Comparison
ml-surveys vs best_AI_papers_2022
Verdict
Pick ml-surveys if ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems; pick best_AI_papers_2022 if best AI Papers from 2022 offers video explanations and code links for selected research papers.
Markdown twin · ml-surveys alternatives · best_AI_papers_2022 alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | ml-surveys | best_AI_papers_2022 |
|---|---|---|
| Maintenance | Dormant (1254d since push) As of 2d · github_public_v1 | Dormant (1016d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2d · github_public_v1 | Not a fork · Personal account As of 3w · 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
- ml-surveys
- Survey papers summarizing advances in various AI domains
- best_AI_papers_2022
- A curated list of breakthrough AI papers from 2022 with video explanations and code links
Stars
- ml-surveys
- 2.9k
- best_AI_papers_2022
- 3.2k
Forks
- ml-surveys
- 292
- best_AI_papers_2022
- 197
Open issues
- ml-surveys
- 2
- best_AI_papers_2022
- 0
Language
- ml-surveys
- -
- best_AI_papers_2022
- -
Adopt for
- ml-surveys
- ml-surveys is a collection of detailed review papers summarizing advancements in various AI domains such as deep learning, NLP, CV, graphs, reinforcement learning, and recommendation systems.
- best_AI_papers_2022
- Best AI Papers from 2022 offers video explanations and code links for selected research papers.
Persona
- ml-surveys
- -
- best_AI_papers_2022
- -
Runtime
- ml-surveys
- -
- best_AI_papers_2022
- -
License
- ml-surveys
- MIT
- best_AI_papers_2022
- MIT
Last pushed
- ml-surveys
- Mar 17, 2023
- best_AI_papers_2022
- Oct 18, 2023
Categories
- ml-surveys
- Computer Vision, Evaluation & Observability, Model Training
- best_AI_papers_2022
- Evaluation & Observability, Model Training
Trust and health
Days since push
- ml-surveys
- 1254d
- best_AI_papers_2022
- 1016d
Open issues (now)
- ml-surveys
- 2
- best_AI_papers_2022
- 0
Stars delta
- ml-surveys
- 0 (30d)
- best_AI_papers_2022
- Unknown
Open issues delta
- ml-surveys
- 0 (30d)
- best_AI_papers_2022
- Unknown
Full report
- ml-surveys
- Trust report
- best_AI_papers_2022
- Trust report
Choose ml-surveys if…
- Tags unique to ml-surveys: embeddings, nlp, recommender-system, reinforcement-learning.
- Also covers Computer Vision.
- When you need comprehensive overviews and summaries of the latest research trends in multiple areas within machine learning
When NOT to use ml-surveys
- If you are seeking detailed technical details, original experiments, or specific algorithm implementations as ml-surveys focuses more on synthesis and summary
- In cases where deep-dive analysis is required into a single niche topic, as ml-surveys provides broad overviews rather than in-depth coverage of individual niches
Choose best_AI_papers_2022 if…
- Tags unique to best_AI_papers_2022: ai, neural-network.
- Need to catch up on key innovations in AI from 2022
- More GitHub stars (3.2k vs 2.9k) - visibility, not fit.
When NOT to use best_AI_papers_2022
- Looking for real-time updates or post-2022 research findings
- Require detailed technical analysis beyond paper abstracts
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (eugeneyan/ml-surveys) · observed Aug 22, 2026
- GitHub forks (eugeneyan/ml-surveys) · observed Aug 22, 2026
- Last push (eugeneyan/ml-surveys) · observed Mar 17, 2023
- License file (MIT) · observed Aug 22, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (louisfb01/best_AI_papers_2022) · observed Jul 31, 2026
- GitHub forks (louisfb01/best_AI_papers_2022) · observed Jul 31, 2026
- Last push (louisfb01/best_AI_papers_2022) · observed Oct 18, 2023
- License file (MIT) · observed Jul 31, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ml-surveys 2.9k · best_AI_papers_2022 3.2k (synced Aug 22, 2026).
Common questions
- What is the difference between ml-surveys and best_AI_papers_2022?
- ml-surveys: Survey papers summarizing advances in various AI domains. best_AI_papers_2022: A curated list of breakthrough AI papers from 2022 with video explanations and code links. See the comparison table for live GitHub stats and shared categories.
- When should I choose ml-surveys over best_AI_papers_2022?
- Choose ml-surveys over best_AI_papers_2022 when Tags unique to ml-surveys: embeddings, nlp, recommender-system, reinforcement-learning; Also covers Computer Vision; When you need comprehensive overviews and summaries of the latest research trends in multiple areas within machine learning.
- When should I choose best_AI_papers_2022 over ml-surveys?
- Choose best_AI_papers_2022 over ml-surveys when Tags unique to best_AI_papers_2022: ai, neural-network; Need to catch up on key innovations in AI from 2022; More GitHub stars (3.2k vs 2.9k) - visibility, not fit.
- When should I avoid ml-surveys?
- If you are seeking detailed technical details, original experiments, or specific algorithm implementations as ml-surveys focuses more on synthesis and summary In cases where deep-dive analysis is required into a single niche topic, as ml-surveys provides broad overviews rather than in-depth coverage of individual niches
- When should I avoid best_AI_papers_2022?
- Looking for real-time updates or post-2022 research findings Require detailed technical analysis beyond paper abstracts
- Is ml-surveys or best_AI_papers_2022 more popular on GitHub?
- best_AI_papers_2022 has more GitHub stars (3,187 vs 2,902). Stars measure visibility, not whether either tool fits your constraints.
- Are ml-surveys and best_AI_papers_2022 open source?
- Yes - both are open-source projects on GitHub (ml-surveys: MIT, best_AI_papers_2022: MIT).
- Where can I find alternatives to ml-surveys or best_AI_papers_2022?
- GraphCanon lists graph-backed alternatives at ml-surveys alternatives and best_AI_papers_2022 alternatives (ml-surveys markdown twin, best_AI_papers_2022 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, ml-surveys or best_AI_papers_2022?
- ml-surveys: Dormant. best_AI_papers_2022: 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 ml-surveys and best_AI_papers_2022?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ml-surveys trust report; best_AI_papers_2022 trust report.