7 citations · 12 across the 5 of their papers we have counts for
5 papers
Steerable Pluralism: Pluralistic Alignment via Few-Shot Comparative Regression
Jadie Adams, Brian Hu, Emily Veenhuis +5
Large language models (LLMs) are currently aligned using techniques such as reinforcement learning from human feedback (RLHF). However, these methods use scalar rewards that can on…
ALIGN: Prompt-based Attribute Alignment for Reliable, Responsible, and Personalized LLM-based Decision-Making
Bharadwaj Ravichandran, David Joy, Paul Elliott +6
Large language models (LLMs) are increasingly being used as decision aids. However, users have diverse values and preferences that can affect their decision-making, which requires…
LEARN: A Unified Framework for Multi-Task Domain Adapt Few-Shot Learning
Bharadwaj Ravichandran, Alexander Lynch, Sarah Brockman +4
Both few-shot learning and domain adaptation sub-fields in Computer Vision have seen significant recent progress in terms of the availability of state-of-the-art algorithms and dat…
From Kinematics To Dynamics: Estimating Center of Pressure and Base of Support from Video Frames of Human Motion
Jesse Scott, Christopher Funk, Bharadwaj Ravichandran +3
To gain an understanding of the relation between a given human pose image and the corresponding physical foot pressure of the human subject, we propose and validate two end-to-end…
Learning Dynamics from Kinematics: Estimating 2D Foot Pressure Maps from Video Frames
Christopher Funk, Savinay Nagendra, Jesse Scott +4
Pose stability analysis is the key to understanding locomotion and control of body equilibrium, with applications in numerous fields such as kinesiology, medicine, and robotics. In…