--- title: "AutoRAG vs LLM-Agent-Paper-List" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/marker-inc-korea-autorag-vs-woooodyy-llm-agent-paper-list" tools: ["marker-inc-korea-autorag", "woooodyy-llm-agent-paper-list"] --- # AutoRAG vs LLM-Agent-Paper-List *GraphCanon updated Sep 20, 2026* ## Verdict Pick AutoRAG if autoRAG: Automate RAG task evaluation and optimization using AutoML techniques; 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. [AutoRAG](https://marker-inc-korea.github.io/AutoRAG/) reports 5.1k GitHub stars, 434 forks, and 125 open issues, last pushed Sep 7, 2026. [LLM-Agent-Paper-List](https://arxiv.org/abs/2309.07864) has 8.2k stars, 499 forks, and 32 open issues, last pushed Sep 12, 2025. Figures are from public GitHub metadata via [AutoRAG's repository](https://github.com/Marker-Inc-Korea/AutoRAG) and [LLM-Agent-Paper-List's repository](https://github.com/WooooDyy/LLM-Agent-Paper-List). | | [AutoRAG](/tools/marker-inc-korea-autorag.md) | [LLM-Agent-Paper-List](/tools/woooodyy-llm-agent-paper-list.md) | | --- | --- | --- | | Tagline | Open-source framework for RAG evaluation and optimization via AutoML | Must-read papers for LLM-based agents. | | Stars | 5,060 | 8,222 | | Forks | 434 | 499 | | Open issues | 125 | 32 | | Language | TypeScript | - | | Adopt for | AutoRAG: Automate RAG task evaluation and optimization using AutoML techniques. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 licensed, allowing free use in commercial projects while retaining copyright notices. | - | | Categories | Evaluation & Observability, Model Training | AI Agents, Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AutoRAG](/tools/marker-inc-korea-autorag.md) | [LLM-Agent-Paper-List](/tools/woooodyy-llm-agent-paper-list.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 371d | | Open issues (now) | 125 | 32 | | Stars delta | +92 (30d) | +50 (30d) | | Open issues delta | +2 (30d) | +1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/marker-inc-korea-autorag/trust.md) | [trust report](/tools/woooodyy-llm-agent-paper-list/trust.md) | ## Decision facts: AutoRAG - **Adopt for:** AutoRAG: Automate RAG task evaluation and optimization using AutoML techniques. - **License detail:** Apache-2.0 licensed, allowing free use in commercial projects while retaining copyright notices. ## Decision facts: LLM-Agent-Paper-List - **Adopt for:** 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. ## Choose when ### Choose AutoRAG if… - Tags unique to AutoRAG: analysis, automl, benchmarking, document-parser. - Automated benchmarking is needed for retrieval-augmented generation tasks - More recently updated (last pushed Sep 7, 2026). ### Choose LLM-Agent-Paper-List if… - Tags unique to LLM-Agent-Paper-List: agent, large-language-models, 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 AutoRAG - Requirements exceed capabilities of open-source tools - No need for RAG-specific optimization and evaluation features ## 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 ## Common questions ### What is the difference between AutoRAG and LLM-Agent-Paper-List? AutoRAG: Open-source framework for RAG evaluation and optimization via AutoML. 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 AutoRAG over LLM-Agent-Paper-List? Choose AutoRAG over LLM-Agent-Paper-List when Tags unique to AutoRAG: analysis, automl, benchmarking, document-parser; Automated benchmarking is needed for retrieval-augmented generation tasks; More recently updated (last pushed Sep 7, 2026). ### When should I choose LLM-Agent-Paper-List over AutoRAG? Choose LLM-Agent-Paper-List over AutoRAG when Tags unique to LLM-Agent-Paper-List: agent, large-language-models, 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 AutoRAG? Requirements exceed capabilities of open-source tools No need for RAG-specific optimization and evaluation features ### 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 AutoRAG or LLM-Agent-Paper-List more popular on GitHub? LLM-Agent-Paper-List has more GitHub stars (8,222 vs 5,060). Stars measure visibility, not whether either tool fits your constraints. ### Are AutoRAG and LLM-Agent-Paper-List open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to AutoRAG or LLM-Agent-Paper-List? GraphCanon lists graph-backed alternatives at [AutoRAG alternatives](/tools/marker-inc-korea-autorag/alternatives) and [LLM-Agent-Paper-List alternatives](/tools/woooodyy-llm-agent-paper-list/alternatives) ([AutoRAG markdown twin](/tools/marker-inc-korea-autorag/alternatives.md), [LLM-Agent-Paper-List markdown twin](/tools/woooodyy-llm-agent-paper-list/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/marker-inc-korea-autorag-vs-woooodyy-llm-agent-paper-list.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AutoRAG or LLM-Agent-Paper-List? AutoRAG: Very active. 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 AutoRAG and LLM-Agent-Paper-List? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoRAG trust report](/tools/marker-inc-korea-autorag/trust); [LLM-Agent-Paper-List trust report](/tools/woooodyy-llm-agent-paper-list/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=marker-inc-korea-autorag`](/api/graphcanon/graph?tool=marker-inc-korea-autorag) - 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/_