Microsoft published RetroChimera, a retrosynthesis prediction framework, in Nature and open-sourced its implementation and weights. It combines the Transformer model R-SMILES 2 with GNN-based NeuralLoc, using a learned ensemble to rerank predictions. Chemists preferred its single-step reaction predictions in blind testing.
Google Research released MilleMiglia, a C++ generator of realistic, privacy-preserving benchmark instances for middle-mile logistics delivery. Source and documentation are public on GitHub.
METR research shows AI's effects on scientific discovery are uneven: cybersecurity vulnerability reporting accelerated sharply in 2026 compared with 2025, mathematics accelerated only modestly, and algorithmic progress in AI research itself showed no significant acceleration. A multi-university team proposed SPADE, alternating LLM generation of executable training environments with solving them. Qwen3-30B-A3B averaged 58.3 on the game-environment suite, 8.1 above baseline.
Hugging Face released ScarfBench (Self-Contained Application Refactoring Benchmark) to evaluate AI agents migrating enterprise Java applications between Spring, Jakarta EE and Quarkus.
Hugging Face proposed DiScoFormer (Density and Score Transformer), estimating a distribution's density and score simultaneously in one forward pass from a set of data points, without retraining for new distributions.
Import AI 457 focuses on three studies. SentinelOne analysed fast16.sys, malware from over 20 years ago that sabotages engineering and physics simulations by altering in-memory results from precision software such as LS-DYNA 970, PKPM and MOHID.
Google Research proposed MoGen (Neuronal Morphology Generation), using PointInfinity point-cloud flow matching to generate synthetic neuronal shapes and supplement PATHFINDER reconstruction training. It reduced reconstruction error by 4.4% on held-out mouse axons, mainly by reducing merge errors.