Awesome-LM-SSP

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Awesome-LM-SSP is a curated list of resources focusing on the safety, security, and privacy of large models (LMs). It helps researchers and practitioners stay informed about LM trustworthiness, especially for multi-modal LMs.

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Pricing

free

Free tier

Yes

API

—

Skill level

Technical

About

What is Awesome-LM-SSP?

Awesome-LM-SSP provides a curated collection of resources dedicated to the safety, security, and privacy aspects of large models (LMs). The repository specifically highlights multi-modal LMs, encompassing vision-language and diffusion models. It serves as a continuously updated resource, with manually collected materials, to assist researchers and practitioners in keeping abreast of the latest developments and best practices concerning the trustworthiness of large models.

Best used for

Staying informed about the latest research and best practices in large model safety, security, and privacy, particularly for multi-modal AI.

Common actions

Learn about LM safety

Research LM security

Stay updated on AI ethics

Find multi-modal LM resources

deepfakeautomated workflowlow-code/no-codeworkflowscollaboration"AI Agents"face swappingopen-sourcegithub copilot

Capabilities

Key features

Curated resource list
LM safety & security
Multi-modal LM focus
Continuously updated

Target Audience

ResearchersPractitionersAI DevelopersData Scientists

Integrations

Not yet documented

Pricing & Plans

free

Free

FAQs

Is Awesome-LM-SSP truly free, or are there hidden costs for accessing certain resources?

Awesome-LM-SSP is an open-source curated list of resources, meaning the repository itself is completely free to access and use. Any costs associated with the linked external resources would depend on those individual platforms, not Awesome-LM-SSP.

How frequently is the Awesome-LM-SSP repository updated with new research and best practices?

The repository is continuously updated with manually collected materials. While there isn't a fixed schedule, new and relevant resources are added regularly to ensure users have access to the latest developments in LM safety, security, and privacy.

Does Awesome-LM-SSP include resources for specific large model architectures or only general safety guidelines?

Awesome-LM-SSP focuses on the safety, security, and privacy of large models, with a specific highlight on multi-modal LMs like vision-language and diffusion models. It includes resources that cover both general guidelines and aspects relevant to these specific architectures.

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