Researchers from Princeton, Ant Group and Stanford Introduce AQuA: A Two-Part Agentic Framework for Autonomous Factor Discovery and Model Development in Quantitative Finance

Quantitative research agents that write their own experiments can corrupt the evidence they later learn from. A leaky feature that […]

Google AI Introduces EnvHarness: A Programmable Layer That Turns Static Agent Environments Into Adaptive Training Worlds

A team of researchers from Google Cloud AI Research, Washington University in St. Louis and UNC Chapel Hill has released […]

Liquid AI Open-Sources Pipette: A Reproducible Benchmarking Suite That Measures On-Device Models, Quantization, Runtime and Hardware Together

Model cards report quality under server-class, full-precision conditions. Those numbers rarely predict how the same model behaves on a phone. […]