Discovery Foundation Models aim at open-ended AI scientific discovery
Ling Yang · hf · 2026-09-15
Discovery Foundation Models target open-ended scientific discovery through an iterative loop of problem formulation, hypothesis testing, and evidence-based revision, spanning both dry and wet lab settings—modeling the research process itself rather than single-shot scientific QA.
More from Research
- BVB benchmark tests agent video understanding by rebuilding 288 real videos in Blender — SonglinYang4 · 2026-09-15
- Stanford Bioengineering opens tenure-track faculty search, applications due Sept 30 — anshulkundaje · 2026-09-15
- Terence Tao's inverse Galois AI challenge completes its first stage — tak3sh8 · 2026-09-15
- Training from scratch on a single H100 hits 76% on ARC-AGI-1 in ~4 hours — GregKamradt · 2026-09-15
- First cryptanalytic extraction of neural networks without knowing their architecture — chaumian · 2026-09-15
- Poison set choice swings LLM backdoor attack success from 3% to 80%, SAILS paper shows — chaumian · 2026-09-15