Comparison
awesome-ai-safety vs awesome-automl-papers
Verdict
Pick awesome-ai-safety if awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP; pick awesome-automl-papers if awesome-automl-papers is an organized collection of AutoML academic resources including papers on automated feature engineering, hyperparameter optimization, and neural architecture search.
Markdown twin · awesome-ai-safety alternatives · awesome-automl-papers alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | awesome-ai-safety | awesome-automl-papers |
|---|---|---|
| Maintenance | Dormant (473d since push) As of 3w · github_public_v1 | Dormant (784d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- awesome-ai-safety
- A curated list of papers and technical articles on AI Quality & Safety
- awesome-automl-papers
- A curated list of automated machine learning papers and resources.
Stars
- awesome-ai-safety
- 220
- awesome-automl-papers
- 4.2k
Forks
- awesome-ai-safety
- 39
- awesome-automl-papers
- 678
Open issues
- awesome-ai-safety
- 17
- awesome-automl-papers
- 2
Language
- awesome-ai-safety
- -
- awesome-automl-papers
- -
Adopt for
- awesome-ai-safety
- awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP.
- awesome-automl-papers
- awesome-automl-papers is an organized collection of AutoML academic resources including papers on automated feature engineering, hyperparameter optimization, and neural architecture search.
Persona
- awesome-ai-safety
- -
- awesome-automl-papers
- -
Runtime
- awesome-ai-safety
- -
- awesome-automl-papers
- -
License
- awesome-ai-safety
- Apache-2.0
- awesome-automl-papers
- Apache-2.0
Last pushed
- awesome-ai-safety
- Apr 14, 2025
- awesome-automl-papers
- Jun 11, 2024
Categories
- awesome-ai-safety
- Evaluation & Observability
- awesome-automl-papers
- Evaluation & Observability, Model Training
Trust and health
Days since push
- awesome-ai-safety
- 473d
- awesome-automl-papers
- 784d
Open issues (now)
- awesome-ai-safety
- 17
- awesome-automl-papers
- 2
Owner type
- awesome-ai-safety
- Organization
- awesome-automl-papers
- User
Full report
- awesome-ai-safety
- Trust report
- awesome-automl-papers
- Trust report
Choose awesome-ai-safety if…
- Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs..
- Tags unique to awesome-ai-safety: ai, ai safety, ai-alignment, ai-quality.
- When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models.
When NOT to use awesome-ai-safety
- Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles.
- Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities.
- This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models.
Choose awesome-automl-papers if…
- Tags unique to awesome-automl-papers: automl, feature-engineering, hyperparameter-optimization, neural-architecture-search.
- Also covers Model Training.
- When you need a curated list of academic materials to research or learn about AutoML technologies
When NOT to use awesome-automl-papers
- If looking for direct integration with commercial AutoML systems, as the tool provides only a list of academic papers and resources
- When seeking practical AutoML solutions to directly apply in production settings without extensive customization or interpretation from papers
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Giskard-AI/awesome-ai-safety) · observed Aug 1, 2026
- GitHub forks (Giskard-AI/awesome-ai-safety) · observed Aug 1, 2026
- Last push (Giskard-AI/awesome-ai-safety) · observed Apr 14, 2025
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (hibayesian/awesome-automl-papers) · observed Aug 4, 2026
- GitHub forks (hibayesian/awesome-automl-papers) · observed Aug 4, 2026
- Last push (hibayesian/awesome-automl-papers) · observed Jun 11, 2024
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-ai-safety 220 · awesome-automl-papers 4.2k (synced Aug 1, 2026).
Common questions
- What is the difference between awesome-ai-safety and awesome-automl-papers?
- awesome-ai-safety: A curated list of papers and technical articles on AI Quality & Safety. awesome-automl-papers: A curated list of automated machine learning papers and resources.. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-ai-safety over awesome-automl-papers?
- Choose awesome-ai-safety over awesome-automl-papers when Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs.; Tags unique to awesome-ai-safety: ai, ai safety, ai-alignment, ai-quality; When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models.
- When should I choose awesome-automl-papers over awesome-ai-safety?
- Choose awesome-automl-papers over awesome-ai-safety when Tags unique to awesome-automl-papers: automl, feature-engineering, hyperparameter-optimization, neural-architecture-search; Also covers Model Training; When you need a curated list of academic materials to research or learn about AutoML technologies.
- When should I avoid awesome-ai-safety?
- Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles. Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities. This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models.
- When should I avoid awesome-automl-papers?
- If looking for direct integration with commercial AutoML systems, as the tool provides only a list of academic papers and resources When seeking practical AutoML solutions to directly apply in production settings without extensive customization or interpretation from papers
- Is awesome-ai-safety or awesome-automl-papers more popular on GitHub?
- awesome-automl-papers has more GitHub stars (4,155 vs 220). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-ai-safety and awesome-automl-papers open source?
- Yes - both are open-source projects on GitHub (awesome-ai-safety: Apache-2.0, awesome-automl-papers: Apache-2.0).
- Where can I find alternatives to awesome-ai-safety or awesome-automl-papers?
- GraphCanon lists graph-backed alternatives at awesome-ai-safety alternatives and awesome-automl-papers alternatives (awesome-ai-safety markdown twin, awesome-automl-papers markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, awesome-ai-safety or awesome-automl-papers?
- awesome-ai-safety: Dormant. awesome-automl-papers: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for awesome-ai-safety and awesome-automl-papers?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-ai-safety trust report; awesome-automl-papers trust report.