430 citations · 817 across the 12 of their papers we have counts for
3 papers · 1 filter
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Han Zhou, Xingchen Wan, Lev Proleev +4
Prompting and in-context learning (ICL) have become efficient learning paradigms for large language models (LLMs). However, LLMs suffer from prompt brittleness and various bias fac…
STUDY: Socially Aware Temporally Causal Decoder Recommender Systems
Eltayeb Ahmed, Diana Mincu, Lauren Harrell +2
Recommender systems are widely used to help people find items that are tailored to their interests. These interests are often influenced by social networks, making it important to…
Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression
Alexander Norcliffe, Lev Proleev, Diana Mincu +3
Multiple sclerosis is a disease that affects the brain and spinal cord, it can lead to severe disability and has no known cure. The majority of prior work in machine learning for m…