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Abraham J. Fetterman

3 papers hereh-index 384 citations3 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CL1

identity via Semantic Scholar / OpenAlex

most citedDespite "super-human" performance, current LLMs are unsuited for decisions about ethics and safety

7 citations · 11 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2023★ 4 cited

Tune As You Scale: Hyperparameter Optimization For Compute Efficient Training

Abraham J. Fetterman, Ellie Kitanidis, Joshua Albrecht +6

Hyperparameter tuning of deep learning models can lead to order-of-magnitude performance gains for the same amount of compute. Despite this, systematic tuning is uncommon, particul…

cs.LG2023

On the Stepwise Nature of Self-Supervised Learning

James B. Simon, Maksis Knutins, Liu Ziyin +3

We present a simple picture of the training process of joint embedding self-supervised learning methods. We find that these methods learn their high-dimensional embeddings one dime…

cs.CL2022★ 7 cited

Despite "super-human" performance, current LLMs are unsuited for decisions about ethics and safety

Joshua Albrecht, Ellie Kitanidis, Abraham J. Fetterman

Large language models (LLMs) have exploded in popularity in the past few years and have achieved undeniably impressive results on benchmarks as varied as question answering and tex…

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