Comparison
AlignLLMHumanSurvey vs awesome-RLHF
Verdict
Pick AlignLLMHumanSurvey if alignLLMHumanSurvey is a survey repository aggregating resources and research on aligning large language models with human expectations through various methodologies like data collection, training techniques, and model评价; pick awesome-RLHF if awesome-RLHF is a curated resource list focusing on reinforcement learning with human feedback (RLHF), which is crucial for refining large language models through interactive training methods.
Markdown twin · AlignLLMHumanSurvey alternatives · awesome-RLHF alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | AlignLLMHumanSurvey | awesome-RLHF |
|---|---|---|
| Maintenance | Dormant (1060d since push) As of 2w · github_public_v1 | Steady (89d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Organization account As of 1w · 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
- AlignLLMHumanSurvey
- A survey on aligning large language models with human expectations
- awesome-RLHF
- A curated list of reinforcement learning with human feedback resources (continually updated)
Stars
- AlignLLMHumanSurvey
- 742
- awesome-RLHF
- 4.4k
Forks
- AlignLLMHumanSurvey
- 30
- awesome-RLHF
- 258
Open issues
- AlignLLMHumanSurvey
- 0
- awesome-RLHF
- 6
Language
- AlignLLMHumanSurvey
- -
- awesome-RLHF
- -
Adopt for
- AlignLLMHumanSurvey
- AlignLLMHumanSurvey is a survey repository aggregating resources and research on aligning large language models with human expectations through various methodologies like data collection, training techniques, and model评价
- awesome-RLHF
- awesome-RLHF is a curated resource list focusing on reinforcement learning with human feedback (RLHF), which is crucial for refining large language models through interactive training methods.
Persona
- AlignLLMHumanSurvey
- -
- awesome-RLHF
- -
Runtime
- AlignLLMHumanSurvey
- -
- awesome-RLHF
- -
License
- AlignLLMHumanSurvey
- -
- awesome-RLHF
- Apache-2.0
Last pushed
- AlignLLMHumanSurvey
- Sep 11, 2023
- awesome-RLHF
- May 20, 2026
Categories
- AlignLLMHumanSurvey
- Evaluation & Observability, Model Training
- awesome-RLHF
- Evaluation & Observability, Model Training
Trust and health
Maintenance
- AlignLLMHumanSurvey
- Dormant (18%)
- awesome-RLHF
- Steady (60%)
Days since push
- AlignLLMHumanSurvey
- 1060d
- awesome-RLHF
- 89d
Open issues (now)
- AlignLLMHumanSurvey
- 0
- awesome-RLHF
- 6
Stars delta
- AlignLLMHumanSurvey
- Unknown
- awesome-RLHF
- +9 (30d)
Open issues delta
- AlignLLMHumanSurvey
- Unknown
- awesome-RLHF
- 0 (30d)
Owner type
- AlignLLMHumanSurvey
- User
- awesome-RLHF
- Organization
Full report
- AlignLLMHumanSurvey
- Trust report
- awesome-RLHF
- Trust report
Choose AlignLLMHumanSurvey if…
- Tags unique to AlignLLMHumanSurvey: awesome, chatgpt, chinese-llama, gpt-4.
- 当您需要全面了解将大型语言模型与人类期望对齐的技术和方法时，可以使用AlignLLMHumanSurvey，它涵盖了数据收集、训练方法和模型评估等多个方面。
- Leaner open-issue backlog (0).
When NOT to use AlignLLMHumanSurvey
- ，AlignLLMHumanSurvey，，。
Choose awesome-RLHF if…
- Tags unique to awesome-RLHF: deep-learning, depth-reinforcement-learning, human-feedback, reinforcement-learning.
- When you are specifically interested in the resources that pertain to enhancing reinforcement learning algorithms with human feedback for developing advanced AI systems.
- More GitHub stars (4.4k vs 742) - visibility, not fit.
When NOT to use awesome-RLHF
- If your focus is exclusively on generic deep-learning or reinforcement-learning resources without the aspect of integrating human feedback into the training process.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (GaryYufei/AlignLLMHumanSurvey) · observed Aug 6, 2026
- GitHub forks (GaryYufei/AlignLLMHumanSurvey) · observed Aug 6, 2026
- Last push (GaryYufei/AlignLLMHumanSurvey) · observed Sep 11, 2023
- License file (unknown) · observed Aug 6, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (opendilab/awesome-RLHF) · observed Aug 17, 2026
- GitHub forks (opendilab/awesome-RLHF) · observed Aug 17, 2026
- Last push (opendilab/awesome-RLHF) · observed May 20, 2026
- License file (Apache-2.0) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: AlignLLMHumanSurvey 742 · awesome-RLHF 4.4k (synced Aug 6, 2026).
Common questions
- What is the difference between AlignLLMHumanSurvey and awesome-RLHF?
- AlignLLMHumanSurvey: A survey on aligning large language models with human expectations. awesome-RLHF: A curated list of reinforcement learning with human feedback resources (continually updated). See the comparison table for live GitHub stats and shared categories.
- When should I choose AlignLLMHumanSurvey over awesome-RLHF?
- Choose AlignLLMHumanSurvey over awesome-RLHF when Tags unique to AlignLLMHumanSurvey: awesome, chatgpt, chinese-llama, gpt-4; 当您需要全面了解将大型语言模型与人类期望对齐的技术和方法时，可以使用AlignLLMHumanSurvey，它涵盖了数据收集、训练方法和模型评估等多个方面。; Leaner open-issue backlog (0).
- When should I choose awesome-RLHF over AlignLLMHumanSurvey?
- Choose awesome-RLHF over AlignLLMHumanSurvey when Tags unique to awesome-RLHF: deep-learning, depth-reinforcement-learning, human-feedback, reinforcement-learning; When you are specifically interested in the resources that pertain to enhancing reinforcement learning algorithms with human feedback for developing advanced AI systems; More GitHub stars (4.4k vs 742) - visibility, not fit.
- When should I avoid AlignLLMHumanSurvey?
- ，AlignLLMHumanSurvey，，。
- When should I avoid awesome-RLHF?
- If your focus is exclusively on generic deep-learning or reinforcement-learning resources without the aspect of integrating human feedback into the training process.
- Is AlignLLMHumanSurvey or awesome-RLHF more popular on GitHub?
- awesome-RLHF has more GitHub stars (4,422 vs 742). Stars measure visibility, not whether either tool fits your constraints.
- Are AlignLLMHumanSurvey and awesome-RLHF open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to AlignLLMHumanSurvey or awesome-RLHF?
- GraphCanon lists graph-backed alternatives at AlignLLMHumanSurvey alternatives and awesome-RLHF alternatives (AlignLLMHumanSurvey markdown twin, awesome-RLHF 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, AlignLLMHumanSurvey or awesome-RLHF?
- AlignLLMHumanSurvey: Dormant. awesome-RLHF: Steady. 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 AlignLLMHumanSurvey and awesome-RLHF?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AlignLLMHumanSurvey trust report; awesome-RLHF trust report.