Awesome-Llm-Unlearning

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awesome-llm-unlearning is a repository of resources for machine unlearning in large language models. It tracks the latest research on unlearning in LLMs, including papers, surveys, frameworks, and blog posts.

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Pricing

free

Free tier

Yes

API

—

Skill level

Technical

About

What is awesome-llm-unlearning?

awesome-llm-unlearning is a comprehensive repository dedicated to machine unlearning within large language models (LLMs). It serves as a centralized hub for the latest research and developments in this critical area. The repository curates and organizes a variety of resources, including academic papers, insightful surveys, practical frameworks, and informative blog posts. It is specifically designed to support researchers and developers who are actively engaged in or interested in the field of LLM unlearning, providing them with a valuable collection of materials to advance their understanding and work.

Best used for

Staying informed and accessing research materials on machine unlearning in large language models.

Common actions

Learn about LLM unlearning

Research LLM unlearning

Find unlearning frameworks

Stay updated on LLM research

"AI Agents"face swappinggithub copilotdeepfakecollaborationworkflowslow-code/no-codeopen-sourceautomated workflow

Capabilities

Key features

LLM unlearning resources
Tracks latest research
Includes papers, surveys
Frameworks and blog posts

Target Audience

ResearchersDevelopersAI EngineersData Scientists

Integrations

Not yet documented

Pricing & Plans

free

Free

FAQs

Is there a cost associated with accessing the resources in awesome-llm-unlearning?

No, awesome-llm-unlearning is a free, open-source repository. All the curated research papers, surveys, frameworks, and blog posts are accessible without any charge, making it a valuable resource for the community.

How frequently is the awesome-llm-unlearning repository updated with new research?

The repository aims to track the latest developments in LLM unlearning. While there isn't a fixed update schedule, new papers, frameworks, and relevant blog posts are added regularly as they emerge in the research landscape.

Can I contribute my own research or relevant resources to the awesome-llm-unlearning repository?

Yes, as an open-source project, contributions are generally welcome. You can typically submit pull requests on the GitHub repository to suggest new papers, frameworks, or other valuable resources to be included.

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