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Why do universal adversarial attacks work on large language models?: Geometry might be the answer
We believe this new geometric perspective on the underlying mechanism driving universal attacks could help us gain deeper insight into the internal workings and failure modes of LLMs, thus enabling their mitigation.
Can Large Language Models Change User Preference Adversarially?
Pretrained large language models (LLMs) are becoming increasingly powerful and ubiquitous in mainstream applications such as being a personal assistant, a dialogue model, etc.
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations
In this work, we survey properties defined in interpretable machine learning papers, synthesize them based on what they actually measure, and describe the trade-offs between different formulations of these properties.
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