--- title: "FLsystem-paper vs Awesome-LLMs-ICLR-24" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/amberljc-flsystem-paper-vs-azminewasi-awesome-llms-iclr-24" tools: ["amberljc-flsystem-paper", "azminewasi-awesome-llms-iclr-24"] --- # FLsystem-paper vs Awesome-LLMs-ICLR-24 *GraphCanon updated Aug 8, 2026* ## Verdict Pick FLsystem-paper if fLsystem-paper is a curated list of federated learning systems literature geared towards providing research and development insights exclusively from big tech companies and open-source projects; pick Awesome-LLMs-ICLR-24 if awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024. [FLsystem-paper](https://github.com/AmberLJC/FLsystem-paper) reports 75 GitHub stars, 7 forks, and 1 open issues, last pushed Feb 7, 2024. [Awesome-LLMs-ICLR-24](https://github.com/azminewasi/Awesome-LLMs-ICLR-24) has 72 stars, 5 forks, and 0 open issues, last pushed Apr 4, 2024. Figures are from public GitHub metadata via [FLsystem-paper's repository](https://github.com/AmberLJC/FLsystem-paper) and [Awesome-LLMs-ICLR-24's repository](https://github.com/azminewasi/Awesome-LLMs-ICLR-24). | | [FLsystem-paper](/tools/amberljc-flsystem-paper.md) | [Awesome-LLMs-ICLR-24](/tools/azminewasi-awesome-llms-iclr-24.md) | | --- | --- | --- | | Tagline | A curated list of FL system-related academic papers and frameworks | Compilation of LLM papers from ICLR 2024 | | Stars | 75 | 72 | | Forks | 7 | 5 | | Open issues | 1 | 0 | | Language | - | - | | Adopt for | FLsystem-paper is a curated list of federated learning systems literature geared towards providing research and development insights exclusively from big tech companies and open-source projects. | Awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024. | | Persona | - | - | | Runtime | - | - | | License | (unknown) | MIT | | Categories | Developer Tools, Model Training | Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FLsystem-paper](/tools/amberljc-flsystem-paper.md) | [Awesome-LLMs-ICLR-24](/tools/azminewasi-awesome-llms-iclr-24.md) | | --- | --- | --- | | Days since push | 909d | 856d | | Open issues (now) | 1 | 0 | | Full report | [trust report](/tools/amberljc-flsystem-paper/trust.md) | [trust report](/tools/azminewasi-awesome-llms-iclr-24/trust.md) | ## Decision facts: FLsystem-paper - **Hosting:** self hosted - (no information available) - **Pricing:** freemium - The repository itself is free and open source, but usage might involve proprietary frameworks or projects from big tech companies that could have their own licensing models. - **Adopt for:** FLsystem-paper is a curated list of federated learning systems literature geared towards providing research and development insights exclusively from big tech companies and open-source projects. - **License detail:** (unknown) ## Decision facts: Awesome-LLMs-ICLR-24 - **Adopt for:** Awesome-LLMs-ICLR-24 is an essential resource hub for researchers and developers working with large language models, focusing on LLM research papers accepted at ICLR in 2024. ## Choose when ### Choose FLsystem-paper if… - (no information available) - Pricing: The repository itself is free and open source, but usage might involve proprietary frameworks or projects from big tech companies that could have their own licensing models.. - Tags unique to FLsystem-paper: federated-learning, machine-learning, papers. - When you need to focus on federated learning systems contributions from major technology firms like Apple, Google, Meta, Microsoft, IBM, Nvidia, WeBank, and Alibaba. ### Choose Awesome-LLMs-ICLR-24 if… - Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-evaluation, llm-framework. - Also covers Evaluation & Observability, Inference & Serving, LLM Frameworks. - If you are focusing specifically on recent advancements in Large Language Models discussed in the context of ICLR 2024, this repository will provide cutting-edge research papers and insights. ## When NOT to use FLsystem-paper - If your research scope is broader than federated learning systems; this repository focuses specifically on the system aspects within FL. - For a comprehensive collection that includes other ML domains, as FLsystem-paper restricts its curation to federated learning systems and closely related works. ## When NOT to use Awesome-LLMs-ICLR-24 - If you are looking for more general resources that cover a wider time span or different conferences than ICLR 2024. - For projects where immediate practical application of models without understanding the underlying research is prioritized over detailed exploration and analysis. ## Common questions ### What is the difference between FLsystem-paper and Awesome-LLMs-ICLR-24? FLsystem-paper: A curated list of FL system-related academic papers and frameworks. Awesome-LLMs-ICLR-24: Compilation of LLM papers from ICLR 2024. See the comparison table for live GitHub stats and shared categories. ### When should I choose FLsystem-paper over Awesome-LLMs-ICLR-24? Choose FLsystem-paper over Awesome-LLMs-ICLR-24 when (no information available); Pricing: The repository itself is free and open source, but usage might involve proprietary frameworks or projects from big tech companies that could have their own licensing models.; Tags unique to FLsystem-paper: federated-learning, machine-learning, papers; When you need to focus on federated learning systems contributions from major technology firms like Apple, Google, Meta, Microsoft, IBM, Nvidia, WeBank, and Alibaba. ### When should I choose Awesome-LLMs-ICLR-24 over FLsystem-paper? Choose Awesome-LLMs-ICLR-24 over FLsystem-paper when Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-evaluation, llm-framework; Also covers Evaluation & Observability, Inference & Serving, LLM Frameworks; If you are focusing specifically on recent advancements in Large Language Models discussed in the context of ICLR 2024, this repository will provide cutting-edge research papers and insights. ### When should I avoid FLsystem-paper? If your research scope is broader than federated learning systems; this repository focuses specifically on the system aspects within FL. For a comprehensive collection that includes other ML domains, as FLsystem-paper restricts its curation to federated learning systems and closely related works. ### When should I avoid Awesome-LLMs-ICLR-24? If you are looking for more general resources that cover a wider time span or different conferences than ICLR 2024. For projects where immediate practical application of models without understanding the underlying research is prioritized over detailed exploration and analysis. ### Is FLsystem-paper or Awesome-LLMs-ICLR-24 more popular on GitHub? FLsystem-paper has more GitHub stars (75 vs 72). Stars measure visibility, not whether either tool fits your constraints. ### Are FLsystem-paper and Awesome-LLMs-ICLR-24 open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to FLsystem-paper or Awesome-LLMs-ICLR-24? GraphCanon lists graph-backed alternatives at [FLsystem-paper alternatives](/tools/amberljc-flsystem-paper/alternatives) and [Awesome-LLMs-ICLR-24 alternatives](/tools/azminewasi-awesome-llms-iclr-24/alternatives) ([FLsystem-paper markdown twin](/tools/amberljc-flsystem-paper/alternatives.md), [Awesome-LLMs-ICLR-24 markdown twin](/tools/azminewasi-awesome-llms-iclr-24/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/amberljc-flsystem-paper-vs-azminewasi-awesome-llms-iclr-24.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FLsystem-paper or Awesome-LLMs-ICLR-24? FLsystem-paper: Dormant. Awesome-LLMs-ICLR-24: 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 FLsystem-paper and Awesome-LLMs-ICLR-24? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FLsystem-paper trust report](/tools/amberljc-flsystem-paper/trust); [Awesome-LLMs-ICLR-24 trust report](/tools/azminewasi-awesome-llms-iclr-24/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=amberljc-flsystem-paper`](/api/graphcanon/graph?tool=amberljc-flsystem-paper) - 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/_