arXiv AI
AgentIdeaBench: Benchmarking Scientific Ideation in the Agent Era
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Oct 27
DISCERN: Can AI Agents Work Like Scientists and Guide Discovery?
arXiv:2609.33357v2 Announce Type: replace Abstract: Reliable automated research requires agents to vet data, verify analyses, and generate hypotheses grounded in trustworthy evidence, potentially red...
arXiv AI
Jul 14
FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights
arXiv:2602. 02905v2 Announce Type: replace Abstract: Autonomous agents powered by large language models (LLMs) promise to accelerate scientific discovery end-to-end, but rigorously evaluating their capacity for verifiable discovery remains a central challenge.
arXiv Machine Learning
Oct 22
Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?
arXiv:2610.28763v1 Announce Type: cross Abstract: Frontier coding agents are increasingly framed as end-to-end automated researchers, and ML for science offers a demanding test of that promise: impro...
arXiv AI
Jun 8
Act As a Real Researcher: A Suite of Benchmarks Evaluating Frontier LLMs and Agentic Harnesses in Research Lifecycle
arXiv:2606. 07462v1 Announce Type: new Abstract: As foundation models advance and agent scaffolding becomes increasingly sophisticated, agents have demonstrated remarkable proficiency in complex, long-horizon coding tasks and even autonomous experiment execution.
arXiv AI
Oct 1
AIM: Agentic Idea Management for Automated Research
arXiv:2609.38445v1 Announce Type: new Abstract: Frontier LLMs are increasingly used to automate scientific research through iterative search. We distinguish idea-driven search from solution-driven se...
arXiv AI
Jun 9
EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale
arXiv:2604. 17406v3 Announce Type: replace Abstract: The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science.