28 citations · 87 across the 22 of their papers we have counts for
4 papers · 1 filter
Continued Pretraining for Better Zero- and Few-Shot Promptability
Zhaofeng Wu, Robert L. Logan, Pete Walsh +4
Recently introduced language model prompting methods can achieve high accuracy in zero- and few-shot settings while requiring few to no learned task-specific parameters. Neverthele…
Modeling Context With Linear Attention for Scalable Document-Level Translation
Zhaofeng Wu, Hao Peng, Nikolaos Pappas +1
Document-level machine translation leverages inter-sentence dependencies to produce more coherent and consistent translations. However, these models, predominantly based on transfo…
Transparency Helps Reveal When Language Models Learn Meaning
Zhaofeng Wu, William Merrill, Hao Peng +2
Many current NLP systems are built from language models trained to optimize unsupervised objectives on large amounts of raw text. Under what conditions might such a procedure acqui…
Learning with Latent Structures in Natural Language Processing: A Survey
Zhaofeng Wu
While end-to-end learning with fully differentiable models has enabled tremendous success in natural language process (NLP) and machine learning, there have been significant recent…