2 papers
cs.CL2023
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…
cs.SI2023
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…