106 citations · 117 across the 4 of their papers we have counts for
4 papers
PrivacyAlign: Contextual Privacy Alignment for LLM Agents
Manveer Singh Tamber, Abhay Puri, Marc-Etienne Brunet +3
AI agents acting on behalf of users are constantly making decisions, and for users to trust their agents, those decisions must align with what they actually want. Privacy is an imp…
ICL Markup: Structuring In-Context Learning using Soft-Token Tags
Marc-Etienne Brunet, Ashton Anderson, Richard Zemel
Large pretrained language models (LLMs) can be rapidly adapted to a wide variety of tasks via a text-to-text approach, where the instruction and input are fed to the model in natur…
RelatIF: Identifying Explanatory Training Examples via Relative Influence
Elnaz Barshan, Marc-Etienne Brunet, Gintare Karolina Dziugaite
In this work, we focus on the use of influence functions to identify relevant training examples that one might hope "explain" the predictions of a machine learning model. One short…
Understanding the Origins of Bias in Word Embeddings
Marc-Etienne Brunet, Colleen Alkalay-Houlihan, Ashton Anderson +1
The power of machine learning systems not only promises great technical progress, but risks societal harm. As a recent example, researchers have shown that popular word embedding a…