An Adversarial Example for Direct Logit Attribution: Memory Management in GELU-4L

Fuente: arXiv
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Main Authors: Janiak, Jett, Rager, Can, Dao, James, Lau, Yeu-Tong
Format: Preprint
Published: 2023
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author Janiak, Jett
Rager, Can
Dao, James
Lau, Yeu-Tong
author_facet Janiak, Jett
Rager, Can
Dao, James
Lau, Yeu-Tong
contents Prior work suggests that language models manage the limited bandwidth of the residual stream through a "memory management" mechanism, where certain attention heads and MLP layers clear residual stream directions set by earlier layers. Our study provides concrete evidence for this erasure phenomenon in a 4-layer transformer, identifying heads that consistently remove the output of earlier heads. We further demonstrate that direct logit attribution (DLA), a common technique for interpreting the output of intermediate transformer layers, can show misleading results by not accounting for erasure.
format Preprint
id arxiv_https___arxiv_org_abs_2310_07325
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle An Adversarial Example for Direct Logit Attribution: Memory Management in GELU-4L
Janiak, Jett
Rager, Can
Dao, James
Lau, Yeu-Tong
Machine Learning
Artificial Intelligence
Prior work suggests that language models manage the limited bandwidth of the residual stream through a "memory management" mechanism, where certain attention heads and MLP layers clear residual stream directions set by earlier layers. Our study provides concrete evidence for this erasure phenomenon in a 4-layer transformer, identifying heads that consistently remove the output of earlier heads. We further demonstrate that direct logit attribution (DLA), a common technique for interpreting the output of intermediate transformer layers, can show misleading results by not accounting for erasure.
title An Adversarial Example for Direct Logit Attribution: Memory Management in GELU-4L
topic Machine Learning
Artificial Intelligence
url https://arxiv.org/abs/2310.07325