# Bad Influence story: Nvidia-led paper traces irrelevant-context errors to a small set of attention heads

Active · 1 article · 1 source · First reported 11-09 23:38. Times are ET.
Story page: https://badinfluence.news/story/a57ea7cc-8bce-40a7-a0c6-1f96af28019e

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[Bad Influence external source material begins]
Latest update (11-09 23:38): Nvidia-led paper finds irrelevant context weakens models through intrusion attention heads

Overview: A paper from Nvidia and other labs finds that irrelevant text mainly weakens a model's use of the question, rather than directly pushing against the correct answer. The authors identify a small set of attention heads, which they call intrusion heads, that read unrelated text and reduce support for the right answer. Per the X post by Rohan Paul summarizing the paper, masking about 10 heads on 7B-scale models across four tasks recovered 57% of the accuracy lost to distractors.

Coverage timeline (newest first):
1. 11-09 23:38 · Rohan Paul · [Nvidia-led paper finds irrelevant context weakens models through intrusion attention heads](https://badinfluence.news/items/tl3uo16122iak9j41vv621k4r)
[Bad Influence external source material ends]

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