Comparison
awesome-RLHF vs Awesome-LLM-in-Social-Science
Verdict
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; pick Awesome-LLM-in-Social-Science if curate research papers on LLM applications in social science, covering topics like alignment, economics, policy, psychology, and more.
Markdown twin · awesome-RLHF alternatives · Awesome-LLM-in-Social-Science alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | awesome-RLHF | Awesome-LLM-in-Social-Science |
|---|---|---|
| Maintenance | Steady (89d since push) As of 4d · github_public_v1 | Steady (49d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Organization 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-RLHF
- A curated list of reinforcement learning with human feedback resources (continually updated)
- Awesome-LLM-in-Social-Science
- Awesome papers involving LLMs in Social Science
Stars
- awesome-RLHF
- 4.4k
- Awesome-LLM-in-Social-Science
- 639
Forks
- awesome-RLHF
- 258
- Awesome-LLM-in-Social-Science
- 48
Open issues
- awesome-RLHF
- 6
- Awesome-LLM-in-Social-Science
- 0
Language
- awesome-RLHF
- -
- Awesome-LLM-in-Social-Science
- -
Adopt for
- 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.
- Awesome-LLM-in-Social-Science
- Curate research papers on LLM applications in social science, covering topics like alignment, economics, policy, psychology, and more.
Persona
- awesome-RLHF
- -
- Awesome-LLM-in-Social-Science
- -
Runtime
- awesome-RLHF
- -
- Awesome-LLM-in-Social-Science
- -
License
- awesome-RLHF
- Apache-2.0
- Awesome-LLM-in-Social-Science
- MIT
Last pushed
- awesome-RLHF
- May 20, 2026
- Awesome-LLM-in-Social-Science
- Jun 8, 2026
Categories
- awesome-RLHF
- Evaluation & Observability, Model Training
- Awesome-LLM-in-Social-Science
- Evaluation & Observability, Model Training
Trust and health
Days since push
- awesome-RLHF
- 89d
- Awesome-LLM-in-Social-Science
- 49d
Open issues (now)
- awesome-RLHF
- 6
- Awesome-LLM-in-Social-Science
- 0
Stars delta
- awesome-RLHF
- +9 (30d)
- Awesome-LLM-in-Social-Science
- Unknown
Open issues delta
- awesome-RLHF
- 0 (30d)
- Awesome-LLM-in-Social-Science
- Unknown
Full report
- awesome-RLHF
- Trust report
- Awesome-LLM-in-Social-Science
- Trust report
Choose awesome-RLHF if…
- License: awesome-RLHF is Apache-2.0, Awesome-LLM-in-Social-Science is MIT.
- 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.
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.
Choose Awesome-LLM-in-Social-Science if…
- License: Awesome-LLM-in-Social-Science is MIT, awesome-RLHF is Apache-2.0.
- Tags unique to Awesome-LLM-in-Social-Science: alignment, economics, llm-agent, llm-evaluation.
- Need to explore academic insights into LLM impacts on specific social areas
When NOT to use Awesome-LLM-in-Social-Science
- Looking for a hands-on coding or practical implementation guide of LLMs
- In need of real-time data analysis tools for immediate social science research outcomes
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (ValueByte-AI/Awesome-LLM-in-Social-Science) · observed Jul 28, 2026
- GitHub forks (ValueByte-AI/Awesome-LLM-in-Social-Science) · observed Jul 28, 2026
- Last push (ValueByte-AI/Awesome-LLM-in-Social-Science) · observed Jun 8, 2026
- License file (MIT) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-RLHF 4.4k · Awesome-LLM-in-Social-Science 639 (synced Aug 17, 2026).
Common questions
- What is the difference between awesome-RLHF and Awesome-LLM-in-Social-Science?
- awesome-RLHF: A curated list of reinforcement learning with human feedback resources (continually updated). Awesome-LLM-in-Social-Science: Awesome papers involving LLMs in Social Science. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-RLHF over Awesome-LLM-in-Social-Science?
- Choose awesome-RLHF over Awesome-LLM-in-Social-Science when License: awesome-RLHF is Apache-2.0, Awesome-LLM-in-Social-Science is MIT; 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.
- When should I choose Awesome-LLM-in-Social-Science over awesome-RLHF?
- Choose Awesome-LLM-in-Social-Science over awesome-RLHF when License: Awesome-LLM-in-Social-Science is MIT, awesome-RLHF is Apache-2.0; Tags unique to Awesome-LLM-in-Social-Science: alignment, economics, llm-agent, llm-evaluation; Need to explore academic insights into LLM impacts on specific social areas.
- 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.
- When should I avoid Awesome-LLM-in-Social-Science?
- Looking for a hands-on coding or practical implementation guide of LLMs In need of real-time data analysis tools for immediate social science research outcomes
- Is awesome-RLHF or Awesome-LLM-in-Social-Science more popular on GitHub?
- awesome-RLHF has more GitHub stars (4,422 vs 639). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-RLHF and Awesome-LLM-in-Social-Science open source?
- Yes - both are open-source projects on GitHub (awesome-RLHF: Apache-2.0, Awesome-LLM-in-Social-Science: MIT).
- Where can I find alternatives to awesome-RLHF or Awesome-LLM-in-Social-Science?
- GraphCanon lists graph-backed alternatives at awesome-RLHF alternatives and Awesome-LLM-in-Social-Science alternatives (awesome-RLHF markdown twin, Awesome-LLM-in-Social-Science 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-RLHF or Awesome-LLM-in-Social-Science?
- awesome-RLHF: Steady. Awesome-LLM-in-Social-Science: 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 awesome-RLHF and Awesome-LLM-in-Social-Science?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-RLHF trust report; Awesome-LLM-in-Social-Science trust report.