--- title: "AlignLLMHumanSurvey vs awesome-RLHF" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/garyyufei-alignllmhumansurvey-vs-opendilab-awesome-rlhf" tools: ["garyyufei-alignllmhumansurvey", "opendilab-awesome-rlhf"] --- # AlignLLMHumanSurvey vs awesome-RLHF *GraphCanon updated Aug 17, 2026* ## 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. [AlignLLMHumanSurvey](https://arxiv.org/abs/2307.12966) reports 742 GitHub stars, 30 forks, and 0 open issues, last pushed Sep 11, 2023. [awesome-RLHF](https://github.com/opendilab/awesome-RLHF) has 4.4k stars, 258 forks, and 6 open issues, last pushed May 20, 2026. Figures are from public GitHub metadata via [AlignLLMHumanSurvey's repository](https://github.com/GaryYufei/AlignLLMHumanSurvey) and [awesome-RLHF's repository](https://github.com/opendilab/awesome-RLHF). | | [AlignLLMHumanSurvey](/tools/garyyufei-alignllmhumansurvey.md) | [awesome-RLHF](/tools/opendilab-awesome-rlhf.md) | | --- | --- | --- | | Tagline | A survey on aligning large language models with human expectations | A curated list of reinforcement learning with human feedback resources (continually updated) | | Stars | 742 | 4,422 | | Forks | 30 | 258 | | Open issues | 0 | 6 | | Language | - | - | | Adopt for | 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 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 | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Evaluation & Observability, Model Training | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AlignLLMHumanSurvey](/tools/garyyufei-alignllmhumansurvey.md) | [awesome-RLHF](/tools/opendilab-awesome-rlhf.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 1060d | 89d | | Open issues (now) | 0 | 6 | | Stars delta | Unknown | +9 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/garyyufei-alignllmhumansurvey/trust.md) | [trust report](/tools/opendilab-awesome-rlhf/trust.md) | ## Decision facts: AlignLLMHumanSurvey - **Adopt for:** 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 ## Decision facts: awesome-RLHF - **Adopt for:** 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. ## Choose when ### 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). ### 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 AlignLLMHumanSurvey - ，AlignLLMHumanSurvey，，。 ## 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. ## 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](/tools/garyyufei-alignllmhumansurvey/alternatives) and [awesome-RLHF alternatives](/tools/opendilab-awesome-rlhf/alternatives) ([AlignLLMHumanSurvey markdown twin](/tools/garyyufei-alignllmhumansurvey/alternatives.md), [awesome-RLHF markdown twin](/tools/opendilab-awesome-rlhf/alternatives.md)), 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](/compare/garyyufei-alignllmhumansurvey-vs-opendilab-awesome-rlhf.md) 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](/tools/garyyufei-alignllmhumansurvey/trust); [awesome-RLHF trust report](/tools/opendilab-awesome-rlhf/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=garyyufei-alignllmhumansurvey`](/api/graphcanon/graph?tool=garyyufei-alignllmhumansurvey) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_