178 citations · 247 across the 5 of their papers we have counts for
5 papers
Linearity of Relation Decoding in Transformer Language Models
Evan Hernandez, Arnab Sen Sharma, Tal Haklay +5
Much of the knowledge encoded in transformer language models (LMs) may be expressed in terms of relations: relations between words and their synonyms, entities and their attributes…
Mass-Editing Memory in a Transformer
Kevin Meng, Arnab Sen Sharma, Alex Andonian +2
Recent work has shown exciting promise in updating large language models with new memories, so as to replace obsolete information or add specialized knowledge. However, this line o…
Exploiting and Defending Against the Approximate Linearity of Apple's NeuralHash
Jagdeep Singh Bhatia, Kevin Meng
Perceptual hashes map images with identical semantic content to the same -bit hash value, while mapping semantically-different images to different hashes. These algorithms carry…
Locating and Editing Factual Associations in GPT
Kevin Meng, David Bau, Alex Andonian +1
We analyze the storage and recall of factual associations in autoregressive transformer language models, finding evidence that these associations correspond to localized, directly-…
Gradient-Based Adversarial Training on Transformer Networks for Detecting Check-Worthy Factual Claims
Kevin Meng, Damian Jimenez, Fatma Arslan +3
We present a study on the efficacy of adversarial training on transformer neural network models, with respect to the task of detecting check-worthy claims. In this work, we introdu…