Comparison
Awesome-LLMs-ICLR-24 vs best_AI_papers_2022
Verdict
Pick Awesome-LLMs-ICLR-24 if awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024; pick best_AI_papers_2022 if best AI Papers from 2022 offers video explanations and code links for selected research papers.
Markdown twin · Awesome-LLMs-ICLR-24 alternatives · best_AI_papers_2022 alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | Awesome-LLMs-ICLR-24 | best_AI_papers_2022 |
|---|---|---|
| Maintenance | Dormant (856d since push) As of 2w · github_public_v1 | Dormant (1016d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · 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
- Awesome-LLMs-ICLR-24
- Compilation of LLM papers from ICLR 2024
- best_AI_papers_2022
- A curated list of breakthrough AI papers from 2022 with video explanations and code links
Stars
- Awesome-LLMs-ICLR-24
- 72
- best_AI_papers_2022
- 3.2k
Forks
- Awesome-LLMs-ICLR-24
- 5
- best_AI_papers_2022
- 197
Open issues
- Awesome-LLMs-ICLR-24
- 0
- best_AI_papers_2022
- 0
Language
- Awesome-LLMs-ICLR-24
- -
- best_AI_papers_2022
- -
Adopt for
- Awesome-LLMs-ICLR-24
- Awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024.
- best_AI_papers_2022
- Best AI Papers from 2022 offers video explanations and code links for selected research papers.
Persona
- Awesome-LLMs-ICLR-24
- -
- best_AI_papers_2022
- -
Runtime
- Awesome-LLMs-ICLR-24
- -
- best_AI_papers_2022
- -
License
- Awesome-LLMs-ICLR-24
- MIT
- best_AI_papers_2022
- MIT
Last pushed
- Awesome-LLMs-ICLR-24
- Apr 4, 2024
- best_AI_papers_2022
- Oct 18, 2023
Categories
- Awesome-LLMs-ICLR-24
- Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training
- best_AI_papers_2022
- Evaluation & Observability, Model Training
Trust and health
Days since push
- Awesome-LLMs-ICLR-24
- 856d
- best_AI_papers_2022
- 1016d
Full report
- Awesome-LLMs-ICLR-24
- Trust report
- best_AI_papers_2022
- Trust report
Choose Awesome-LLMs-ICLR-24 if…
- Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-evaluation, llm-framework.
- Also covers Developer Tools, Inference & Serving, LLM Frameworks.
- If you are focusing specifically on recent advancements in Large Language Models discussed in the context of ICLR 2024, this repository will provide cutting-edge research papers and insights.
When NOT to use Awesome-LLMs-ICLR-24
- If you are looking for more general resources that cover a wider time span or different conferences than ICLR 2024.
- For projects where immediate practical application of models without understanding the underlying research is prioritized over detailed exploration and analysis.
Choose best_AI_papers_2022 if…
- Tags unique to best_AI_papers_2022: ai, computer-vision, deep-learning, machine-learning.
- Need to catch up on key innovations in AI from 2022
- More GitHub stars (3.2k vs 72) - 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 (azminewasi/Awesome-LLMs-ICLR-24) · observed Aug 8, 2026
- GitHub forks (azminewasi/Awesome-LLMs-ICLR-24) · observed Aug 8, 2026
- Last push (azminewasi/Awesome-LLMs-ICLR-24) · observed Apr 4, 2024
- License file (MIT) · observed Aug 8, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 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: Awesome-LLMs-ICLR-24 72 · best_AI_papers_2022 3.2k (synced Aug 8, 2026).
Common questions
- What is the difference between Awesome-LLMs-ICLR-24 and best_AI_papers_2022?
- Awesome-LLMs-ICLR-24: Compilation of LLM papers from ICLR 2024. 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 Awesome-LLMs-ICLR-24 over best_AI_papers_2022?
- Choose Awesome-LLMs-ICLR-24 over best_AI_papers_2022 when Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-evaluation, llm-framework; Also covers Developer Tools, Inference & Serving, LLM Frameworks; If you are focusing specifically on recent advancements in Large Language Models discussed in the context of ICLR 2024, this repository will provide cutting-edge research papers and insights.
- When should I choose best_AI_papers_2022 over Awesome-LLMs-ICLR-24?
- Choose best_AI_papers_2022 over Awesome-LLMs-ICLR-24 when Tags unique to best_AI_papers_2022: ai, computer-vision, deep-learning, machine-learning; Need to catch up on key innovations in AI from 2022; More GitHub stars (3.2k vs 72) - visibility, not fit.
- When should I avoid Awesome-LLMs-ICLR-24?
- If you are looking for more general resources that cover a wider time span or different conferences than ICLR 2024. For projects where immediate practical application of models without understanding the underlying research is prioritized over detailed exploration and analysis.
- 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 Awesome-LLMs-ICLR-24 or best_AI_papers_2022 more popular on GitHub?
- best_AI_papers_2022 has more GitHub stars (3,187 vs 72). Stars measure visibility, not whether either tool fits your constraints.
- Are Awesome-LLMs-ICLR-24 and best_AI_papers_2022 open source?
- Yes - both are open-source projects on GitHub (Awesome-LLMs-ICLR-24: MIT, best_AI_papers_2022: MIT).
- Where can I find alternatives to Awesome-LLMs-ICLR-24 or best_AI_papers_2022?
- GraphCanon lists graph-backed alternatives at Awesome-LLMs-ICLR-24 alternatives and best_AI_papers_2022 alternatives (Awesome-LLMs-ICLR-24 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, Awesome-LLMs-ICLR-24 or best_AI_papers_2022?
- Awesome-LLMs-ICLR-24: 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 Awesome-LLMs-ICLR-24 and best_AI_papers_2022?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-LLMs-ICLR-24 trust report; best_AI_papers_2022 trust report.