Home› Projects› KnowledgeEditingPapers
KnowledgeEditingPapers
awsome-list

KnowledgeEditingPapers

Must-read Papers on Knowledge Editing for Large Language Models.

by zjunlp · GitHub
Stars
Forks
License
Created
Last commit
Category
awsome-listeasyeditfoundation-modelsMIT
View on GitHub
In plain words

Read essential papers on how to edit knowledge in large language models for better understanding and control.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
KnowledgeEditingPapers — GitHub preview card
📈 Star history
1.25k1.24k
2026-07-202026-08-31
📈 Track KnowledgeEditingPapers

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

Must-read Papers on Knowledge Editing for Large Language Models.

KnowledgeEditingPapers has 1.2k stars on GitHub. It has been forked 78 times. It has been in active development since 2022. KnowledgeEditingPapers is available under the MIT license. Its main topics are awsome-list, easyedit, foundation-models, knowledge-editing.

❓ Frequently asked questions

What is KnowledgeEditingPapers?

Must-read Papers on Knowledge Editing for Large Language Models.

Is KnowledgeEditingPapers open source?

KnowledgeEditingPapers is an open-source project. It is released under the MIT license.

Is KnowledgeEditingPapers free?

Yes. KnowledgeEditingPapers is free and open source — you can use, modify and self-host it.

What license does KnowledgeEditingPapers use?

KnowledgeEditingPapers is available under the MIT license.

🏅 Maintainer of this project?
olud.ai badge — KnowledgeEditingPapers

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=zjunlp-knowledgeeditingpapers)](https://olud.ai/project/zjunlp-knowledgeeditingpapers.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.