3 citations · 4 across the 3 of their papers we have counts for
3 papers · 1 filter
Distinguishing the Knowable from the Unknowable with Language Models
Gustaf Ahdritz, Tian Qin, Nikhil Vyas +2
We study the feasibility of identifying epistemic uncertainty (reflecting a lack of knowledge), as opposed to aleatoric uncertainty (reflecting entropy in the underlying distributi…
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
Benjamin L. Edelman, Ezra Edelman, Surbhi Goel +2
Large language models have the ability to generate text that mimics patterns in their inputs. We introduce a simple Markov Chain sequence modeling task in order to study how this i…
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck
Benjamin L. Edelman, Surbhi Goel, Sham Kakade +2
In modern deep learning, algorithmic choices (such as width, depth, and learning rate) are known to modulate nuanced resource tradeoffs. This work investigates how these complexiti…