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AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

Hugging Face Daily Papers · 2026-05-19 Cached

AutoResearchClaw is a multi-agent autonomous research system that improves scientific discovery through structured debate, self-healing execution, and human collaboration, outperforming previous systems on the ARC-Bench benchmark by 54.7%.

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#autonomous-research

@ChrisHayduk: GPT 5.5 is an effective autoresearcher in structural biology! I've had goal mode running for over 150 hours straight, l…

X AI KOLs Timeline · 2026-05-16 Cached

A user reports that GPT 5.5 successfully conducts autonomous research in structural biology, improving AlphaFold2's performance after 150+ hours of goal mode.

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#autonomous-research

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

Papers with Code Trending · 2026-05-04 Cached

ARIS is an open-source research harness that uses cross-model adversarial collaboration to ensure reliable long-term research outcomes through coordinated execution, orchestration, and assurance layers.

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Deep Research Max: a step change for autonomous research agents | New from Deepmind

Reddit r/singularity · 2026-04-22 Cached

Deepmind's upgraded Gemini Deep Research dramatically accelerates scientific literature review, autonomously synthesizing multi-modal data and reshaping workflows in finance, biotech, and consulting.

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@GoogleDeepMind: Deep Research and Deep Research Max are our latest autonomous research agents powered by Gemini 3.1 Pro. They can safel…

X AI KOLs · 2026-04-21 Cached

Google DeepMind launched Deep Research and Deep Research Max, autonomous agents using Gemini 3.1 Pro to browse web and custom data for professional, fully-cited reports.

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@omarsar0: Karpathy's autoresearch repo started an impressive trend. Agents can now train AI models to build SoTA agentic systems.…

X AI KOLs Following · 2026-04-21 Cached

Karpathy's autoresearch repository has sparked a trend where agents train AI models to build state-of-the-art agentic systems, highlighting current limitations in LLM-driven hypothesis generation.

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EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

Papers with Code Trending · 2026-03-09 Cached

EvoScientist is an adaptive multi-agent framework for end-to-end scientific discovery that continuously improves through persistent memory modules, comprising three specialized agents for idea generation, experiment execution, and knowledge distillation. It outperforms 7 state-of-the-art systems in scientific idea generation and improves code execution success rates through multi-agent evolution.

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