Home/Compare/Awesome-LLM-Eval vs Awesome-LLM-in-Social-Science

Comparison

Awesome-LLM-Eval vs Awesome-LLM-in-Social-Science

Verdict

Pick Awesome-LLM-Eval if awesome-LLM-Eval provides a comprehensive curated list of resources for evaluating large language models including tools, datasets, and benchmarks; 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-LLM-Eval alternatives · Awesome-LLM-in-Social-Science alternatives

GraphCanon updated Sep 20, 2026

12views this month

Awesome-LLM-Eval logo

Awesome-LLM-Eval

onejune2018/Awesome-LLM-Eval

★ 656pushed Nov 24, 2025
vs
Awesome-LLM-in-Social-Science logo

Awesome-LLM-in-Social-Science

ValueByte-AI/Awesome-LLM-in-Social-Science

★ 648pushed Sep 7, 2026

Trust & integrity

SignalAwesome-LLM-EvalAwesome-LLM-in-Social-Science
Maintenance
Slowing (300d since push)
As of Sep 20, 2026 · github_public_v1
Active (12d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Personal account
As of Sep 20, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 20, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · 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-LLM-Eval
Curated list for evaluation of large language models
Awesome-LLM-in-Social-Science
Awesome papers involving LLMs in Social Science

Stars

Awesome-LLM-Eval
656
Awesome-LLM-in-Social-Science
648

Forks

Awesome-LLM-Eval
90
Awesome-LLM-in-Social-Science
53

Open issues

Awesome-LLM-Eval
55
Awesome-LLM-in-Social-Science
0

Language

Awesome-LLM-Eval
-
Awesome-LLM-in-Social-Science
-

Adopt for

Awesome-LLM-Eval
Awesome-LLM-Eval provides a comprehensive curated list of resources for evaluating large language models including tools, datasets, and benchmarks.
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-LLM-Eval
-
Awesome-LLM-in-Social-Science
-

Runtime

Awesome-LLM-Eval
-
Awesome-LLM-in-Social-Science
-

License

Awesome-LLM-Eval
MIT
Awesome-LLM-in-Social-Science
MIT

Last pushed

Awesome-LLM-Eval
Nov 24, 2025
Awesome-LLM-in-Social-Science
Sep 7, 2026

Categories

Awesome-LLM-Eval
Evaluation & Observability
Awesome-LLM-in-Social-Science
Evaluation & Observability, Model Training

Trust and health

Maintenance

Awesome-LLM-Eval
Slowing (36%)
Awesome-LLM-in-Social-Science
Active (82%)

Days since push

Awesome-LLM-Eval
300d
Awesome-LLM-in-Social-Science
12d

Open issues (now)

Awesome-LLM-Eval
55
Awesome-LLM-in-Social-Science
0

Stars delta

Awesome-LLM-Eval
+2 (30d)
Awesome-LLM-in-Social-Science
+9 (30d)

Open issues delta

Awesome-LLM-Eval
+11 (30d)
Awesome-LLM-in-Social-Science
0 (30d)

Owner type

Awesome-LLM-Eval
User
Awesome-LLM-in-Social-Science
Organization

Full report

Awesome-LLM-Eval
Trust report
Awesome-LLM-in-Social-Science
Trust report

Choose Awesome-LLM-Eval if…

  • Pricing: The core resources listed in Awesome-LLM-Eval are freely accessible under MIT license, however, certain datasets or tools might have individual licensing terms..
  • Requirements: The resources listed may vary in their own requirements, including software dependencies and hardware specifications..
  • Tags unique to Awesome-LLM-Eval: awesome-list, benchmark, datasets, evaluation.
  • When you specifically need access to an extensive compilation of evaluation-related resources tailored towards large language model assessment.

When NOT to use Awesome-LLM-Eval

  • You require real-time testing capabilities or interactive features; Awesome-LLM-Eval is a static resource list and not an interactive platform.
  • If integration with specific third-party platforms or direct API access is necessary, since the repository predominantly serves as a reference point rather than an operational tool.

Choose Awesome-LLM-in-Social-Science if…

  • Tags unique to Awesome-LLM-in-Social-Science: alignment, economics, llm-agent, policy.
  • Also covers Model Training.
  • 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 on cards: Awesome-LLM-Eval 656 · Awesome-LLM-in-Social-Science 648 (synced Sep 20, 2026).

Common questions

What is the difference between Awesome-LLM-Eval and Awesome-LLM-in-Social-Science?
Awesome-LLM-Eval: Curated list for evaluation of large language models. 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-LLM-Eval over Awesome-LLM-in-Social-Science?
Choose Awesome-LLM-Eval over Awesome-LLM-in-Social-Science when Pricing: The core resources listed in Awesome-LLM-Eval are freely accessible under MIT license, however, certain datasets or tools might have individual licensing terms.; Requirements: The resources listed may vary in their own requirements, including software dependencies and hardware specifications.; Tags unique to Awesome-LLM-Eval: awesome-list, benchmark, datasets, evaluation; When you specifically need access to an extensive compilation of evaluation-related resources tailored towards large language model assessment.
When should I choose Awesome-LLM-in-Social-Science over Awesome-LLM-Eval?
Choose Awesome-LLM-in-Social-Science over Awesome-LLM-Eval when Tags unique to Awesome-LLM-in-Social-Science: alignment, economics, llm-agent, policy; Also covers Model Training; Need to explore academic insights into LLM impacts on specific social areas.
When should I avoid Awesome-LLM-Eval?
You require real-time testing capabilities or interactive features; Awesome-LLM-Eval is a static resource list and not an interactive platform. If integration with specific third-party platforms or direct API access is necessary, since the repository predominantly serves as a reference point rather than an operational tool.
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-LLM-Eval or Awesome-LLM-in-Social-Science more popular on GitHub?
Awesome-LLM-Eval has more GitHub stars (656 vs 648). Stars measure visibility, not whether either tool fits your constraints.
Are Awesome-LLM-Eval and Awesome-LLM-in-Social-Science open source?
Yes - both are open-source projects on GitHub (Awesome-LLM-Eval: MIT, Awesome-LLM-in-Social-Science: MIT).
Where can I find alternatives to Awesome-LLM-Eval or Awesome-LLM-in-Social-Science?
GraphCanon lists graph-backed alternatives at Awesome-LLM-Eval alternatives and Awesome-LLM-in-Social-Science alternatives (Awesome-LLM-Eval 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-LLM-Eval or Awesome-LLM-in-Social-Science?
Awesome-LLM-Eval: Slowing. Awesome-LLM-in-Social-Science: Active. 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-LLM-Eval and Awesome-LLM-in-Social-Science?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Awesome-LLM-Eval trust report; Awesome-LLM-in-Social-Science trust report.

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