elder-plinius/CL4R1T4S
CL4R1T4S is a project that provides transparency by collecting and sharing the hidden system prompts and guidelines used by major AI models and agents to promote trust and understanding of AI behavior.
Awesome AI Agents › LLM Research Repositories
VoltAgent/awesome-ai-agent-papers
Awesome AI Agent Papers is a curated bibliography maintained by the VoltAgent project that tracks research papers about the AI agent ecosystem published on arXiv from January 2026 onward. The maintainers review the weekly arXiv output, filter for papers directly relevant to agents, and sort them into five sections: Multi-Agent, covering coordination, communication topologies, negotiation, social simulation and meta-agent architectures; Memory and RAG; Eval and Observability; Agent Tooling; and AI Agent Security. At the time of the snapshot the list holds more than 360 papers, with roughly 53 entries under multi-agent, 57 under memory and RAG, 80 under evaluation and observability, 95 under agent tooling and 82 under security, and it is described as updated weekly. Each section is rendered as a collapsible table where every row gives the paper title linked to its arXiv PDF, a one to three sentence summary of what the paper investigates or claims, and a badge linking to the arXiv abstract page with the identifier. Summaries state the mechanism and, where the paper reports them, headline results, for example dynamic rewiring of agent-to-agent connections by semantic matching at each reasoning round, conformal prediction used to filter noisy inter-agent messages in multi-robot coordination, self-evolving long-running multi-agent systems built on shared persistent memory and asynchronous execution, benchmarks for buyer-seller negotiation between LLM agents, and analyses of emergent social structure among tens of thousands of autonomous agents on a social platform. The repository contains no code, only the annotated index in the README. It is aimed at engineers building agent systems, researchers surveying architectures and developers integrating LLM agents into products who want a filtered view of recent literature instead of raw arXiv feeds. Contributions come through pull requests, and the list follows the awesome list conventions.
https://github.com/VoltAgent/awesome-ai-agent-papers
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