Summary of Teleclass: Taxonomy Enrichment and Llm-enhanced Hierarchical Text Classification with Minimal Supervision, by Yunyi Zhang et al.
TELEClass: Taxonomy Enrichment and LLM-Enhanced Hierarchical Text Classification with Minimal Supervision
by Yunyi Zhang, Ruozhen Yang, Xueqiang Xu, Rui Li, Jinfeng Xiao, Jiaming Shen, Jiawei Han
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed Hierarchical Text Classification (HTC) method, called TELEClass, aims to categorize documents into a label taxonomy with minimal supervision. Unlike fully or semi-supervised methods that require extensive human annotation, TELEClass utilizes the sole class name of each node as the only supervision. The approach leverages large language models (LLMs) and weakly-supervised hierarchical text classification methods to incorporate rich information from unlabeled corpora. By combining LLM-based data annotation and generation methods with task-specific features, TELEClass demonstrates significant performance gains over previous baselines while reducing inference costs. This method has potential applications in web content analysis, semantic indexing, and other areas. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to categorize documents into different categories. Most methods need lots of help from humans to make it work. But what if we could do it with just a little bit of help? That’s what the TELEClass method does. It uses big language models and some clever tricks to sort documents into categories. The best part is that it doesn’t require a lot of human effort, which makes it really efficient. This technology can be used for things like analyzing web content and indexing texts. |
Keywords
* Artificial intelligence * Inference * Semi supervised * Supervised * Text classification
