AutoResearchClaw: Fully Autonomous Self-Evolving Research Agent (Idea to Paper)
AutoResearchClaw is an open-source Python project from aiming-lab that claims to automate the full research pipeline from idea to paper, positioning itself as a fully autonomous and self-evolving research agent. The repository has accumulated 12,426 stars with 55 added today, indicating notable community traction. It represents a concrete implementation in the growing space of AI agents designed to conduct and write scientific research autonomously.
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ARIS: Lightweight autonomous ML research agent using Markdown-only skills
ARIS (Auto-Research-In-Sleep) is an open-source Python project providing lightweight, framework-free Markdown-based skills for autonomous ML research workflows, including cross-model review loops, idea discovery, and experiment automation. It is designed to work with any LLM agent backend including Claude Code, Codex, or others. The project has accumulated 11,791 GitHub stars with notable daily traction (+106), suggesting meaningful community adoption.
karpathy/autoresearch: AI Agents for Automated Single-GPU Research
Andrej Karpathy's autoresearch repository on GitHub has accumulated over 82,000 stars, with 332 new stars today. The project focuses on AI agents that autonomously run research experiments on single-GPU nanochat training setups. The high star count and trending activity suggest significant community interest in automated ML research tooling.
OpenAI Introduces Deep Research Agent
OpenAI has launched 'deep research,' an agentic capability that uses reasoning to synthesize large volumes of online information and complete multi-step research tasks autonomously. The feature is initially available to ChatGPT Pro users, with rollout to Plus and Team tiers to follow. It represents a step toward practical autonomous research agents built on OpenAI's reasoning model infrastructure.
PaperBench: OpenAI Benchmark for Evaluating AI Agents on Research Replication
OpenAI introduces PaperBench, a benchmark designed to evaluate AI agents' ability to replicate state-of-the-art AI research papers end-to-end. The benchmark targets a high-complexity capability: reproducing experimental results from frontier AI research, which requires code generation, experimental design, and scientific reasoning. This positions PaperBench as a tool for tracking progress toward autonomous AI research agents.
Open-source DeepResearch – Freeing our search agents
Hugging Face published a blog post introducing Open Deep Research, an open-source replication of agentic deep research capabilities (similar to OpenAI's Deep Research). The project aims to build open-weight search agents capable of multi-step web research and synthesis. The post details the architecture, tooling, and early benchmark results of the system.
Microsoft RD-Agent: automated AI-driven R&D for data and model development
Microsoft has released RD-Agent, an open-source Python framework aimed at automating high-value R&D processes in AI, with a focus on data and model development. The project positions AI as the driver of data-driven AI workflows, targeting industrial productivity use cases. With 13,500 GitHub stars, it has attracted meaningful community interest, and a technical report is available.
last30days-skill: AI agent skill for multi-source research synthesis
A Python-based AI agent skill on GitHub that queries Reddit, X, YouTube, Hacker News, Polymarket, and the web to research any topic, then synthesizes a grounded summary. The repository has accumulated 27,522 stars with 173 added today, indicating significant community traction. It represents a practical agent tool for multi-source information aggregation.
AiraXiv: AI-Driven Open-Access Publishing Platform for Human and AI Scientists
AiraXiv is a proposed open-access academic publishing platform designed to accommodate both human and AI-generated research outputs, addressing scalability challenges in traditional peer review. The platform supports AI scientists via Model Context Protocol (MCP)-based interactions and human scientists through an interactive UI, with papers evolving through continuous feedback-driven iteration. It was validated through real-world deployment as the submission platform for ICAIS 2025. The work positions itself as infrastructure for a future where AI agents are first-class participants in the scientific publishing ecosystem.