4 papers
MINT: A Universal Zero-Shot Predictor for Transaction Data
Parameswaran Kamalaruban, Viktor Drobnyi, Maeve Madigan +3
Banks analyse sequential financial transaction data to perform many tasks, including fraud prevention, credit risk assessment and offer personalization. To improve the predictive a…
DMAP: A Distribution Map for Text
Tom Kempton, Julia Rozanova, Parameswaran Kamalaruban +5
Large Language Models (LLMs) are a powerful tool for statistical text analysis, with derived sequences of next-token probability distributions offering a wealth of information. Ext…
Emergent Bias and Fairness in Multi-Agent Decision Systems
Maeve Madigan, Parameswaran Kamalaruban, Glenn Moynihan +3
Multi-agent systems have demonstrated the ability to improve performance on a variety of predictive tasks by leveraging collaborative decision making. However, the lack of effectiv…
Fairness-Aware Low-Rank Adaptation Under Demographic Privacy Constraints
Parameswaran Kamalaruban, Mark Anderson, Stuart Burrell +3
Pre-trained foundation models can be adapted for specific tasks using Low-Rank Adaptation (LoRA). However, the fairness properties of these adapted classifiers remain underexplored…