--- title: "Awesome-LLMs-ICLR-24 vs Awesome-LLM-hallucination" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/azminewasi-awesome-llms-iclr-24-vs-luckyyysta-awesome-llm-hallucination" tools: ["azminewasi-awesome-llms-iclr-24", "luckyyysta-awesome-llm-hallucination"] --- # Awesome-LLMs-ICLR-24 vs Awesome-LLM-hallucination *GraphCanon updated Aug 8, 2026* ## Verdict 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; pick Awesome-LLM-hallucination if awesome-LLM-hallucination stands out as a resource dedicated to the in-depth analysis of hallucination phenomena within Large Language Models (LLMs). Its curated list and categorization make it distinct from other. [Awesome-LLMs-ICLR-24](https://github.com/azminewasi/Awesome-LLMs-ICLR-24) reports 72 GitHub stars, 5 forks, and 0 open issues, last pushed Apr 4, 2024. [Awesome-LLM-hallucination](https://github.com/LuckyyySTA/Awesome-LLM-hallucination) has 339 stars, 25 forks, and 4 open issues, last pushed Mar 11, 2024. Figures are from public GitHub metadata via [Awesome-LLMs-ICLR-24's repository](https://github.com/azminewasi/Awesome-LLMs-ICLR-24) and [Awesome-LLM-hallucination's repository](https://github.com/LuckyyySTA/Awesome-LLM-hallucination). | | [Awesome-LLMs-ICLR-24](/tools/azminewasi-awesome-llms-iclr-24.md) | [Awesome-LLM-hallucination](/tools/luckyyysta-awesome-llm-hallucination.md) | | --- | --- | --- | | Tagline | Compilation of LLM papers from ICLR 2024 | A Survey on Hallucination in Large Language Models | | Stars | 72 | 339 | | Forks | 5 | 25 | | Open issues | 0 | 4 | | Language | - | - | | 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. | Awesome-LLM-hallucination stands out as a resource dedicated to the in-depth analysis of hallucination phenomena within Large Language Models (LLMs). Its curated list and categorization make it distinct from other tools, | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Awesome-LLMs-ICLR-24](/tools/azminewasi-awesome-llms-iclr-24.md) | [Awesome-LLM-hallucination](/tools/luckyyysta-awesome-llm-hallucination.md) | | --- | --- | --- | | Days since push | 856d | 877d | | Open issues (now) | 0 | 4 | | Full report | [trust report](/tools/azminewasi-awesome-llms-iclr-24/trust.md) | [trust report](/tools/luckyyysta-awesome-llm-hallucination/trust.md) | ## 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. ## Decision facts: Awesome-LLM-hallucination - **Requirements:** The exact language used by the repository is unknown, as no specific programming languages are listed. - **Adopt for:** Awesome-LLM-hallucination stands out as a resource dedicated to the in-depth analysis of hallucination phenomena within Large Language Models (LLMs). Its curated list and categorization make it distinct from other tools, - **License detail:** MIT ## Choose when ### Choose Awesome-LLMs-ICLR-24 if… - Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-evaluation, llm-framework. - Also covers Developer Tools, Inference & Serving, LLM Frameworks, Model Training. - 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. ### Choose Awesome-LLM-hallucination if… - Requirements: The exact language used by the repository is unknown, as no specific programming languages are listed.. - Tags unique to Awesome-LLM-hallucination: hallucination, large language models, llm, survey. - - When you need detailed categorizations by causes, detection methods, and mitigation strategies for LLM hallucinations. ## 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. ## When NOT to use Awesome-LLM-hallucination - - Avoid using this resource for practical, hands-on tools or code that helps mitigate hallucinations directly (it's primarily informative). - - Do not use if you are looking for real-time diagnostic software for identifying and correcting LLM hallucination mistakes in live applications. - - This tool is not suitable as a standalone guide for implementing mitigation techniques within your own large language models; it lacks detailed technical instructions. ## Common questions ### What is the difference between Awesome-LLMs-ICLR-24 and Awesome-LLM-hallucination? Awesome-LLMs-ICLR-24: Compilation of LLM papers from ICLR 2024. Awesome-LLM-hallucination: A Survey on Hallucination in Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose Awesome-LLMs-ICLR-24 over Awesome-LLM-hallucination? Choose Awesome-LLMs-ICLR-24 over Awesome-LLM-hallucination when Tags unique to Awesome-LLMs-ICLR-24: large-language-model, llm-agent, llm-evaluation, llm-framework; Also covers Developer Tools, Inference & Serving, LLM Frameworks, Model Training; 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 choose Awesome-LLM-hallucination over Awesome-LLMs-ICLR-24? Choose Awesome-LLM-hallucination over Awesome-LLMs-ICLR-24 when Requirements: The exact language used by the repository is unknown, as no specific programming languages are listed.; Tags unique to Awesome-LLM-hallucination: hallucination, large language models, llm, survey; - When you need detailed categorizations by causes, detection methods, and mitigation strategies for LLM hallucinations. ### 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. ### When should I avoid Awesome-LLM-hallucination? - Avoid using this resource for practical, hands-on tools or code that helps mitigate hallucinations directly (it's primarily informative). - Do not use if you are looking for real-time diagnostic software for identifying and correcting LLM hallucination mistakes in live applications. - This tool is not suitable as a standalone guide for implementing mitigation techniques within your own large language models; it lacks detailed technical instructions. ### Is Awesome-LLMs-ICLR-24 or Awesome-LLM-hallucination more popular on GitHub? Awesome-LLM-hallucination has more GitHub stars (339 vs 72). Stars measure visibility, not whether either tool fits your constraints. ### Are Awesome-LLMs-ICLR-24 and Awesome-LLM-hallucination open source? Yes - both are open-source projects on GitHub (Awesome-LLMs-ICLR-24: MIT, Awesome-LLM-hallucination: MIT). ### Where can I find alternatives to Awesome-LLMs-ICLR-24 or Awesome-LLM-hallucination? GraphCanon lists graph-backed alternatives at [Awesome-LLMs-ICLR-24 alternatives](/tools/azminewasi-awesome-llms-iclr-24/alternatives) and [Awesome-LLM-hallucination alternatives](/tools/luckyyysta-awesome-llm-hallucination/alternatives) ([Awesome-LLMs-ICLR-24 markdown twin](/tools/azminewasi-awesome-llms-iclr-24/alternatives.md), [Awesome-LLM-hallucination markdown twin](/tools/luckyyysta-awesome-llm-hallucination/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/azminewasi-awesome-llms-iclr-24-vs-luckyyysta-awesome-llm-hallucination.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Awesome-LLMs-ICLR-24 or Awesome-LLM-hallucination? Awesome-LLMs-ICLR-24: Dormant. Awesome-LLM-hallucination: 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-LLMs-ICLR-24 and Awesome-LLM-hallucination? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Awesome-LLMs-ICLR-24 trust report](/tools/azminewasi-awesome-llms-iclr-24/trust); [Awesome-LLM-hallucination trust report](/tools/luckyyysta-awesome-llm-hallucination/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=azminewasi-awesome-llms-iclr-24`](/api/graphcanon/graph?tool=azminewasi-awesome-llms-iclr-24) - 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/_