Official Repo of paper "KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction". In the paper, we propose KnowCoder, the most powerful large language model so far for universal information extraction.
☆107May 28, 2025Updated last year
Alternatives and similar repositories for KnowCoder
Users that are interested in KnowCoder are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- [EMNLP 2023] Semi-automatic Data Enhancement for Document-Level Relation Extraction with Distant Supervision from Large Language Models☆17Oct 30, 2023Updated 2 years ago
- [ACL 23] CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors☆42Dec 14, 2025Updated 6 months ago
- Guideline following Large Language Model for Information Extraction☆441Oct 27, 2024Updated last year
- Completing the Puzzle of All-in-One Event Understanding Benchmark with Event Arguments☆14Mar 12, 2024Updated 2 years ago
- The official implementation of ICLR 2025 paper "Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models".☆18Apr 25, 2025Updated last year
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Code and Data for "SCTc-TE: A Comprehensive Formulation and Benchmark for Temporal Event Forecasting""☆16Feb 2, 2024Updated 2 years ago
- ☆20Feb 20, 2025Updated last year
- Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)☆1,059Nov 18, 2024Updated last year
- ☆85Sep 14, 2024Updated last year
- TECHS: Temporal Logical Graph Networks for Explainable Extrapolation Reasoning☆10Jan 16, 2024Updated 2 years ago
- Universal information extraction with instruction learning☆396Feb 28, 2025Updated last year
- Code for our ACL-2023 paper AMPERE: AMR-Aware Prefix for Generation-Based Event Argument Extraction Model