DiscoPER uses code generation, statistical validation, and second-order meta-reflection on accumulated discoveries to recover 8 of 9 known ecological patterns on a new benchmark at 72.7% support rate.
Biodsa-1k: Benchmarking data science agents for biomedical research
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DeepER-Med introduces a three-module agentic AI workflow for evidence-based medical research that outperforms production platforms on a new expert-curated dataset of 100 questions and matches clinical recommendations in seven of eight real-world cases.
A survey organizing AI-powered research automation into five workflow stages, defining AutoResearch and Vibe Research, and proposing five evaluation dimensions while noting domain-conditioned limits on autonomy.
citing papers explorer
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Autonomous Scientific Discovery via Iterative Meta-Reflection
DiscoPER uses code generation, statistical validation, and second-order meta-reflection on accumulated discoveries to recover 8 of 9 known ecological patterns on a new benchmark at 72.7% support rate.
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DeepER-Med: Advancing Deep Evidence-Based Research in Medicine Through Agentic AI
DeepER-Med introduces a three-module agentic AI workflow for evidence-based medical research that outperforms production platforms on a new expert-curated dataset of 100 questions and matches clinical recommendations in seven of eight real-world cases.
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AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery
A survey organizing AI-powered research automation into five workflow stages, defining AutoResearch and Vibe Research, and proposing five evaluation dimensions while noting domain-conditioned limits on autonomy.