4 papers · 1 filter
Multi-Objective Alignment of Large Language Models Through Hypervolume Maximization
Subhojyoti Mukherjee, Anusha Lalitha, Sailik Sengupta +2
Multi-objective alignment from human feedback (MOAHF) in large language models (LLMs) is a challenging problem as human preferences are complex, multifaceted, and often conflicting…
Online Posterior Sampling with a Diffusion Prior
Branislav Kveton, Boris Oreshkin, Youngsuk Park +2
Posterior sampling in contextual bandits with a Gaussian prior can be implemented exactly or approximately using the Laplace approximation. The Gaussian prior is computationally ef…
Experimental Design for Active Transductive Inference in Large Language Models
Subhojyoti Mukherjee, Anusha Lalitha, Aniket Deshmukh +3
One emergent ability of large language models (LLMs) is that query-specific examples can be included in the prompt at inference time. In this work, we use active learning for adapt…
Optimal Design for Human Preference Elicitation
Subhojyoti Mukherjee, Anusha Lalitha, Kousha Kalantari +4
Learning of preference models from human feedback has been central to recent advances in artificial intelligence. Motivated by the cost of obtaining high-quality human annotations,…