1 citations · 1 across the 3 of their papers we have counts for
3 papers
A Taxonomy for Data Contamination in Large Language Models
Medha Palavalli, Amanda Bertsch, Matthew R. Gormley
Large language models pretrained on extensive web corpora demonstrate remarkable performance across a wide range of downstream tasks. However, a growing concern is data contaminati…
Improving Autoregressive Training with Dynamic Oracles
Jianing Yang, Harshine Visvanathan, Yilin Wang +2
Many tasks within NLP can be framed as sequential decision problems, ranging from sequence tagging to text generation. However, for many tasks, the standard training methods, inclu…
It's MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk
Amanda Bertsch, Alex Xie, Graham Neubig +1
Minimum Bayes Risk (MBR) decoding is a method for choosing the outputs of a machine learning system based not on the output with the highest probability, but the output with the lo…