[2202. 05262] Locating and Editing Factual Associations in GPT We analyze the storage and recall of factual associations in autoregressive transformer language models, finding evidence that these associations correspond to localized, directly-editable computations
Locating and Editing Factual Associations in GPT We analyze the storage and recall of factual associations in autoregressive trans-former language models, finding evidence that these associations correspond to localized, directly-editable computations
[2202. 05262] Locating and Editing Factual Associations in GPT - ar5iv In this paper, we investigate how such factual associations are stored within GPT-like autoregressive transformer models Although many of the largest neural networks in use today are autoregressive, the way that they store knowledge remains under-explored
Locating and Editing Factual Associations in GPT - NIPS We analyze the storage and recall of factual associations in autoregressive transformer language models, finding evidence that these associations correspond to localized, directly-editable computations