Comparison
awesome-RLHF vs LLM-Agent-Paper-List
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 LLM-Agent-Paper-List if lLM-Agent-Paper-List is a curated repository of essential papers on large language model-based agents, focusing on AgentGym, a framework for developing and training LLM agents through reinforcement learning.
Markdown twin · awesome-RLHF alternatives · LLM-Agent-Paper-List alternatives
GraphCanon updated Sep 20, 2026
12views this month
Trust & integrity
| Signal | awesome-RLHF | LLM-Agent-Paper-List |
|---|---|---|
| Maintenance | Steady (89d since push) As of Aug 17, 2026 · github_public_v1 | Dormant (371d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 17, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 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 Sep 18, 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-RLHF
- A curated list of reinforcement learning with human feedback resources (continually updated)
- LLM-Agent-Paper-List
- Must-read papers for LLM-based agents.
Stars
- awesome-RLHF
- 4.4k
- LLM-Agent-Paper-List
- 8.2k
Forks
- awesome-RLHF
- 258
- LLM-Agent-Paper-List
- 499
Open issues
- awesome-RLHF
- 6
- LLM-Agent-Paper-List
- 32
Language
- awesome-RLHF
- -
- LLM-Agent-Paper-List
- -
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.
- LLM-Agent-Paper-List
- LLM-Agent-Paper-List is a curated repository of essential papers on large language model-based agents, focusing on AgentGym, a framework for developing and training LLM agents through reinforcement learning.
Persona
- awesome-RLHF
- -
- LLM-Agent-Paper-List
- -
Runtime
- awesome-RLHF
- -
- LLM-Agent-Paper-List
- -
License
- awesome-RLHF
- Apache-2.0
- LLM-Agent-Paper-List
- -
Last pushed
- awesome-RLHF
- May 20, 2026
- LLM-Agent-Paper-List
- Sep 12, 2025
Categories
- awesome-RLHF
- Evaluation & Observability, Model Training
- LLM-Agent-Paper-List
- AI Agents, Evaluation & Observability, Model Training
Trust and health
Maintenance
- awesome-RLHF
- Steady (60%)
- LLM-Agent-Paper-List
- Dormant (18%)
Days since push
- awesome-RLHF
- 89d
- LLM-Agent-Paper-List
- 371d
Open issues (now)
- awesome-RLHF
- 6
- LLM-Agent-Paper-List
- 32
Stars delta
- awesome-RLHF
- +9 (30d)
- LLM-Agent-Paper-List
- +50 (30d)
Open issues delta
- awesome-RLHF
- 0 (30d)
- LLM-Agent-Paper-List
- +1 (30d)
Owner type
- awesome-RLHF
- Organization
- LLM-Agent-Paper-List
- User
Full report
- awesome-RLHF
- Trust report
- LLM-Agent-Paper-List
- Trust report
Choose awesome-RLHF if…
- Tags unique to awesome-RLHF: deep-learning, depth-reinforcement-learning, human-feedback, rlhf.
- When you are specifically interested in the resources that pertain to enhancing reinforcement learning algorithms with human feedback for developing advanced AI systems.
- More recently updated (last pushed May 20, 2026).
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 LLM-Agent-Paper-List if…
- Tags unique to LLM-Agent-Paper-List: agent, evaluation, llm, nlp.
- Also covers AI Agents.
- When you need a comprehensive list of must-read papers on LLM-based agents, including detailed insights into AgentGym, a framework for developing and training LLM agents through reinforcement learning
When NOT to use LLM-Agent-Paper-List
- If you are looking for a tool that focuses on a broader range of AI agent development beyond LLM-based agents, as LLM-Agent-Paper-List is specifically curated for LLM-based agents
- When you need real-time updates or a dynamic list of papers, as the repository is a static list and does not automatically update with new publications
- If you require a tool that includes practical code implementations for all listed papers, as the repository primarily serves as a list and does not provide comprehensive code for every paper
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 Sep 20, 2026
- GitHub forks (opendilab/awesome-RLHF) · observed Sep 20, 2026
- Last push (opendilab/awesome-RLHF) · observed May 20, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (WooooDyy/LLM-Agent-Paper-List) · observed Sep 20, 2026
- GitHub forks (WooooDyy/LLM-Agent-Paper-List) · observed Sep 20, 2026
- Last push (WooooDyy/LLM-Agent-Paper-List) · observed Sep 12, 2025
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: awesome-RLHF 4.4k · LLM-Agent-Paper-List 8.2k (synced Sep 20, 2026).
Common questions
- What is the difference between awesome-RLHF and LLM-Agent-Paper-List?
- awesome-RLHF: A curated list of reinforcement learning with human feedback resources (continually updated). LLM-Agent-Paper-List: Must-read papers for LLM-based agents.. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-RLHF over LLM-Agent-Paper-List?
- Choose awesome-RLHF over LLM-Agent-Paper-List when Tags unique to awesome-RLHF: deep-learning, depth-reinforcement-learning, human-feedback, rlhf; When you are specifically interested in the resources that pertain to enhancing reinforcement learning algorithms with human feedback for developing advanced AI systems; More recently updated (last pushed May 20, 2026).
- When should I choose LLM-Agent-Paper-List over awesome-RLHF?
- Choose LLM-Agent-Paper-List over awesome-RLHF when Tags unique to LLM-Agent-Paper-List: agent, evaluation, llm, nlp; Also covers AI Agents; When you need a comprehensive list of must-read papers on LLM-based agents, including detailed insights into AgentGym, a framework for developing and training LLM agents through reinforcement learning.
- 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 LLM-Agent-Paper-List?
- If you are looking for a tool that focuses on a broader range of AI agent development beyond LLM-based agents, as LLM-Agent-Paper-List is specifically curated for LLM-based agents When you need real-time updates or a dynamic list of papers, as the repository is a static list and does not automatically update with new publications If you require a tool that includes practical code implementations for all listed papers, as the repository primarily serves as a list and does not provide comprehensive code for every paper
- Is awesome-RLHF or LLM-Agent-Paper-List more popular on GitHub?
- LLM-Agent-Paper-List has more GitHub stars (8,222 vs 4,422). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-RLHF and LLM-Agent-Paper-List open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to awesome-RLHF or LLM-Agent-Paper-List?
- GraphCanon lists graph-backed alternatives at awesome-RLHF alternatives and LLM-Agent-Paper-List alternatives (awesome-RLHF markdown twin, LLM-Agent-Paper-List 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 LLM-Agent-Paper-List?
- awesome-RLHF: Steady. LLM-Agent-Paper-List: 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-RLHF and LLM-Agent-Paper-List?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-RLHF trust report; LLM-Agent-Paper-List trust report.