7 citations · 17 across the 21 of their papers we have counts for
4 papers · 1 filter
On the steerability of large language models toward data-driven personas
Junyi Li, Ninareh Mehrabi, Charith Peris +5
Large language models (LLMs) are known to generate biased responses where the opinions of certain groups and populations are underrepresented. Here, we present a novel approach to…
Coordinated Replay Sample Selection for Continual Federated Learning
Jack Good, Jimit Majmudar, Christophe Dupuy +5
Continual Federated Learning (CFL) combines Federated Learning (FL), the decentralized learning of a central model on a number of client devices that may not communicate their data…
Holistic Survey of Privacy and Fairness in Machine Learning
Sina Shaham, Arash Hajisafi, Minh K Quan +6
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML). Each objective has been independently studied in the…
Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning
Mustafa Safa Ozdayi, Charith Peris, Jack FitzGerald +5
Large Language Models (LLMs) are known to memorize significant portions of their training data. Parts of this memorized content have been shown to be extractable by simply querying…