Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
| Date | Stars |
|---|---|
| 2026-07-24 | 1060 |
| 2026-07-25 | 1060 |
| 2026-07-28 | 1060 |
| 2026-07-30 | 1060 |
| 2026-07-31 | 1060 |
| 2026-08-06 | 1060 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Awesome-LLM4IE-Papers 🔥🔥🔥 **The article has been accepted by Frontiers of Computer Science (FCS)**. --- Awesome papers about generative Information extraction using LLMs <p align="center" width="80%"> <img src="./image/intro.png" style="width: 50%"> </p> The organization of papers is discussed in our survey: [Large Language Models for Generative Information Extraction: A Survey](https://link.springer.com/article/10.1007/s11704-024-40555-y). If you find any relevant academic papers that have not been included in our research, please submit a request for an update. We welcome contributions from everyone. If any suggestions or mistakes, please feel free to let us know via email at **[email protected]** and **[email protected]**. We appreciate your feedback and help in improving our work. If you find our survey useful for your research, please cite the following paper: @article{xu2024large, title={Large language models for generative information extraction: A survey}, author={Xu, Derong and Chen, Wei and Peng, Wenjun and Zhang, Chao and Xu, Tong and Zhao, Xiangyu and Wu, Xian and Zheng, Yefeng and Wang, Yang and Chen, Enhong}, journal={Frontiers of Computer Science}, volume={18}, number={6}, pages={186357}, year={2024}, publisher={Springer} } ## 📒 Table of Contents - [Information Extraction tasks](#information-extraction-tasks) - [Named Entity Recognition](#named-entity-recognition) - [Relation Extraction ](#relation-extraction) - [Event Extraction](#event-extraction) - [Universal Information Extraction](#universal-information-extraction) - [Information Extraction Techniques](#information-extraction-techniques) - [Supervised Fine-tuning](#supervised-fine-tuning) - [Few-shot ](#few-shot) - [Zero-shot](#zero-shot) - [Data Augmentation](#data-augmentation) - [Prompts Design](#prompts-design) - [Constrained Decoding Generation](#constrained-decoding-generation) - [Specific Domain](#specific-domain) - [Evaluation and Analysis](#evaluation-and-analysis) - [Project and Toolkit](#project-and-toolkit) - ⏰ [Recently Updated Papers](#recently-updated-papers) (After 2024/09/04, the updated papers is here~) - ⭐️ [Datasets](#datasets) (with Download Link~) ## 💡 News - **Update Logs** - The details can be find in <code>./update_new_papers_list</code>. - **2024/09/04** Add 22 papers - **2024/06/06** Add 41 papers - **2024/03/30** Add 27 papers - **2024/03/29** Add 20 papers # Information Extraction tasks A taxonomy by various tasks. ## Named Entity Recognition Models targeting only ner tasks. ### Entity Typing | Paper | Venue | Date | Code | | :----- | :--------------: | :------- | :---------: | | [Calibrated Seq2seq Models for Efficient and Generalizable Ultra-fine Entity Typing](https://aclanthology.org/2023.findings-emnlp.1040/) | EMNLP Findings | 2023-12 | [GitHub](https://github.com/yanlinf/CASENT) | | [Generative Entity Typing with Curriculum Learning](https://arxiv.org/abs/2210.02914) | EMNLP | 2022-12 | [GitHub](https://github.com/siyuyuan/GET) | ### Entity Identification & Typing | Paper | Venue | Date | Code | | :----- | :--------------: | :------- | :---------: | | [Granular Entity Mapper: Advancing Fine-grained Multimodal Named Entity Recognition and Grounding](https://aclanthology.org/2024.findings-emnlp.183/) | EMNLP Findings | 2024 | | | [Double-Checker: Large Language Model as a Checker for Few-shot Named Entity Recognition](https://aclanthology.org/2024.findings-emnlp.180/) | EMNLP Findings | 2024 | [GitHub](https://github.com/fanshu6hao/Double-Checker) | | [VerifiNER: Verification-augmented NER via Knowledge-grounded Reasoning with Large Language Models](https://aclanthology.org/2024.acl-long.134/) | ACL | 2024 | [GitHub](https://github.com/emseoyk/VerifiNER) | | [ProgGen: Generating Named Entity Recognition Datasets Step-by
Excerpt of 110,416 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e6b1a85ae8f088a6, topic:named-entity-recognition, topic:information-extraction, readme:named entity recognition
