Track papers across labs, topics, and trends.
Search papers, labs, and topics across Lattice.
2
0
3
Transformers can be quantitatively predicted by a Bayesian reference, revealing their failure modes on complex, interdependent sequential data.
A new Bayesian estimator achieves competitive performance with established methods while being remarkably simple and tuneless, revealing critical scaling laws in data discovery.