4 papers
When Should an AI Scientist Stop? Verifiable Experiment Steering and Refusal for Autonomous Discovery
Neel Tushar Shah, Manglam Kartik
We present CARTOGRAPH, a verification layer for AI scientists that couples unresolved-subspace experiment steering (select), explicit ambiguity closure (resolve), and residual-base…
Light Cones For Vision: Simple Causal Priors For Visual Hierarchy
Manglam Kartik, Neel Tushar Shah
Standard vision models treat objects as independent points in Euclidean space, unable to capture hierarchical structure like parts within wholes. We introduce Worldline Slot Attent…
Atlas 2 -- Foundation models for clinical deployment
Maximilian Alber, Timo Milbich, Alexandra Carpen-Amarie +24
Pathology foundation models substantially advanced the possibilities in computational pathology --- yet tradeoffs in terms of performance, robustness, and computational requirement…
Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics
Maximilian Alber, Stephan Tietz, Jonas Dippel +24
Recent advances in digital pathology have demonstrated the effectiveness of foundation models across diverse applications. In this report, we present Atlas, a novel vision foundati…