Elicit: AI for scientific research

Machine learning

Planning is unsolved

May 4, 2026
Models are getting better at long-horizon tasks. So why don't they help much when you're planning clinical development or thinking through a launch?

Against RL: The Case for System 2 Learning

Jan 30, 2025
Reinforcement learning may boost LLMs today, but it cannot deliver safe, long-term intelligence. We argue for System 2 learning instead.

Trust at scale: Auto-evaluation for high-stakes LLM accuracy

Jul 23, 2024
Elicit develops LLM-based auto-evals to balance scale, trust, and flexibility, ensuring reliable scientific reasoning at superhuman speed.

Factored Verification: Detecting and Reducing Hallucinations in Frontier Models Using AI Supervision

Oct 20, 2023
We evaluate an automated approach for catching hallucinations in paper abstracts, aiming for consistently more trustworthy results.