2 papers
cs.LG2024
Can Custom Models Learn In-Context? An Exploration of Hybrid Architecture Performance on In-Context Learning Tasks
Ryan Campbell, Nelson Lojo, Kesava Viswanadha +5
In-Context Learning (ICL) is a phenomenon where task learning occurs through a prompt sequence without the necessity of parameter updates. ICL in Multi-Headed Attention (MHA) with…
econ.EM2024
Random Utility Models with Skewed Random Components: the Smallest versus Largest Extreme Value Distribution
Richard T. Carson, Derrick H. Sun, Yixiao Sun
At the core of most random utility models (RUMs) is an individual agent with a random utility component following a largest extreme value Type I (LEVI) distribution. What if, inste…