130 citations · 174 across the 4 of their papers we have counts for
7 papers
Active Learning Helps Pretrained Models Learn the Intended Task
Alex Tamkin, Dat Nguyen, Salil Deshpande +2
Models can fail in unpredictable ways during deployment due to task ambiguity, when multiple behaviors are consistent with the provided training data. An example is an object class…
C5T5: Controllable Generation of Organic Molecules with Transformers
Daniel Rothchild, Alex Tamkin, Julie Yu +2
Methods for designing organic materials with desired properties have high potential impact across fields such as medicine, renewable energy, petrochemical engineering, and agricult…
Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models
Alex Tamkin, Miles Brundage, Jack Clark +1
On October 14th, 2020, researchers from OpenAI, the Stanford Institute for Human-Centered Artificial Intelligence, and other universities convened to discuss open research question…
Language Through a Prism: A Spectral Approach for Multiscale Language Representations
Alex Tamkin, Dan Jurafsky, Noah Goodman
Language exhibits structure at different scales, ranging from subwords to words, sentences, paragraphs, and documents. To what extent do deep models capture information at these sc…
Viewmaker Networks: Learning Views for Unsupervised Representation Learning
Alex Tamkin, Mike Wu, Noah Goodman
Many recent methods for unsupervised representation learning train models to be invariant to different "views," or distorted versions of an input. However, designing these views re…
Investigating Transferability in Pretrained Language Models
Alex Tamkin, Trisha Singh, Davide Giovanardi +1
How does language model pretraining help transfer learning? We consider a simple ablation technique for determining the impact of each pretrained layer on transfer task performance…