This is interesting, but why don’t they link to the paper? Or at least give its title? The paper is «“Low-Resource” Text Classification: A Parameter-Free Class

This is interesting, but why don’t they link to the paper? Or at least give its title? The paper is «“Low-Resource” Text Classification: A Parameter-Free Classification Method with Compressors»: ACL Anthology, has PDF link: https://aclanthology.org/2023.findings-acl.426/ https://aclanthology.org/2023.findings-acl.426/ Arxiv, has PDF link: https://arxiv.org/abs/2212.09410 https://arxiv.org/abs/2212.09410 arXiv Vanity, HTML render of it: https://www.arxiv-vanity.com/papers/2212.09410/ https://www.arxiv-vanity.com/papers/2212.09410/ ResearchGate, has PDF link: https://www.researchgate.net/publication/366423949_Less_is_More_Parameter-Free_Text_Classification_with_Gzip https://www.researchgate.net/publication/366423949_Less_is_M... This is Listing 1: ”Python Code for Text Classification with gzip.” import gzip import numpy as np for (x1, _) in test_set: Cx1 = len(gzip.compress(x1.encode())) distance_from_x1 = [] for (x2, _) in training_set: Cx2 = len(gzip.compress(x2.encode()) x1x2 = " ".join([x1, x2]) Cx1x2 = len(gzip.compress(x1x2.encode()) ncd = (Cx1x2 - min(Cx1,Cx2)) / max(Cx1, Cx2) distance_from_x1.append(ncd) sorted_idx = np.argsort(np.array(distance_from_x1)) top_k_class = training_set[sorted_idx[:k], 1] predict_class = max(set(top_k_class), key=top_k_class.count) Abstract: In this paper, we propose a non-parametric alternative to DNNs that’s easy, lightweight, and universal in text classification: a combi- nation of a simple compressor like gzip with a k-nearest-neighbor classifier. Without any training parameters, our method achieves re- sults that are competitive with non-pretrained deep learning methods on six in-distribution datasets. It even outperforms BERT on all five OOD datasets, including four low-resource lan- guages. Our method also excels in the few-shot setting, where labeled data are too scarce to train DNNs effectively. Code is available at https://github.com/bazingagin/npc_gzip https://github.com/bazingagin/npc_gzip Ah, this was already mentioned a few days ago in HN: 73 comments: “Gzip and KNN Outperforms Transformers on Text Classification” https://news.ycombinator.com/item?id=36707193 https://news.ycombinator.com/item?id=36707193 7 comments: “Plain old gzip+kNN outperforms BERT and other DNNs” https://news.ycombinator.com/item?id=36705472 https://news.ycombinator.com/item?id=36705472 7 comments: “A Parameter-Free Classification Method with Compressors” https://news.ycombinator.com/item?id=36707509 https://news.ycombinator.com/item?id=36707509