performance through fitlog as:
fitlog log fitlog_search_examples
Then see fitlog in your browser.
@article{icl_support_example,
author = {Xiaonan Li and
Xipeng Qiu},
title = {Finding Supporting Examples for In-Context Learning},
journal = {CoRR},
volume = {abs/2302.13539},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2302.13539},
doi = {10.48550/ARXIV.2302.13539},
eprinttype = {arXiv},
eprint = {2302.13539},
timestamp = {Tue, 28 Feb 2023 14:02:05 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2302-13539.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}