January 18, 2026

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

blue click pen on top of gray book near clear drinking glass
Bookblock / Unsplash

Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works weren't about a single breakthrough model. Ins...